title: Mouse thymus stage 1 B6 iNKT scATAC-seq

city: Detroit

first: Indra

last: Adrianto

state: MI

address: 1 Ford Place

department: Public Health Sciences

institute: Henry Ford Health System

description: Stage 1 iNKT cells from B6 mouse thymus (sample 1)

data_processing:
Sequenced reads from scATAC-seq libraries were processed using the 10X Genomics Cell Ranger ATAC (v1.0.1).
Raw sequencing reads were demultiplexed and converted into FASTQ files usjng the cellranger-atac mkfastq pipeline. Then, the sequencing reads underwent the cellranger-atac count pipeline consisting of read filtering, alignment to the reference genome using STAR, barcode counting, identification of transposase cut sites and accessible chromatin peaks, cell calling, generation of count matrices for chromatin peaks and transcription factors.
Estimated number of cells captured per sample were between 2,536 - 11,015 with 11,401 - 16,343 median fragments per cell and 55,349 - 87,603 total peaks detected.
Each sample has  4 oligos  with 3 FASTQ files of Read1 (R1), i5 barcode index (R2), Read2 (R3), and i7 sample index (I1). To generate the  single-cell accessibility counts, we utilized the following command using the Cell Ranger ATAC in a Linux terminal: cellranger-atac count --id=<Sample_name> --sample=<Sample_name> --fastqs=<Path_to_fastq_files> --reference=<Path_to_Cell_Ranger_ATAC_compatible_genome_reference>
Genome_build: mm10
Supplementary_files_format_and_content: Cell Ranger ATAC outputs of barcodes, peak-barcode matrix, peaks, filtered peak barcode matrix in HDF5 format, barcoded and aligned fragments, fragment file index, per-barcode fragment counts and metrics.
TSV: Barcodes
MTX: Peak-barcode Matrix
BED: Peaks
H5: Filtered Peak Barcode Matrix in HDF5 Format
TSV.GZ: Barcoded and Aligned Fragments
TSV.GZ.TBI: Barcoded and Aligned Fragment File Index
CSV: Per-barcode Fragment Counts and Metrics

source_name: Thymus

extract_protocol:
Murine thymi were harvested from 5 weeks old C57BL/6 mice or Vα14 transgenic mice. The thymus iNKT cells were enriched by positive selection using biotinylated antibodies against PE. Stage 1(CD24-CD44-NK1.1-), stage 2(CD24-CD44+NK1.1-) and stage 3(CD24-CD44+NK1.1+) were sorted  from 5 weeks C57BL/6 mouse thymus, and Stage 0 iNKT cells (CD24+NK1.1-) were sorted from 5 weeks old Vα14 transgenic mouse thymus through BD FACS AriaII.
FACS-sorted NKT cells from B6 (stages 0, 1, 2, and 3) and Vα14 transgenic (stage 0) mouse thymi were used to generate Chromium Single Cell ATAC Libraries following the recommended protocol (10x Genomics, Pleasanton, CA). Briefly, after isolating, washing, and counting of nuclei suspensions, the recovered nuclei were combined with the ATAC buffer and enzyme to create a transposition mix in a tube and incubated at 37°C for 60 minutes. A master mix that include the barcoding reagent, reducing agent, and barcoding enzyme was then added to the same tube. This solution was loaded into the 10x Genomics Chromium Single Cell Controller instrument along with the vortexed single-cell ATAC gel beads and partition oil. The resulting GEMs were amplified in a Thermocycler (Veriti™ 96-Well Fast Thermal Cycler, Applied Biosynthesis; 72°C for 5 min, 98°C for 30 s, cycled 12x: 98°C for 10 s, 59°C for 30 s, and 72°C for 1 min). After cleaning up using the Recovery Agent, Dynabeads MyOne Silane, and SPRIselect Reagent, the resulting accessible DNA fragments underwent the barcoded and indexed sequencing library construction. These scATAC-seq libraries were sequenced on the Illumina NovaSeq 6000 using paired-end flow cells (50 bp Read 1, 8 bp i7 index, 16 bp i5 index, and 49 bp Read 2) by the University of Michigan DNA Sequencing Core facility following the manufacturer’s protocol.

value: Thymus

value: Invariant natural killer T cells (iNKT) cells

tag: age

value: 5 weeks

tag: developmental stage

value: stage 1


title: 2-Disease-B9

status: Public on Jun 27 2023

type: SRA

city: Gent

first: Anne-Sofie

last: Vermeersch

address: Ottergemsesteenweg 46

country: Belgium

institute: Ghent University

description: Disease sample

library_source: transcriptomic

data_processing:
Quality and length of raw sequencing reads inspection with FastQc (v0.11.7). Fastq_screen was utilized for putative contamination check.
Adaptor and quality trimming with cutadapt (v2.8).
The reads were mapped on the Bos_taurus_ARS-UCD1.2 cow reference genome using splice-aware Spliced Transcripts Alignment to a Reference (STAR) (v2.5.3a) mapper.
Features were counted at the gene and transcript isoform level using rsem_calc_expression (RSEM v1.3.1).
An analysis was done by comparing the healthy samples with the severe lesion samples, using the edgeR package in R.
Assembly: Bos_taurus_ARS-UCD1.2
Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample

molecule: total RNA

organism: Bos taurus

source_name: Skin

extract_protocol:
Samples were taken with a biopsy punch tool and flash frozen in liquid nitrogen. RNA isolation was performed using the Qiagen RNeasy Minikit (Qiagen Benelux, Venlo, the NL).
Sequencing libraries were constructed using the ‘QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina’ from Lexogen (Lexogen Inc, Greenland, NH, USA).

tag: tissue

value: Skin

tag: Sex

value: female

tag: breed

value: Holstein-Friesian


title: Mouse thymus stage 2 B6 iNKT scATAC-seq

country: USA

description: Stage 2 iNKT cells from B6 mouse thymus (sample 1)

library_source: genomic

molecule: genomic DNA

organism: Mus musculus

tag: strain

tag: cell type

value: stage 2


title: Methanol, control, biol rep 3

city: University Park

first: Elizabeth

last: Jolley

state: PA

address: 239 Chemistry Bldg, Pennsylvania State University

institute: Pennsylvania State University

data_processing:
All data processing steps were done using StrutureFold2
Library strategy: Structure-seq2

organism: Methanosarcina acetivorans C2A

extract_protocol:
Pelleted cells were resuspended in 1 mL of Trizol, and the RNA was extracted according to the Direct-zol RNA MiniPrep kit (Zymo Research).
DMS-treated total RNA is reverse transcribed using a random hexamer primer to generate cDNA that is prepared for sequencing by ligating a hairpin adapter and then PCR amplifying products while incorporating Illumina sequencing primers. Libraries are size-selected on a denaturing PAGE gel between 200-600 nucleotides and then submitted for sequencing.

tag: genotype

value: WT

tag: treatment

value: control


title: Sorted tissue lung ILCs, scRNAseq

city: Stockholm

first: Tim

last: Willinger

address: Center for Infectious Medicine (CIM), Alfred Nobels allé 8, level 7

department: Department of Medicine Huddinge

country: Sweden

institute: Karolinska Institutet

description: 10x Genomics

library_source: transcriptomic single cell

data_processing:
The demultiplexing, barcoded processing, gene counting, and aggregation were made using the Cell Ranger Pipeline v3.0.1
Assembly: GRCh38
Supplementary files format and content: 10X Genomics .h5 file (gene expression matrices)

molecule: polyA RNA

organism: Homo sapiens

source_name: Lung

growth_protocol: Newborn MISTRG mice were irradiated and transplanted by intrahepatic injection with human CD34+ HSPCs from umbilical cord blood. MISTRG mice were engrafted with pooled batches of human CD34+ cells to reduce the impact of HSPC donor variability. Two months after transplantation, lung cells were isolated. Before lung harvest, intravascular cell labeling was performed as described below. To obtain enough cells, lungs were pooled from ten MISTRG mice.

extract_protocol:
Human ILCs were purified as live CD45+CD127+CD94-CD3-TCRab-Lin- lymphocytes and divided into intravascular (IV-CD45-PE+) and extravascular (IV-CD45-PE-) ILCs. Human NK cells were purified as live CD45+CD127-CD94+CD3-TCRab-Lin- lymphocytes and divided into intravascular (IV-CD45-PE+) and extravascular (IV-CD45-PE-) NK cells. Lineage (Lin) markers included CD11c, CD14, CD19, CD34 CD123, FceRI. Further processing of sorted ILCs and NK cells (GEM generation, barcoding, cleanup, cDNA amplification) was performed using reagents and protocols from 10x Genomics Chromium Single Cell 3' Reagent kit v2.
Library construction was done using the 10x Genomics Chromium Single Cell 3' Reagent kit v2.

treatment_protocol: Intravascular cell labeling to distinguish vascular from tissue ILCs and NK cells was performed by injecting HSPC-engrafted MISTRG mice intravenously (IV) with a phycoerythrin (PE)-conjugated anti human CD45 antibody 5 minutes before lung harvest without any prior perfusion. Lungs were enzymatically digested, and lymphocytes isolated by density gradient centrifugation. ILCs and NK cells were then purified by immunomagnetic selection and cell sorting.

value: Lung

value: MISTRG humanized mouse

value: Lymphocyte

tag: cell population_characteristic

value: Live human CD45+ TCRab- CD3- Lineage- CD94- CD127+ i.v. CD45-


title: Mouse thymus stage 0 B6 iNKT scATAC-seq

description: Stage 0 iNKT cells from B6 mouse thymus (sample 1)

value: stage 0


title: 1-Disease-A9

description: Disease sample


title: ATA-Aspirin challenge 0hr-4

type: genomic

city: Bucheon

first: Jong Uk

last: Lee

address: 170, Jomaru-ro, Wonmi-gu

country: South Korea

institute: Soonchunhyang University Bucheon Hospital

hyb_protocol: genomic DNA was bisulfite-converted using the EZ DNA Methylation kit (Zymo) then assayed by the Illumina Infinium MethylationEPIC BeadChip array that interrogates over 850,000 CpG methylation sites.

scan_protocol: Arrays were imaged using BeadArray Reader using standard recommended Illumina scanner setting

data_processing: The data were normalised using quantile normalisation with IlluminaGUI in R

label: Cy5 and Cy3

source_name: PBMC

label_protocol: A total of 50 ng of genomic DNA was used for genome-wide DNA methylation profiling using Illumina’s Infinium MethylationEPIC (HM850K) platform.

extract_protocol: Genomic DNA was extracted from whole blood using QIAamp DNA Blood Mini kit  (Qiagen) following the manufacturer’s instructions. DNA quality and concentration were checked using nanodrop and qubit instruments, respectively.

tag: gender

value: Female

value: Human PBMC

tag: time point

value: Aspirin challenge 0hr

tag: disease state

value: ATA


title: Methanol, control, biol rep 2


title: ATA-Aspirin challenge 0hr-3

value: Male


title: Mouse thymus stage 0 Va14 iNKT scATAC-seq

description: Stage 0 iNKT cells from Va14 mouse thymus (sample 1)

value: V<alpha>14 transgenic (C57BL/6 background)

value: Thymus

value: Invariant natural killer T cells (iNKT) cells

value: 5 weeks


title: Sorted intravascular lung ILCs, scRNAseq

description: 10x Genomics

value: Live human CD45+ TCRab- CD3- Lineage- CD94- CD127+ i.v. CD45+


title: ATA-Aspirin challenge 0hr-2


title: Methanol, control, biol rep 1

value: WT


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_51]

status: Public on Jun 26 2023

city: Beijing

first: Cheng-ran

last: Xu

address: NO.5 YIHEYUAN ROAD HAIDIAN DISTRICT, BEIJING, P.R.CHINA

department: School of Basic Medical Sciences

country: China

institute: Peking University

description:
snRNA-seq
P60_2x4N_nuc_51

data_processing:
For mSTRT-seq, libraries were sequenced as 150-bp paired-end reads on an Illumina HiSeq 4000 platform. Raw files (fastq format) were separated based on cell-specific barcode sequences. PolyA sequences were trimmed from R1 reads (3’ end of cDNA). Preprocessed R1 reads from each cell were then aligned to the Mus musculus reference genome GRCm38/mm10 with TopHat V2.1.0. Bam files were annotated to genes with featureCounts (v1.5.3). We used samtools (v1.3.1) to sort and index the output bam files. UMIs of each gene were counted with umi-tools (v0.5.0) with the “unique” method.
For Smart-seq 3, libraries were sequenced as 100-bp paired-end reads on an MGI-seq 2000 platform. We trimmed the index, primer and adaptor sequences from the paired-end reads using Trimmomatic v0.39. The trimmed reads were aligned to the M. musculus reference genome GRCm38/mm10 with HISAT v2.1.0. Bam files were annotated to genes with featureCounts (v2.0.0). Either 5’ fragments or internal fragments were used during alignment.
For snRNA-seq, libraries were sequenced as 150-bp paired-end reads on an Illumina HiSeq 4000 platform. The alignment processes of snRNA-seq were similar to those of mSTRT-seq. The specific parameter of featureCounts (v1.5.3) during snRNA-seq alignment was “-t transcript” to ensure that the intron of mRNA could be detected.
For RNA-seq, libraries were sequenced as 150-bp paired-end reads on an Illumina HiSeq 2500 platform. the sequencing reads were aligned to the M. musculus genome (mm10) using TopHat (v2.1.0; https://ccb.jhu.edu/software/tophat/index.shtml) with the parameters ‘-o out_dir -G gtf –transcriptome-index trans_index bowtie2_index input_fastq1 input_fastq2’. Reads aligned to genes were counted using HTSeq (v0.6.0; https://htseq.readthedocs.io/) with the parameters ‘htseq-count -f bam -r pos -s reverse -a 30 input_bam gtf’.
Assembly: mm10
Supplementary files format and content: Comma-Separated Values files (.csv)

source_name: liver

extract_protocol:
For scRNA-seq, single cells were picked up into cell lysis buffer, and mRNA was reverse transcribed and amplified. For snRNA-seq, nucleus extraction was performed as previously reported(Krishnaswami et al., 2016). In brief, hepatocytes were collected through FACS sorting. Cell membranes were broken down with a homogenizer in homogenization buffer (250 mM sucrose, 25 mM KCl, 5 mM MgCl2, 10 mM Tris buffer (pH 8.0), 1 µM DTT, protease inhibitor, RNase inhibitor and 0.1% Triton X-100). After centrifugation (5 min, 500 g, 4° C), the nucleus was washed with PBS containing RNase inhibitor and stained with 0.5 ug/ml DAPI. The single nucleus was sorted into cell lysis. SnRNA-seq was performed using well-based mSTRT-seq just as scRNA-seq, but the cycles of cDNA amplification was 4 + 16. For bulk RNA-seq, total RNA was extracted using the RNAprep Pure Micro Kit. Poly(A) RNA was purified with the NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB, #E7490).
For well-based mSTRT-seq(Li et al., 2017), barcoded DNA products were pooled and libraries were constructed with a Kapa Hyper Prep Kit (Kapa Biosystems, KK8505). For Smart-seq3(Hagemann-Jensen et al., 2022), the library of each cell was constructed separately with TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme, TD501).  For bulk RNA-seq, libraries were constructed using the NEBNext Ultra II Directional RNA Library Prep with Sample Purification Beads (NEB, #E7765) according to the manufacturer’s instructions.

value: liver

value: hepatocyte

value: Alb-Cre; Rosa-tdTomato

tag: ploidy

tag: zonation


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_49]

description:
snRNA-seq
P60_2x4N_nuc_49


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_52]

description:
snRNA-seq
P60_2x4N_nuc_52


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_53]

description:
snRNA-seq
P60_2x4N_nuc_53


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_54]

description:
snRNA-seq
P60_2x4N_nuc_54


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_47]

description:
snRNA-seq
P60_2x4N_nuc_47


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_50]

description:
snRNA-seq
P60_2x4N_nuc_50


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_55]

description:
snRNA-seq
P60_2x4N_nuc_55


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_56]

description:
snRNA-seq
P60_2x4N_nuc_56


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_45]

description:
snRNA-seq
P60_2x4N_nuc_45


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_46]

description:
snRNA-seq
P60_2x4N_nuc_46


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_42]

description:
snRNA-seq
P60_2x4N_nuc_42


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_43]

description:
snRNA-seq
P60_2x4N_nuc_43


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_44]

description:
snRNA-seq
P60_2x4N_nuc_44


title: ATA-Aspirin challenge 0hr-1


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_40]

description:
snRNA-seq
P60_2x4N_nuc_40


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_39]

description:
snRNA-seq
P60_2x4N_nuc_39


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_41]

description:
snRNA-seq
P60_2x4N_nuc_41


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_38]

description:
snRNA-seq
P60_2x4N_nuc_38


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_37]

description:
snRNA-seq
P60_2x4N_nuc_37


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_36]

description:
snRNA-seq
P60_2x4N_nuc_36


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_35]

description:
snRNA-seq
P60_2x4N_nuc_35


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_34]

description:
snRNA-seq
P60_2x4N_nuc_34


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_33]

description:
snRNA-seq
P60_2x4N_nuc_33


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_32]

description:
snRNA-seq
P60_2x4N_nuc_32


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_48]

description:
snRNA-seq
P60_2x4N_nuc_48


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_29]

description:
snRNA-seq
P60_2x4N_nuc_29


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_22]

description:
snRNA-seq
P60_2x4N_nuc_22


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_25]

description:
snRNA-seq
P60_2x4N_nuc_25


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_24]

description:
snRNA-seq
P60_2x4N_nuc_24


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_30]

description:
snRNA-seq
P60_2x4N_nuc_30


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_27]

description:
snRNA-seq
P60_2x4N_nuc_27


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_26]

description:
snRNA-seq
P60_2x4N_nuc_26


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_19]

description:
snRNA-seq
P60_2x4N_nuc_19


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_20]

description:
snRNA-seq
P60_2x4N_nuc_20


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_28]

description:
snRNA-seq
P60_2x4N_nuc_28


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_18]

description:
snRNA-seq
P60_2x4N_nuc_18


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_14]

description:
snRNA-seq
P60_2x4N_nuc_14


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_17]

description:
snRNA-seq
P60_2x4N_nuc_17


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_23]

description:
snRNA-seq
P60_2x4N_nuc_23


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_16]

description:
snRNA-seq
P60_2x4N_nuc_16


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_11]

description:
snRNA-seq
P60_2x4N_nuc_11


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_13]

description:
snRNA-seq
P60_2x4N_nuc_13


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_21]

description:
snRNA-seq
P60_2x4N_nuc_21


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_15]

description:
snRNA-seq
P60_2x4N_nuc_15


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_9]

description:
snRNA-seq
P60_2x4N_nuc_9


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_8]

description:
snRNA-seq
P60_2x4N_nuc_8


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_6]

description:
snRNA-seq
P60_2x4N_nuc_6


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_5]

description:
snRNA-seq
P60_2x4N_nuc_5


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_31]

description:
snRNA-seq
P60_2x4N_nuc_31


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_7]

description:
snRNA-seq
P60_2x4N_nuc_7


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_2]

description:
snRNA-seq
P60_2x4N_nuc_2


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_3]

description:
snRNA-seq
P60_2x4N_nuc_3


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_1]

description:
snRNA-seq
P60_2x4N_nuc_1


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_12]

description:
snRNA-seq
P60_2x4N_nuc_12


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_63]

description:
snRNA-seq
P60_2x2N_nuc_63


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_64]

description:
snRNA-seq
P60_2x2N_nuc_64


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_61]

description:
snRNA-seq
P60_2x2N_nuc_61


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_60]

description:
snRNA-seq
P60_2x2N_nuc_60


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_65]

description:
snRNA-seq
P60_2x2N_nuc_65


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_62]

description:
snRNA-seq
P60_2x2N_nuc_62


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_59]

description:
snRNA-seq
P60_2x2N_nuc_59


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_58]

description:
snRNA-seq
P60_2x2N_nuc_58


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_57]

description:
snRNA-seq
P60_2x2N_nuc_57


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_10]

description:
snRNA-seq
P60_2x4N_nuc_10


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_56]

description:
snRNA-seq
P60_2x2N_nuc_56


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_52]

description:
snRNA-seq
P60_2x2N_nuc_52


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_55]

description:
snRNA-seq
P60_2x2N_nuc_55


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_53]

description:
snRNA-seq
P60_2x2N_nuc_53


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_47]

description:
snRNA-seq
P60_2x2N_nuc_47


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_48]

description:
snRNA-seq
P60_2x2N_nuc_48


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_49]

description:
snRNA-seq
P60_2x2N_nuc_49


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_46]

description:
snRNA-seq
P60_2x2N_nuc_46


title: P60, 2x4N nuc, snRNA-seq [P60_2x4N_nuc_4]

description:
snRNA-seq
P60_2x4N_nuc_4


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_66]

description:
snRNA-seq
P60_2x2N_nuc_66


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_45]

description:
snRNA-seq
P60_2x2N_nuc_45


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_44]

description:
snRNA-seq
P60_2x2N_nuc_44


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_54]

description:
snRNA-seq
P60_2x2N_nuc_54


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_51]

description:
snRNA-seq
P60_2x2N_nuc_51


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_50]

description:
snRNA-seq
P60_2x2N_nuc_50


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_36]

description:
snRNA-seq
P60_2x2N_nuc_36


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_42]

description:
snRNA-seq
P60_2x2N_nuc_42


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_41]

description:
snRNA-seq
P60_2x2N_nuc_41


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_33]

description:
snRNA-seq
P60_2x2N_nuc_33


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_37]

description:
snRNA-seq
P60_2x2N_nuc_37


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_39]

description:
snRNA-seq
P60_2x2N_nuc_39


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_43]

description:
snRNA-seq
P60_2x2N_nuc_43


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_35]

description:
snRNA-seq
P60_2x2N_nuc_35


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_29]

description:
snRNA-seq
P60_2x2N_nuc_29


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_31]

description:
snRNA-seq
P60_2x2N_nuc_31


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_32]

description:
snRNA-seq
P60_2x2N_nuc_32


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_38]

description:
snRNA-seq
P60_2x2N_nuc_38


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_28]

description:
snRNA-seq
P60_2x2N_nuc_28


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_26]

description:
snRNA-seq
P60_2x2N_nuc_26


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_25]

description:
snRNA-seq
P60_2x2N_nuc_25


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_24]

description:
snRNA-seq
P60_2x2N_nuc_24


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_27]

description:
snRNA-seq
P60_2x2N_nuc_27


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_23]

description:
snRNA-seq
P60_2x2N_nuc_23


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_40]

description:
snRNA-seq
P60_2x2N_nuc_40


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_22]

description:
snRNA-seq
P60_2x2N_nuc_22


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_21]

description:
snRNA-seq
P60_2x2N_nuc_21


title: Acetate, control, biol rep 3

value: control


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_20]

description:
snRNA-seq
P60_2x2N_nuc_20


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_34]

description:
snRNA-seq
P60_2x2N_nuc_34


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_30]

description:
snRNA-seq
P60_2x2N_nuc_30


title: Mouse thymus stage 3 B6 iNKT scATAC-seq

description: Stage 3 iNKT cells from B6 mouse thymus (sample 1)

value: stage 3


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_19]

description:
snRNA-seq
P60_2x2N_nuc_19


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_9]

description:
snRNA-seq
P60_2x2N_nuc_9


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_12]

description:
snRNA-seq
P60_2x2N_nuc_12


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_8]

description:
snRNA-seq
P60_2x2N_nuc_8


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_18]

description:
snRNA-seq
P60_2x2N_nuc_18


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_10]

description:
snRNA-seq
P60_2x2N_nuc_10


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_13]

description:
snRNA-seq
P60_2x2N_nuc_13


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_15]

description:
snRNA-seq
P60_2x2N_nuc_15


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_17]

description:
snRNA-seq
P60_2x2N_nuc_17


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_14]

description:
snRNA-seq
P60_2x2N_nuc_14


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_1]

description:
snRNA-seq
P60_2x2N_nuc_1


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_68]

description:
snRNA-seq
P60_1x4N_nuc_68


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_6]

description:
snRNA-seq
P60_2x2N_nuc_6


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_69]

description:
snRNA-seq
P60_1x4N_nuc_69


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_7]

description:
snRNA-seq
P60_2x2N_nuc_7


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_3]

description:
snRNA-seq
P60_2x2N_nuc_3


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_67]

description:
snRNA-seq
P60_1x4N_nuc_67


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_66]

description:
snRNA-seq
P60_1x4N_nuc_66


title: 3-Disease-C9

description: Disease sample

value: Skin

value: female

value: Holstein-Friesian


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_65]

description:
snRNA-seq
P60_1x4N_nuc_65


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_64]

description:
snRNA-seq
P60_1x4N_nuc_64


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_62]

description:
snRNA-seq
P60_1x4N_nuc_62


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_16]

description:
snRNA-seq
P60_2x2N_nuc_16


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_61]

description:
snRNA-seq
P60_1x4N_nuc_61


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_11]

description:
snRNA-seq
P60_2x2N_nuc_11


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_5]

description:
snRNA-seq
P60_2x2N_nuc_5


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_2]

description:
snRNA-seq
P60_2x2N_nuc_2


title: P60, 2x2N nuc, snRNA-seq [P60_2x2N_nuc_4]

description:
snRNA-seq
P60_2x2N_nuc_4


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_63]

description:
snRNA-seq
P60_1x4N_nuc_63


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_48]

description:
snRNA-seq
P60_1x4N_nuc_48


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_44]

description:
snRNA-seq
P60_1x4N_nuc_44


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_43]

description:
snRNA-seq
P60_1x4N_nuc_43


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_59]

description:
snRNA-seq
P60_1x4N_nuc_59


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_57]

description:
snRNA-seq
P60_1x4N_nuc_57


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_40]

description:
snRNA-seq
P60_1x4N_nuc_40


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_47]

description:
snRNA-seq
P60_1x4N_nuc_47


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_54]

description:
snRNA-seq
P60_1x4N_nuc_54


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_52]

description:
snRNA-seq
P60_1x4N_nuc_52


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_60]

description:
snRNA-seq
P60_1x4N_nuc_60


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_55]

description:
snRNA-seq
P60_1x4N_nuc_55


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_56]

description:
snRNA-seq
P60_1x4N_nuc_56


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_45]

description:
snRNA-seq
P60_1x4N_nuc_45


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_46]

description:
snRNA-seq
P60_1x4N_nuc_46


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_51]

description:
snRNA-seq
P60_1x4N_nuc_51


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_50]

description:
snRNA-seq
P60_1x4N_nuc_50


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_42]

description:
snRNA-seq
P60_1x4N_nuc_42


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_49]

description:
snRNA-seq
P60_1x4N_nuc_49


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_41]

description:
snRNA-seq
P60_1x4N_nuc_41


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_39]

description:
snRNA-seq
P60_1x4N_nuc_39


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_38]

description:
snRNA-seq
P60_1x4N_nuc_38


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_37]

description:
snRNA-seq
P60_1x4N_nuc_37


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_35]

description:
snRNA-seq
P60_1x4N_nuc_35


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_34]

description:
snRNA-seq
P60_1x4N_nuc_34


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_58]

description:
snRNA-seq
P60_1x4N_nuc_58


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_53]

description:
snRNA-seq
P60_1x4N_nuc_53


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_33]

description:
snRNA-seq
P60_1x4N_nuc_33


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_36]

description:
snRNA-seq
P60_1x4N_nuc_36


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_32]

description:
snRNA-seq
P60_1x4N_nuc_32


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_31]

description:
snRNA-seq
P60_1x4N_nuc_31


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_29]

description:
snRNA-seq
P60_1x4N_nuc_29


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_30]

description:
snRNA-seq
P60_1x4N_nuc_30


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_3]

description:
snRNA-seq
P60_1x4N_nuc_3


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_4]

description:
snRNA-seq
P60_1x4N_nuc_4


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_16]

description:
snRNA-seq
P60_1x4N_nuc_16


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_7]

description:
snRNA-seq
P60_1x4N_nuc_7


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_17]

description:
snRNA-seq
P60_1x4N_nuc_17


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_6]

description:
snRNA-seq
P60_1x4N_nuc_6


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_21]

description:
snRNA-seq
P60_1x4N_nuc_21


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_12]

description:
snRNA-seq
P60_1x4N_nuc_12


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_11]

description:
snRNA-seq
P60_1x4N_nuc_11


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_8]

description:
snRNA-seq
P60_1x4N_nuc_8


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_5]

description:
snRNA-seq
P60_1x4N_nuc_5


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_25]

description:
snRNA-seq
P60_1x4N_nuc_25


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_10]

description:
snRNA-seq
P60_1x4N_nuc_10


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_15]

description:
snRNA-seq
P60_1x4N_nuc_15


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_22]

description:
snRNA-seq
P60_1x4N_nuc_22


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_19]

description:
snRNA-seq
P60_1x4N_nuc_19


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_14]

description:
snRNA-seq
P60_1x4N_nuc_14


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_24]

description:
snRNA-seq
P60_1x4N_nuc_24


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_13]

description:
snRNA-seq
P60_1x4N_nuc_13


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_20]

description:
snRNA-seq
P60_1x4N_nuc_20


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_28]

description:
snRNA-seq
P60_1x4N_nuc_28


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_27]

description:
snRNA-seq
P60_1x4N_nuc_27


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_18]

description:
snRNA-seq
P60_1x4N_nuc_18


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_9]

description:
snRNA-seq
P60_1x4N_nuc_9


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_26]

description:
snRNA-seq
P60_1x4N_nuc_26


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_2]

description:
snRNA-seq
P60_1x4N_nuc_2


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_1]

description:
snRNA-seq
P60_1x4N_nuc_1


title: P60, 1x4N nuc, snRNA-seq [P60_1x4N_nuc_23]

description:
snRNA-seq
P60_1x4N_nuc_23


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_56]

description:
snRNA-seq
P60_1x2N_nuc_56


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_57]

description:
snRNA-seq
P60_1x2N_nuc_57


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_55]

description:
snRNA-seq
P60_1x2N_nuc_55


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_54]

description:
snRNA-seq
P60_1x2N_nuc_54


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_52]

description:
snRNA-seq
P60_1x2N_nuc_52


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_45]

description:
snRNA-seq
P60_1x2N_nuc_45


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_39]

description:
snRNA-seq
P60_1x2N_nuc_39


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_43]

description:
snRNA-seq
P60_1x2N_nuc_43


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_42]

description:
snRNA-seq
P60_1x2N_nuc_42


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_53]

description:
snRNA-seq
P60_1x2N_nuc_53


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_46]

description:
snRNA-seq
P60_1x2N_nuc_46


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_48]

description:
snRNA-seq
P60_1x2N_nuc_48


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_51]

description:
snRNA-seq
P60_1x2N_nuc_51


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_33]

description:
snRNA-seq
P60_1x2N_nuc_33


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_50]

description:
snRNA-seq
P60_1x2N_nuc_50


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_49]

description:
snRNA-seq
P60_1x2N_nuc_49


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_34]

description:
snRNA-seq
P60_1x2N_nuc_34


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_41]

description:
snRNA-seq
P60_1x2N_nuc_41


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_40]

description:
snRNA-seq
P60_1x2N_nuc_40


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_30]

description:
snRNA-seq
P60_1x2N_nuc_30


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_38]

description:
snRNA-seq
P60_1x2N_nuc_38


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_47]

description:
snRNA-seq
P60_1x2N_nuc_47


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_28]

description:
snRNA-seq
P60_1x2N_nuc_28


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_44]

description:
snRNA-seq
P60_1x2N_nuc_44


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_26]

description:
snRNA-seq
P60_1x2N_nuc_26


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_32]

description:
snRNA-seq
P60_1x2N_nuc_32


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_31]

description:
snRNA-seq
P60_1x2N_nuc_31


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_35]

description:
snRNA-seq
P60_1x2N_nuc_35


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_36]

description:
snRNA-seq
P60_1x2N_nuc_36


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_37]

description:
snRNA-seq
P60_1x2N_nuc_37


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_27]

description:
snRNA-seq
P60_1x2N_nuc_27


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_25]

description:
snRNA-seq
P60_1x2N_nuc_25


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_23]

description:
snRNA-seq
P60_1x2N_nuc_23


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_24]

description:
snRNA-seq
P60_1x2N_nuc_24


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_29]

description:
snRNA-seq
P60_1x2N_nuc_29


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_17]

description:
snRNA-seq
P60_1x2N_nuc_17


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_21]

description:
snRNA-seq
P60_1x2N_nuc_21


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_20]

description:
snRNA-seq
P60_1x2N_nuc_20


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_18]

description:
snRNA-seq
P60_1x2N_nuc_18


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_16]

description:
snRNA-seq
P60_1x2N_nuc_16


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_14]

description:
snRNA-seq
P60_1x2N_nuc_14


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_15]

description:
snRNA-seq
P60_1x2N_nuc_15


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_22]

description:
snRNA-seq
P60_1x2N_nuc_22


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_11]

description:
snRNA-seq
P60_1x2N_nuc_11


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_13]

description:
snRNA-seq
P60_1x2N_nuc_13


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_10]

description:
snRNA-seq
P60_1x2N_nuc_10


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_12]

description:
snRNA-seq
P60_1x2N_nuc_12


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_9]

description:
snRNA-seq
P60_1x2N_nuc_9


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_8]

description:
snRNA-seq
P60_1x2N_nuc_8


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_7]

description:
snRNA-seq
P60_1x2N_nuc_7


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_4]

description:
snRNA-seq
P60_1x2N_nuc_4


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_6]

description:
snRNA-seq
P60_1x2N_nuc_6


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_5]

description:
snRNA-seq
P60_1x2N_nuc_5


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_3]

description:
snRNA-seq
P60_1x2N_nuc_3


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_1]

description:
snRNA-seq
P60_1x2N_nuc_1


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_2]

description:
snRNA-seq
P60_1x2N_nuc_2


title: P60, 1x2N nuc, snRNA-seq [P60_1x2N_nuc_19]

description:
snRNA-seq
P60_1x2N_nuc_19


title: E14.5,Hepatoblast,Jmjd3KO,H3K27me3,2

data_processing:
For CUT&RUN ChIP, index, primer and daptor sequences were identified using FastQC (v0.11.3) with parameters "--extract --o out_dir -t 4 fastqc.file". Next, we trimmed the index, primer and adaptor sequences off from the paired-end reads using Trimmomatic (v0.38) 30 with parameters "java jar trimmoma 0.38.jar PE -phred33 fasq1.file fastq2.file ILLUMINACLIP:fasta.file:2:30:10 LEADING:3 TAILING:3 SLIDINGWINDOW:4:15 MINLEN:36". The trimmed reads were aligned to the Mus musculus genome (mm10) using bowtie2 (v2.2.5) with default parameters. Reads with mapping quality ≥30 were retained for the downstream analysis. Duplicate reads were removed from the PCR results using samtools (v1.3.1) with the command "samtools sort in_bam|samtools rmdup -s - out_bam". Reads generated from biological replicates were pooled. TP10M values were calculated and stored in bedGraph files using Homer with the command "makeUCSCfile out_dir -o out.bdg -name sample_name -avg -fsize 1e20". Peak calling was performed using MACS2 (v2.1.0) with ‘--broad’ mode and default parameters. Genome regions that overlapped with ENCODE blacklist regions (Encode Project Consortium, 2012) were excluded from peak regions.
For bulk cell RNA-seq, sequencing reads were aligned to the Mus musculus reference genome (mm10) using TopHat (v2.1.0) with the parameters "-o out_dir -G gtf --transcriptome-index trans_index bowtie2_index input_fastq [input_fastq2]". HTSeq (v0.6.0) was used to quantify the reads that mapped to each gene with the parameters "-f bam -r pos -s no -a 30".
Assembly: mm10
Supplementary files format and content: For bulk cell RNA-seq, comma-Separated Values files (.csv) include read count for each sample. For N-ChIP and CUT&RUN ChIP, bedgraph files (.bdg.gz) include scores representing read count per bp per 1 × 10e7 reads; BED files (.bed) include highly enriched regions (peaks).

source_name: Liver

extract_protocol:
For CUT&RUN ChIP-seq, we collected approximately 2,000–4,000 cells for each ChIP-seq, and used antibodies against H3K4me3 (Abcam, ab8580, 1ng), H3K27me3 (Millipore, 07-449, 1ng), H3K4me1 (Millipore, 07-436, 1ng), H3K27ac (Active motif, 39133, 1ng) and EZH2 (Cell Signaling Technology, 5246, 1:100). CUT&RUN ChIP-seq was performed following the protocol of Peter J Skene et al. (2018). For bulk cell RNA-seq, livers were dissociated into single cells by treatment with 0.25% trypsin at 37°C. The reaction was terminated by the addition of 0.4 volumes of FBS. The single-cell suspensions were centrifuged at 100 × g for 5 min at 4 °C, and the resulting pellets were re-suspended with PBS containing 1% FBS. Cells were incubated with the DLK-FITC antibody (MBL, D187-4, 1:100) at 4 °C for 20 min. After washing, cells were sorted with a BD FACS Aria SORP cell sorter (BD Bioscience). Dead cells were excluded by DAPI (Sigma, D9564, 0.5 µg/mL). Total RNA was extracted from approximately 50,000 cells using the RNeasy Micro Kit (Qiagen, 74004).
For CUT&RUN ChIP, libraries of ChIP DNA were constructed with the Ultra DNA Library Prep Kit for Illumina (New England Biolabs, E7370) or the KAPA Hyper Prep Kit (Kapa Biosystems, KK8502). DNA purification was conducted with VAHTS DNA Clean Beads XP beads (Vazyme, N411-03). The quality of the libraries was assessed with an Advanced Analytical Fragment Analyzer (AATI).

value: Liver

value: Hepatoblast

tag: time

tag: antibody


title: E14.5,Hepatoblast,Jmjd3WT,H3K27me3,2


title: E14.5,Hepatoblast,Jmjd3WT,H3K27me3,1


title: E14.5,Hepatoblast,Jmjd3KO,H3K27me3,1


title: TRAB9_mrna

city: Rochester

first: Michael

middle: Justin

last: Emch

state: Minnesota

address: 200 1st Street SW

department: Biochemistry and Molecular Biology

institute: Mayo Clinic

data_processing:
RNA-seq analysis follows the mapRseq pipeline (PMID: 24972667). Fastq files are assessed using fastqc and trimmed as necessary. Alignment to mm10 was performed using Tophat (2.0.6 or newer). Bam files are then sorted and annotated using HTSeq-count and differential expression analysis was performed using edgeR.
Assembly: mm10
Supplementary files format and content: .xlsx table of mature mRNA expression in counts following mapRseq pipeline delineated by treatment type.

source_name: Trabecular OVX+ERT 3

growth_protocol: Animals were housed in the Mayo Clinic Animal Facility in a temperature controlled (22 ± 2°C)  environment with a standard 12 hour light dark cycle. They had standard laboratory chow and unrestricted access to water

extract_protocol: Muscle and connective tissue were removed from the femurs, followed by removal of the epiphyses. Marrow was removed by centrifugation. Trabecular bone was isolated using a 1mm biopsy punch and then submerged in trizol. Cortical bone was trimmed and each end and the mid diaphysis was placed in a separate trizol containing microcentrifuge tube. Bone tissues were then homogenized using an ULTRA-TURRAX homogenizer and RNA was was extracted using the Qiagen miRNeasy kit. Prior to sequencing, equal amounts of cortical or trabecular RNA from two individual mice were pooled to generate 3 replicate samples for each bone compartment and treatment group.

treatment_protocol: 18 8-week old C57BL/6 mice were randomized to sham+placebo, OVX+placebo, or OVX+ERT treatment groups. Sham and OVX surgeries were performed, and immediately following surgery a 1.88μg 17β-estradiol 30-day slow release pellet or placebo was implanted subcutaneously. 30 days post surgery the mice were sacrificed and the femurs were collected.

value: Femur

tag: tissue type

value: Trabecular

value: OVX+ERT


title: TRAB7_mrna

source_name: Trabecular OVX+ERT 1


title: TRAB4_mrna

source_name: Trabecular OVX 1

value: OVX


title: TRAB8_mrna

source_name: Trabecular OVX+ERT 2


title: TRAB6_mrna

source_name: Trabecular OVX 3


title: E14.5,Hepatoblast,Ezh2KO,H3K27me3,1


title: E14.5,Hepatoblast,Ezh2KO,H3K27me3,2


title: E14.5,Hepatoblast,Ezh2WT,H3K27me3,1


title: TRAB3_mrna

source_name: Trabecular Sham 3

value: Sham


title: TRAB2_mrna

source_name: Trabecular Sham 2


title: TRAB5_mrna

source_name: Trabecular OVX 2


title: TRAB1_mrna

source_name: Trabecular Sham 1


title: CORT9_mrna

source_name: Cortical OVX+ERT 3

value: Cortical


title: E14.5,Hepatoblast,Ezh2WT,H3K27me3,2


title: CORT8_mrna

source_name: Cortical OVX+ERT 2


title: CORT7_mrna

source_name: Cortical OVX+ERT 1


title: CORT5_mrna

source_name: Cortical OVX 2


title: CORT4_mrna

source_name: Cortical OVX 1


title: CORT3_mrna

source_name: Cortical Sham 3


title: CORT1_mrna

source_name: Cortical Sham 1


title: CORT2_mrna

source_name: Cortical Sham 2


title: E17.5,Hepatocyte,H3K4me1,2

data_processing:
For CUT&RUN ChIP, index, primer and daptor sequences were identified using FastQC (v0.11.3) with parameters "--extract --o out_dir -t 4 fastqc.file". Next, we trimmed the index, primer and adaptor sequences off from the paired-end reads using Trimmomatic (v0.38) 30 with parameters "java jar trimmoma 0.38.jar PE -phred33 fasq1.file fastq2.file ILLUMINACLIP:fasta.file:2:30:10 LEADING:3 TAILING:3 SLIDINGWINDOW:4:15 MINLEN:36". The trimmed reads were aligned to the Mus musculus genome (mm10) using bowtie2 (v2.2.5) with default parameters. Reads with mapping quality ≥30 were retained for the downstream analysis. Duplicate reads were removed from the PCR results using samtools (v1.3.1) with the command "samtools sort in_bam|samtools rmdup -s - out_bam". Reads generated from biological replicates were pooled. TP10M values were calculated and stored in bedGraph files using Homer with the command "makeUCSCfile out_dir -o out.bdg -name sample_name -avg -fsize 1e20". Peak calling was performed using MACS2 (v2.1.0) with ‘--broad’ mode and default parameters. Genome regions that overlapped with ENCODE blacklist regions (Encode Project Consortium, 2012) were excluded from peak regions.
For bulk cell RNA-seq, sequencing reads were aligned to the Mus musculus reference genome (mm10) using TopHat (v2.1.0) with the parameters "-o out_dir -G gtf --transcriptome-index trans_index bowtie2_index input_fastq [input_fastq2]". HTSeq (v0.6.0) was used to quantify the reads that mapped to each gene with the parameters "-f bam -r pos -s no -a 30".
Assembly: mm10
Supplementary files format and content: For bulk cell RNA-seq, comma-Separated Values files (.csv) include read count for each sample. For N-ChIP and CUT&RUN ChIP, bedgraph files (.bedgraph) include scores representing read count per bp per 1 × 10e7 reads; BED files (.bed) include highly enriched regions (peaks).
Library strategy: CUT&RUN

source_name: Liver

extract_protocol:
For CUT&RUN ChIP-seq, we collected approximately 2,000–4,000 cells for each ChIP-seq, and used antibodies against H3K4me3 (Abcam, ab8580, 1ng), H3K27me3 (Millipore, 07-449, 1ng), H3K4me1 (Millipore, 07-436, 1ng), H3K27ac (Active motif, 39133, 1ng) and EZH2 (Cell Signaling Technology, 5246, 1:100). CUT&RUN ChIP-seq was performed following the protocol of Peter J Skene et al. (2018). For bulk cell RNA-seq, livers were dissociated into single cells by treatment with 0.25% trypsin at 37°C. The reaction was terminated by the addition of 0.4 volumes of FBS. The single-cell suspensions were centrifuged at 100 × g for 5 min at 4 °C, and the resulting pellets were re-suspended with PBS containing 1% FBS. Cells were incubated with the DLK-FITC antibody (MBL, D187-4, 1:100) at 4 °C for 20 min. After washing, cells were sorted with a BD FACS Aria SORP cell sorter (BD Bioscience). Dead cells were excluded by DAPI (Sigma, D9564, 0.5 µg/mL). Total RNA was extracted from approximately 50,000 cells using the RNeasy Micro Kit (Qiagen, 74004).
For CUT&RUN ChIP, libraries of ChIP DNA were constructed with the Ultra DNA Library Prep Kit for Illumina (New England Biolabs, E7370) or the KAPA Hyper Prep Kit (Kapa Biosystems, KK8502). DNA purification was conducted with VAHTS DNA Clean Beads XP beads (Vazyme, N411-03). The quality of the libraries was assessed with an Advanced Analytical Fragment Analyzer (AATI).
For bulk cell RNA-seq, livers were dissociated into single cells by treatment with 0.25% trypsin at 37°C. The reaction was terminated by the addition of 0.4 volumes of FBS. The single-cell suspensions were centrifuged at 100 × g for 5 min at 4 °C, and the resulting pellets were re-suspended with PBS containing 1% FBS. Cells were incubated with the DLK-FITC antibody (MBL, D187-4, 1:100) at 4 °C for 20 min. After washing, cells were sorted with a BD FACS Aria SORP cell sorter (BD Bioscience). Dead cells were excluded by DAPI (Sigma, D9564, 0.5 µg/mL). Total RNA was extracted from approximately 50,000 cells using the RNeasy Micro Kit (Qiagen, 74004).
For bulk cell RNA-seq, libraries were constructed with the NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs, #E7490) and the NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs, #E7420).

value: Hepatocyte


title: E17.5,Hepatocyte,H3K4me3,1


title: E17.5,Hepatocyte,H3K4me1,1


title: E17.5,Hepatocyte,H3K4me3,2


title: E17.5,Hepatocyte,H3K27me3,1


title: E17.5,Hepatocyte,H3K27me3,2


title: E17.5,Hepatocyte,H3K27ac,1


title: E17.5,Hepatocyte,H3K27ac,2


title: E17.5,Hepatocyte,ATAC,1

data_processing:
For CUT&RUN ChIP, index, primer and daptor sequences were identified using FastQC (v0.11.3) with parameters "--extract --o out_dir -t 4 fastqc.file". Next, we trimmed the index, primer and adaptor sequences off from the paired-end reads using Trimmomatic (v0.38) 30 with parameters "java jar trimmoma 0.38.jar PE -phred33 fasq1.file fastq2.file ILLUMINACLIP:fasta.file:2:30:10 LEADING:3 TAILING:3 SLIDINGWINDOW:4:15 MINLEN:36". The trimmed reads were aligned to the Mus musculus genome (mm10) using bowtie2 (v2.2.5) with default parameters. Reads with mapping quality ≥30 were retained for the downstream analysis. Duplicate reads were removed from the PCR results using samtools (v1.3.1) with the command "samtools sort in_bam|samtools rmdup -s - out_bam". Reads generated from biological replicates were pooled. TP10M values were calculated and stored in bedGraph files using Homer with the command "makeUCSCfile out_dir -o out.bdg -name sample_name -avg -fsize 1e20". Peak calling was performed using MACS2 (v2.1.0) with ‘--broad’ mode and default parameters. Genome regions that overlapped with ENCODE blacklist regions (Encode Project Consortium, 2012) were excluded from peak regions.
For bulk cell RNA-seq, sequencing reads were aligned to the Mus musculus reference genome (mm10) using TopHat (v2.1.0) with the parameters "-o out_dir -G gtf --transcriptome-index trans_index bowtie2_index input_fastq [input_fastq2]". HTSeq (v0.6.0) was used to quantify the reads that mapped to each gene with the parameters "-f bam -r pos -s no -a 30".
Assembly: mm10
Supplementary files format and content: For bulk cell RNA-seq, comma-Separated Values files (.csv) include read count for each sample. For N-ChIP and CUT&RUN ChIP, bedgraph files (.bedgraph) include scores representing read count per bp per 1 × 10e7 reads; BED files (.bed) include highly enriched regions (peaks).


title: E17.5,Hepatocyte,ATAC,2


title: E17.5,Cholangiocyte,H3K27ac,2

value: Cholangiocyte


title: E17.5,Cholangiocyte,H3K27me3,2


title: E17.5,Cholangiocyte,H3K4me1,2


title: E16.5,Hepatocyte,H3K4me3,2


title: E17.5,Cholangiocyte,H3K27ac,1


title: E17.5,Cholangiocyte,ATAC,1


title: CORT6_mrna

source_name: Cortical OVX 3


title: E17.5,Cholangiocyte,H3K4me1,1


title: E16.5,Hepatocyte,H3K27me3,1


title: E16.5,Hepatocyte,H3K27me3,2


title: E17.5,Cholangiocyte,H3K27me3,1


title: E17.5,Cholangiocyte,H3K4me3,1


title: E16.5,Hepatocyte,H3K4me3,1


title: E16.5,Hepatocyte,H3K4me1,1


title: E17.5,Cholangiocyte,ATAC,2


title: E16.5,Hepatocyte,ATAC,2


title: E16.5,Hepatocyte,H3K27ac,1


title: E16.5,Hepatocyte,H3K27ac,2


title: E16.5,Cholangiocyte,RNAseq,2

description: read.count.rnaseq.csv


title: E16.5,Cholangiocyte,RNAseq,1

description: read.count.rnaseq.csv


title: E16.5,Hepatocyte,ATAC,1


title: E16.5,Hepatocyte,H3K4me1,2


title: E17.5,Cholangiocyte,H3K4me3,2


title: E16.5,Cholangiocyte,H3K4me3,1


title: E16.5,Cholangiocyte,H3K4me1,2


title: E16.5,Cholangiocyte,H3K27me3,2


title: E16.5,Cholangiocyte,H3K27me3,1


title: E16.5,Cholangiocyte,H3K4me1,1


title: E16.5,Cholangiocyte,ATAC,2


title: E16.5,Cholangiocyte,H3K27ac,1


title: E16.5,Cholangiocyte,H3K27ac,2


title: E16.5,Cholangiocyte,ATAC,1


title: E15.5,Hepatocyte,H3K4me1,1


title: E15.5,Hepatocyte,H3K27me3,2


title: E15.5,Hepatocyte,H3K4me1,2


title: E15.5,Cholangiocyte,H3K4me3,2


title: E15.5,Hepatocyte,H3K27ac,1


title: E15.5,Cholangiocyte,RNAseq,1

description: read.count.rnaseq.csv


title: E15.5,Hepatocyte,H3K27me3,1


title: E16.5,Cholangiocyte,H3K4me3,2


title: E15.5,Cholangiocyte,RNAseq,2

description: read.count.rnaseq.csv


title: E15.5,Hepatocyte,H3K27ac,2


title: E15.5,Hepatocyte,H3K4me3,1


title: E15.5,Hepatocyte,H3K4me3,2


title: E15.5,Hepatocyte,ATAC,2


title: E15.5,Hepatocyte,ATAC,1


title: E15.5,Cholangiocyte,H3K27me3,1


title: E15.5,Cholangiocyte,H3K27ac,2


title: E15.5,Cholangiocyte,H3K4me1,2


title: E15.5,Cholangiocyte,H3K4me3,1


title: E15.5,Cholangiocyte,H3K4me1,1


title: E15.5,Cholangiocyte,ATAC,2


title: E15.5,Cholangiocyte,ATAC,1


title: E15.5,Cholangiocyte,H3K27me3,2


title: E15.5,Cholangiocyte,H3K27ac,1


title: E14.5,Hepatoblast,H3K4me3,2


title: E14.5,Hepatoblast,H3K4me1,2


title: E14.5,Hepatoblast,H3K4me3,1


title: E14.5,Hepatoblast,H3K4me1,1


title: E14.5,Hepatoblast,H3K27me3,1


title: E14.5,Hepatoblast,H3K27ac,2


title: E14.5,Hepatoblast,ATAC,1


title: E14.5,Hepatoblast,ATAC,2


title: E14.5,Hepatoblast,H3K27ac,1


title: E13.5,Hepatoblast,H3K4me3,2


title: E13.5,Hepatoblast,H3K4me3,1


title: E13.5,Hepatoblast,H3K27ac,1


title: E13.5,Hepatoblast,ATAC,2


title: E13.5,Hepatoblast,H3K27me3,1


title: E13.5,Hepatoblast,H3K27me3,2


title: E13.5,Hepatoblast,H3K4me1,1


title: E13.5,Hepatoblast,H3K4me1,2


title: E12.5,Hepatoblast,H3K4me3,2


title: E12.5,Hepatoblast,H3K4me1,2


title: E13.5,Hepatoblast,ATAC,1


title: E12.5,Hepatoblast,H3K4me1,1


title: E13.5,Hepatoblast,H3K27ac,2


title: E12.5,Hepatoblast,H3K27me3,2


title: E12.5,Hepatoblast,H3K27ac,1


title: E12.5,Hepatoblast,H3K27ac,2


title: E12.5,Hepatoblast,H3K4me3,1


title: E12.5,Hepatoblast,ATAC,1


title: E12.5,Hepatoblast,ATAC,2


title: E12.5,Hepatoblast,H3K27me3,1


title: E14.5,Hepatoblast,H3K27me3,2


title: P60_PV_2, RNA-seq

description:
bulk RNA-seq
readcount.RNA-seq.csv

source_name: liver

value: liver

value: hepatocyte

tag: cell subset

tag: age

value: PV


title: P60_ML_1, RNA-seq

description:
bulk RNA-seq
readcount.RNA-seq.csv

tag: tissue

value: Alb-Cre; Rosa-tdTomato

value: ML


title: P60_ML_2, RNA-seq

description:
bulk RNA-seq
readcount.RNA-seq.csv


title: P60_CV_1, RNA-seq

description:
bulk RNA-seq
readcount.RNA-seq.csv

value: CV


title: P60_CV_2, RNA-seq

description:
bulk RNA-seq
readcount.RNA-seq.csv


title: P60_4N_nuc_150, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_160, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_155, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_154, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_153, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_151, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_157, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_147, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_158, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_144, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_159, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_146, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_142, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_161, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_PV_1, RNA-seq

description:
bulk RNA-seq
readcount.RNA-seq.csv


title: P60_4N_nuc_143, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_156, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_145, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_140, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_141, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_139, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_138, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_149, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_148, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_136, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_152, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_137, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_133, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_130, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_131, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_128, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_123, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_125, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_124, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_115, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_114, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_116, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_118, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_126, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_120, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_121, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_122, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_112, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_134, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_113, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_111, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_110, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_135, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_132, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_109, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_127, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_129, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_107, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_119, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_117, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_104, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_103, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_101, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_99, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_100, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_102, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_98, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_96, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_88, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_89, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_95, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_97, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_91, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_90, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_87, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_86, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_105, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_108, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_106, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_85, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_84, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_82, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_83, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_81, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_79, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_78, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_92, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_93, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_94, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_80, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_71, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_74, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_73, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_66, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_68, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_72, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_65, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_67, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_75, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_69, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_62, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_64, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_77, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_76, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_63, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_57, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_54, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_55, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_61, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_60, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_59, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_56, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_58, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_52, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_53, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_51, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_50, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_70, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_48, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_49, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_46, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_43, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_45, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_44, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_39, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_41, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_42, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_35, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_34, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_40, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_38, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_37, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_33, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_25, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_28, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_29, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_27, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_23, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_24, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_30, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_21, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_31, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_32, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_26, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_22, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_20, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_18, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_47, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_19, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_36, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_16, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_14, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_12, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_11, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_10, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_8, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_7, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_6, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_9, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_5, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_4, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_339, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_1, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_337, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_336, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_2, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_3, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_338, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_334, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_340, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_17, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_335, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_15, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_330, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_333, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_329, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_332, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_331, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_328, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_327, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_325, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_4N_nuc_13, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_323, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_324, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_322, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_319, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_320, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_321, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_315, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_313, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_314, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_317, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_312, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_318, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_310, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_311, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_307, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_309, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_316, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_305, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_304, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_306, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_308, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_303, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_299, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_301, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_302, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_326, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_300, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_298, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_296, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_297, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_294, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_293, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_291, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_290, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_292, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_295, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_286, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_288, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_289, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_287, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_273, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_268, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_270, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_269, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_279, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_277, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_267, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_280, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_271, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_285, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_281, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_283, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_284, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_278, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_276, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_272, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_275, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_263, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_274, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_261, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_260, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_282, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_266, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_256, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_264, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_265, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_258, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_259, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_255, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_257, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_262, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_254, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_252, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_235, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_243, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_237, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_245, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_238, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_248, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_244, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_247, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_253, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_251, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_246, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_250, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_249, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_232, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_231, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_242, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_228, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_241, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_240, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_239, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_226, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_229, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_236, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_225, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_233, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_222, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_227, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_234, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_224, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_220, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_214, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_230, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_215, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_213, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_211, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_219, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_218, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_221, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_223, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_209, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_207, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_217, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_216, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_212, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_210, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_203, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_208, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_197, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_196, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_206, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_205, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_204, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_194, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_202, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_190, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_199, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_192, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_187, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_201, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_189, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_195, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_193, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_183, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_191, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_181, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_178, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_184, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_188, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_182, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_177, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_180, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_179, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_200, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_175, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_186, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_174, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_172, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_164, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_171, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_166, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_173, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_167, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_163, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_165, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_185, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_169, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_162, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_176, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_161, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_158, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_159, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_160, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_157, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_155, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_154, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_156, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_151, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_153, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_170, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_168, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_149, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_148, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_150, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_144, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_141, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_143, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_139, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_146, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_147, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_137, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_136, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_138, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_132, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_135, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_130, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_152, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_134, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_129, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_128, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_126, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_127, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_123, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_124, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_145, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_142, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_140, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_120, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_121, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_119, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_114, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_117, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_116, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_131, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_118, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_133, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_112, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_125, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_111, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_110, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_108, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_107, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_109, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_105, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_104, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_122, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_101, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_100, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_99, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_115, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_98, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_113, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_96, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_97, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_95, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_94, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_88, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_92, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_89, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_93, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_90, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_91, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_106, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_103, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_85, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_102, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_82, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_86, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_84, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_83, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_79, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_80, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_81, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_78, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_77, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_75, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_76, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_74, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_72, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_73, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_69, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_70, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_87, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_67, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_66, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_65, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_63, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_62, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_61, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_60, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_58, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_59, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_56, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_54, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_55, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_53, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_57, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_51, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_49, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_71, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_50, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_48, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_47, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_68, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_46, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_41, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_42, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_45, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_44, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_64, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_43, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_40, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_38, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_39, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_34, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_52, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_35, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_33, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_32, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_37, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_29, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_27, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_23, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_22, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_25, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_26, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_24, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_31, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_20, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_19, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_17, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_15, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_16, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_18, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_14, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_21, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_12, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_36, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_11, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_13, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_30, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_28, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_8, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_7, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_9, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_5, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_6, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_4, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_2, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_3, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_198, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_1, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_45, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_43, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_44, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_46, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_42, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_41, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_39, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_38, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_37, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_36, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_33, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_35, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_31, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_34, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P60_2N_nuc_10, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_32, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_29, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_40, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_30, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_27, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_26, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_24, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_25, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_28, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_22, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_21, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_23, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_18, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_19, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_20, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_17, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_15, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_14, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_16, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_13, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_12, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_11, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_9, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_10, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_8, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_6, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_4, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_2, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_2N_nuc_102, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv


title: P18_4N_nuc_1, snRNA-seq

description:
snRNA-seq
readcount.snRNA-seq.csv