title: lung cancer tissue with only extracranial metastasis, biological rep19

city: Tangshan

first: Guogui

last: Sun

state: China

address: 73 Jian-She Road, Tangshan, Hebei, P.R. China

country: China

institute: North China University of Science and Technology Affiliated Hospital

description: Gene expression data from lung cancer tissue with only extracranial metastasis

hyb_protocol: Following fragmentation, 1 ug of cRNA were hybridized for 16 hr at 48C on GeneChip miRNA 2.0 Array. GeneChips were washed and stained in the Affymetri Fluidics Station 450.

scan_protocol: GeneChips were scanned using the Affymetrix GeneChip Scanner 3000 7G.

data_processing: The data were analyzed with miRNA QC tool version 1.1.1 (AffyMir v 1.1.1) using Affymetrix default analysis settings and global scaling as normalization method. The trimmed mean target intensity of each array was arbitrarily set to 100.

label_protocol: Biotinylated cRNA were prepared according to the standard Affymetrix protocol from 1 ug total RNA (Expression Analysis Technical Manual, 2001, Affymetrix).

growth_protocol: The fresh human lung cancer tissues were fixed by formalin and embedded by paraffin.

extract_protocol: Trizol extraction of total RNA was performed according to the manufacturer's instructions.

treatment_protocol: After dewaxing treatment, tissues were collected for further total RNA extraction.

value: lung


title: HC2_sp2_Normal_Control_ox21_p18

status: Public on Nov 12 2021

type: SRA

city: New York

first: Gabriel

last: Sturm

state: NY

address: 40 Haven Avenue

department: Psychiatry

country: USA

institute: Columbia University

library_source: transcriptomic

data_processing:
360 samples were sent for sequencing; 9 samples did not passed intial QC (low RIN score, high DNA contamination), and 6 samples did not pass post-sequencing QC, for a final of 345 samples.
kallisto alignment v0.44.0 (Bray et al., 2016) using the hg19 genome. Sequence and annotation files were downloaded from the NCBI ftp portal for genome version GRCh37.p13
txi import using lengthScaledTPM (‘tximport’, v1.18.0)
vst normalization (‘DEseq2’, v1.30.1).
log2 transformation
Genome_build: hg19
Supplementary_files_format_and_content: Matrix table with log2 transformed vst normalized expression values for every gene and every sample
processed_cell_lifespan_RNAseq_data.csv: log2 vst normalized expression values
raw_counts_cell_lifespan_RNAseq_data.csv: raw counts as outputted by kallisto alignment
txi_transcript_abundance.csv: transcript abundances (‘tximport’, v1.18.0)
txi_transcript_count_lengthScaledTPM.csv: transcript counts length-scaled TPM (‘tximport’, v1.18.0)
txi_transcript_length.csv: transcript lengths (‘tximport’, v1.18.0)
txi_gene_abundance.csv: gene abundances (‘tximport’, v1.18.0)
txi_gene_count_lengthScaledTPM.csv: gene counts length-scaled TPM (‘tximport’, v1.18.0)
txi_gene_length.csv: gene lengths (‘tximport’, v1.18.0)

molecule: total RNA

organism: Homo sapiens

source_name: Primary Human Fibroblast (breast)

growth_protocol: Primary human dermal fibroblasts were obtained from distributor or in local clinic from 4 healthy and 3 SURF1-patient donors (IRB #AAAB0483). Fibroblasts were isolated from biopsy tissue using standard centrifugation procedure. After isolation, fibroblasts were stored in 10% DMSO (Sigma-Aldrich #D4540), 90% fetal bovine serum (FBS, Life Technologies #10437036) in cryogenic tube under liquid nitrogen. To avoid freeze-shock necrosis cells were frozen gradually in an isopropanol container (Thermofisher #5100-0001) at -80°C overnight before storage in liquid nitrogen. Cells were thawed by placement in 37°C (<4min) and immediately transferred to 20ml of preheated DMEM (Invitrogen #10567022). Cells were cultured in T175 flasks (Eppendorf #0030712129) at standard 5% CO2 and atmospheric O2 at 37°C in DMEM (5.5 mM glucose) supplemented 10% FBS, 50 μg/ml uridine (Sigma-Aldrich #U6381), 1% MEM non-essential amino acids (Life Technologies #11140050), 10 μM palmitate (Sigma-Aldrich #P9767) conjugated to 1.7 μM  BSA (Sigma-Aldrich #A8806), and 0.001% DMSO (treatment-matched, Sigma-Aldrich #D4540). Cells were passaged approximately every 5 days (+/- 1 day). Brightfield microscopy images (10x, 20x magnification) were taken before each passaged using inverted phase-contrast microscope (Fisher Scientific #11350119). Cell counts, volume and death were determined at each passage using the Countess II Automated Cell Counter (ThermoFisher Scientific #A27977). Growth rates were used to determine replating density, by pre-calculating number cells needed to reach ~90% confluency (~2.5 million cells) at time of next passage. Cells were never plated below 200,000 cells or above 2.5 million cells to avoid plating artifacts of isolation or contact inhibtion, respectively. Study measurements and treatment began after 15-days of culturing post-thaw to allow for adjustment to in vitro environment. Individual cell lines were terminated after exhibiting less than one population doubling over a 30-day period. Mycoplasma testing was performed on media across the full sampleset with no detectable infection.

extract_protocol:
Total genomic RNA was isolated every ~11days across cellular lifespan and stored in 1ml trysol (Invitrogen cat#15596026). RNA was extracted on-column using a RNeasy kit (Qiagen cat# 74104), DNase treated according to the manufacturer’s instructions, and quantified using the QUBIT high sensitivity kit (Thermo Fisher Scientific cat#Q32852). RNA samples underwent QC on bioanalyzer and Nanodrop 2000, all samples had a RIN score >8.0 and no detectable levels of DNA. For cDNA library preparation,1,500ng of RNA at 50ng/μl was processed using Ribo-Zero Gold purification (QIAseq FastSelect -rRNA HMR Kit #334387) and NEBNext® Ultra™ II RNA Library Prep Kit (Illumina #E7770L))  (1,500ng/sample, 50ng/μl). cDNA was sequenced using paired-end 150bp chemistry on a HiSeq 4000 instrument (Illumina, single index, 10 samples/lane, Genewiz Inc), yielding  ~40 million reads per sample.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: Treatment conditions include chronic addition (dosed at every passage) of 100nM dexamethasone (DEX, Sigma-Aldrich #D4902), mitoNUITs; a combination of a) 2μM UK5099 (Sigma-Aldrich #PZ0160) b) 4μM Etomoxir (Sigma-Aldrich #E1905) c) 3μM BPTES t (Sigma-Aldrich #SML0601), 5.5mM galactose (Sigma-Aldrich #G5388), 1nM oligomycin (Oligo, Sigma-Aldrich #75351), 1mM 2-deoxy-d-glucose (2DG, Sigma-Aldrich #D3179), 10mM beta-hydroxybutyrate (Sigma-Aldrich #54965), contact inhibition (allowing cells to fill up the dish and enter a quiescent state), hypoxia (3% oxygen), and acute treatment (10days) of 1μg/mL 5-azacytidine (Sigma-Aldrich #A2385).

value: Primary Human Fibroblast (breast)

tag: Sex

value: female

value: Normal

tag: treatments

value: Control

tag: passage


title: lung cancer tissue with only extracranial metastasis, biological rep20

type: RNA

label: biotin

tag: tissue


title: lung cancer tissue with only extracranial metastasis, biological rep21


title: HC2_sp2_Normal_Control_ox21_p15


title: 22_III_ExE_Eed

city: Munich

first: Daniel

last: Andergassen

address: Biedersteiner Straße 29

country: Germany

institute: Technical University Munich

data_processing:
The RNA-seq data were aligned to the mm10 reference genome using the STAR aligner (Dobin, A. et al. 2013, Bioinformatics, STAR version 2.5.0 c: –outFilterMultimapNmax 1). The read counts for every RefSeq isoform (RefSeq gene annotation (downloaded February 2018) were determined using the htseq-count phyton script (Anders, S. et al. 2015 Bioinformatics, version 0.6.1) and further normalized in R. The Allelome.PRO approach was used to calculate allele-specific expression from the RNA-seq data as outlined in Andergassen D. et al. 2015 NAR. Briefly, the Allelome.PRO pipeline uses strain-specific single-nucleotide polymorphisms (SNPs) to assign RNA-seq reads to the corresponding allele in F1 crosses.
Genome_build: mm10
Supplementary_files_format_and_content: bigwig

organism: Mus musculus

source_name: ExE

growth_protocol: Embryos were generated as previously described (Wang et al., 2013). Briefly, BDF1 strain female mice (age 6–8 weeks, Jackson Labs) were superovulated by serial Pregnant Mare Serum Gonadotropin (5 IU per mouse, Prospec Protein Specialists) and human chorionic gonadotropin (5 IU, Millipore) injections 46 h apart. The following day, MII stage oocytes were isolated in M2 media supplemented with hyaluronidase (Millipore) and stored in 25 μl drops of pre-gassed KSOM with half-strength concentration of amino acids (Millipore) under mineral oil (Irvine Scientific). Zygotes were generated by piezo-actuated intracytoplasmic sperm injection (ICSI. See (Grosswendt et al., 2020)) using thawed CAST strain sperm in batches of 30–50 oocytes and standard micromanipulation equipment, including a Hamilton Thorne XY Infrared laser, Eppendorf Transferman NK2 and Patchman NP2 micromanipulators, and a Nikon Ti-U inverted microscope. Zygotes for whole genome bisulfite sequencing were generated by natural mating with BDF1 males. For the reciprocal cross, BDF1 males were naturally mated to CAST females and screened for copulation plugs, after which E6.5 stage embryos were isolated accordingly, with the date of the copulation plug score day E0.5. For zygotic disruption, pronuclear stage 3 (PN3) zygotes were injected with 200 ng μl−1 Cas9 mRNA and a 100 ng μl−1 equimolar ratio of 3–4 sgRNAs targeting different exons of an epigenetic regulator gene locus (designed using ChopChop (Labun et al., 2016) and the IDT CRISPR–Cas9 guide RNA checker, as previously described in (Smith et al., 2017)). We designed the gRNA to avoid CAST SNPs to ensure that the gRNAs are equally effective between the alleles. Injections utilized the same microinjection setup and Piezo-actuated injection of front-filled 6-7 μm injection needles. At around 84 h after fertilization, cavitated blastocysts were transferred into the uterine horns of pseudopregnant CD-1 strain females (25–35g, Charles River) generated by mating with vasectomized SW strain males (Taconic), which results in a 24 h offset in gestational time to accommodate implantation, after which animals were monitored for 5 days for embryo isolation at E6.5.

extract_protocol:
At E6.5, animals were euthanized and the uterine horn removed. Purified epiblast and ExE were isolated according to Ref. (Chenoweth and Tesar, 2010) with a few modifications. Briefly, E6.5 embryos were removed from deciduae and transferred to independent 25 μL drops of M2 media. Using a glass flame-pulled capillary, Reichart’s membrane was reflected, and the embryo carefully bisected along the epiblast, ExE boundary. Then, each Epiblast/ExE pair was transferred into an individual drop of dissociation medium containing 0.5% trypsin and 2.5% pancreatin in PBS (w/v, Sigma). Embryos were cultured with slow orbital rotation at 4ºC for 15 minutes, after which they were transferred into new M2 drops. After ~5 minutes of resting, Epiblast and ExE were passed through a slightly narrower flame-pulled glass capillary to remove the visceral endoderm without disrupting the target tissue. Finally, each tissue was serially washed in 0.1% BSA in PBS prior to snap freezing in lysis buffer.
Approximately 300-600 cells were collected from E6.5 embryos and directly transferred to 2.6 µl of Lysis Buffer (Takara Bio USA, Inc.) followed by snap-freezing at -80°C in preparation for cDNA synthesis using the SMART-Seq v4 assay. Full-length cDNA was prepared using the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing and sequencing libraries prepared using the Nextera XT DNA library preparation kit (Illumina). The resulting libraries were evaluated using a 4200 TapeStation (Agilent Technologies) and quantified by qPCR. Libraries were pooled and sequenced on an Illumina NovaSeq SP or S1 flow cell using paired-end, 50 bp reads. The E6.5 ExE ∆G9a-Glp sample was isolated and processed into WGBS libraries using the Accel-NGS Methyl-seq kit as described in (Grosswendt et al., 2020) and sequenced on an Illumina NovaSeq using paired-end, 150 bp reads.

value: ExE (Extraembryonic Ectoderm)

tag: age

tag: background

tag: genotype

value: {delta}Eed

value: M

tag: embryo


title: MDAMB231Br_Mouse_Model

city: San Francisco

first: Hugo

last: Gonzalez

state: California

address: 513 Parnassus Avenue

department: Anatomy

institute: University of California San Francisco

data_processing:
After sequencing attemping 50,000 counts per cell captured by the 10X chip, Cell Ranger count pipeline (Version 3.0.2 from 10X Genomics) was used to map the FASTQ files to the human genome GRCh38, which generates a gene vs cell expression matrix (See Matrix.mtx.gz and Metrics_Summary.csv files).
The LogNormalized_Data was generated for each sample using the Seurat NormalizeData function. Briefly, counts for each cell are divided by the total counts for that cell and multiplied by the scale.factor 10000. This is then natural-log transformed using log1p
Genome_build: GRCh38
Supplementary_files_format_and_content: raw counts matrix
Supplementary_files_format_and_content: Features for downstream processing
Supplementary_files_format_and_content: Single Cell barcodes for downstream processing
Supplementary_files_format_and_content: Cell Ranger Quality Metrics per each sample
Supplementary_files_format_and_content: Normalized Expression per each sample
Supplementary_files_format_and_content: Annotations of the Cell types described in the study.

source_name: Human Breast Cancer Cell Line

extract_protocol: Single-cell libraries were generated via the Chromium Controller and the Single Cell Reagent Kit 3’ v2 (10x Genomics, Pleasanton, CA) according to the manufacturer’s instructions

tag: type of tumor

value: Experimental Brain Metastasis

value: Breast Cancer Brain Metastasis


title: HC1_sp2_Normal_Control_ox21_p33

value: male


title: lung cancer tissue with only extracranial metastasis, biological rep17


title: HC2_sp2_Normal_Control_ox21_p12


title: lung cancer tissue with only extracranial metastasis, biological rep18


title: lung cancer tissue with only extracranial metastasis, biological rep16


title: HC1_sp2_Normal_Control_ox21_p36


title: 22_I_epi_Eed

source_name: Epiblast

value: Epiblast


title: Rhabdomyosarcoma

source_name: Human Brain Metastasis

value: Metastatic Tumor, Brain Tumor

value: Rhabdomyosarcoma Brain Metastasis


title: HC1_sp2_Normal_Control_ox21_p30


title: 21_III_ExE_Eed


title: HC2_sp2_Normal_Control_ox21_p6


title: HC1_sp2_Normal_Control_ox21_p27


title: 21_I_epi_Eed


title: 23_I_epi_Eed

value: F


title: HC1_sp2_Normal_Control_ox21_p24


title: Renal_Cell_Carcinoma

value: Renal Cell Carcinoma Brain Metastasis


title: 77_I_epi_Rnf2


title: HC1_sp2_Normal_Control_ox21_p21


title: Unknown_Carc.

value: Unknown Carcinoma Brain Metastasis


title: 76_III_ExE_Rnf2


title: HC1_sp2_Normal_Control_ox21_p18


title: lung cancer tissue with only extracranial metastasis, biological rep12

value: lung


title: lung cancer tissue with only extracranial metastasis, biological rep11


title: 75_III_ExE_Rnf2


title: Colorectal

value: Colorectal Cancer Brain Metastasis


title: 75_I_epi_Rnf2


title: HC1_sp2_Normal_Control_ox21_p12

value: Primary Human Fibroblast (breast)


title: lung cancer tissue with only extracranial metastasis, biological rep15


title: HC1_sp2_Normal_Control_ox21_p15

value: Normal


title: lung cancer tissue with only extracranial metastasis, biological rep14


title: HC1_sp2_Normal_Control_ox21_p9

value: Control


title: Lung_3

value: Lung Cancer Brain Metastasis


title: lung cancer tissue with only extracranial metastasis, biological rep10


title: 74_III_ExE_Rnf2

value: ExE (Extraembryonic Ectoderm)


title: 74_I_epi_Rnf2

value: M


title: HC1_sp2_Normal_Control_ox21_p6


title: Lung_1


title: 73_III_ExE_Rnf2


title: lung cancer tissue with only extracranial metastasis, biological rep8


title: lung cancer tissue with only extracranial metastasis, biological rep13


title: SURF1_3_sp2_SURF1_Mutation_Control_ox21_p29

source_name: Primary Human Fibroblast (forearm)

value: Primary Human Fibroblast (forearm)

value: female


title: Breast_3

value: Breast Cancer Brain Metastasis


title: 72_I_epi_Rnf2

value: Epiblast


title: lung cancer tissue with only extracranial metastasis, biological rep5


title: SURF1_3_sp2_SURF1_Mutation_Control_ox21_p26


title: Breast_2

value: Metastatic Tumor, Brain Tumor


title: 71_III_ExE_Rnf2


title: SURF1_3_sp2_SURF1_Mutation_Control_ox21_p23


title: Lung_2


title: 70_I_epi_Rnf2


title: 71_I_epi_Rnf2


title: 43_III_ExE_G9a-Glp


title: lung cancer tissue with only extracranial metastasis, biological rep4


title: SURF1_3_sp2_SURF1_Mutation_Control_ox21_p14


title: lung cancer tissue with only extracranial metastasis, biological rep3


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p31

value: male


title: lung cancer tissue with only extracranial metastasis, biological rep2


title: lung cancer tissue with only extracranial metastasis, biological rep6


title: SURF1_3_sp2_SURF1_Mutation_Control_ox21_p17


title: lung cancer tissue with only extracranial metastasis, biological rep7


title: lung cancer tissue with only extracranial metastasis, biological rep9


title: lung cancer tissue without metastasis, biological rep8

description: Gene expression data from lung cancer tissue without metastasis

source_name: lung cancer tissue without metastasis


title: STARR-seq GP5d random enhancers from binary STARR-seq, replicate 2

city: Helsinki

first: Teemu

last: Kivioja

address: Haartmaninkatu 8

country: Finland

institute: University of Helsinki

description: sequenced random enhancer RNA, can be connected to the promoter only through the input pairs

data_processing:
Library strategy: STARR-seq
The STARR-seq enhancer sequences derived from RNA were mapped to corresponding promoter-enhancer pairs in the input DNA by exact matches of the first 20 bases of the 150 bases long enhancer sequences.
Duplicate reads were removed by sorting the sequences four times based on 40 bases long non-overlapping subsequences from base 16 to 135 and taking only one sequence per identical subsequence at each sort step.
Promoter and enhancer sequences were filtered separately by removing 1) all adapter sequences that included some (partial) adapter sequence according to cutadapt (version 1.9.1), 2) sequences that mapped to plasmid backbone sequence using bowtie2, and 3) outlier sequences in terms of nucleotide composition (count of any nucleotide more than 3 median absolute deviations higher than the median count).
For promoter-enhancer pair analyses, the remaining promoter-enhancer pairs were collected and pairs containing highly similar sequence as promoter and enhancer were removed.
The motifs were matched to sequences using program MOODS (version 1.9.3). The matching was done separately for each strand using p-value thresholds 1e-6 (promoter analysis) and 5e-5 (promoter-enhancer pair analysis) and and strand- and sample-specific nucleotide frequencies.
In the promoter analysis, the number of motif  matches for each motif in the sequences was counted so that overlapping matches in different strands were counted only once and the fold changes between the motif match counts in RNA and  input DNA were estimated using the function PsiLFC in R package lfc.
In the promoter-enhancer pair analysis, for each motif pair, one having a binding site in the promoter, the other in the enhancer of a pair, the expected number of promoter-enhancer pairs was compared to  observed number. The expected number was calculated from the total numbers of promoter and enhancer motif sites assuming that they occur independently of each other. For each pair a p-value was calculated for the null hypothesis that the motifs occur independently using binomial test and corrected for multiple testing using Holm's method.
Supplementary_files_format_and_content: promoter only files are tab delimited text files, the columns are: name (name of the TF), pfm (motif used in the sequence matching), total.count (count of motif matches in STARR-seq RNA), input.total.count (count of motif matches in input DNA), effect (log2 fold change between STARR-seq RNA and input DNA estimated by lfc)
Supplementary_files_format_and_content: pair file (STARRseq_RandomPE_GP5d_rep1.p5e-5.pair_counts.tsv) is a tab delimited text file, the columns are: promoter.name (name of the promoter TF), enhancer.name (name of the enhancer TF),  promoter.pfm, enhancer.pfm (motifs used in the sequence matching),   promoter.count (promoter motif match count), enhancer.count (enhancer motif match count),  pair.count (count of the motif matches in the same promoter-enhancer pair),  expected.pair.count (expected count assuming that matches are independent),   pval.adj (multiple testtin adjusted p-value for pair count assuming independence of motif matches)

source_name: synthetic

growth_protocol: GP5d cells were cultured in DMEM, HepG2 cells in MEM and RPE cells with DMEM/F12  media supplemented with 10% FBS, 2 mM L-glutamine and 1% penicillin-streptocmycin. Cells were checked for mycoplasma contamination and were passaged at 80% confluency. For each random promoter-enhancer binary STARR-seq experiment, a total of 250 million GP5d cells per replicate, and 400 million HepG2 and 480 million RPE cells  were transfected.

extract_protocol:
Total RNA was isolated Qiagen RNeasy maxi kit after 24 hours of transfection followed by polyA(+) purification using direct mRNA purfication beads (ThermoFisher).
STARR-seq reporter and input library was constructed with minor modifications as described in Arnold et al. Science 2013. First strand cDNA synthesis was done with 2.5-5 ug of polyA(+) RNA and with Superscript III (Invitrogen, #18080-044) using a reporter-RNA specific primer. This was followed by RNase A treatment for 1 h at 37˚C and purification. cDNA amplification was performed with reporter-specific nested cDNA primers corresponding to the respective STARR-seq reporter construct using KAPA HiFi PCR Master mix (Roche) in the same number of reactions as done for the reverse transcription. The final PCR reactions to produce Illumina-compatible sequencing libraries were prepared from the entire amplified cDNA using KAPA HiFi PCR Master mix (Roche) as descriubed in Arnold et al. Science 2013. All purifications were done using AMPure XP beads as per manufacturer’s instruction unless otherwise mentioned.
Illumina sequencing strategy adapted for random enhancer pCpG-free STARR-seq construct  using custom adapters, sequencing and index primers.

treatment_protocol: The cells were transfected with random enhancer STARR-seq library using transfex (ATCC) in GP5d cells, transfectin (Biorad) in HepG2 and FuGene HD (Promega) in RPE cells using one ug of library per one million cells.

tag: cell line

value: GP5d  colon carcinoma cells


title: 40_III_ExE_G9a-Glp

value: F


title: lung cancer tissue with only extracranial metastasis, biological rep1


title: 42_III_ExE_G9a-Glp


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p22


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p28


title: lung cancer tissue without metastasis, biological rep7


title: SURF1_3_sp2_SURF1_Mutation_Control_ox21_p20


title: STARR-seq GP5d random enhancers from binary STARR-seq, replicate 1


title: 40_I_epi_G9a-Glp


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p19


title: Input DNA control from HepG2 cells for ChIP-seq

library_source: genomic

data_processing:
The Illumina raw files were demultiplexed using bcl2fastq conversion, followed by alignment to the human genome  using bowtie and peak calling (narrow peaks for TF ChIP-seq and broad peaks for histone modifications) was performed using MACS2 using default parameters.
Genome_build: hg19
Supplementary_files_format_and_content: MACS2 narrowPeak and broadPeak files

molecule: genomic DNA

source_name: HepG2 cell line

growth_protocol: GP5d cells were cultured in DMEM and HepG2 cells in MEM media with 10% FBS, 2 mM L-glutamine and 1% penicillin-streptocmycin. Cells were checked for mycoplasma contamination and were passaged at 80% confluency.

extract_protocol:
Chromatin immunoprecipitation (ChIP) was performed as previously described (Sahu et al. EMBO J 2011). For analyzing genomic occupancy of TP53, cells were treated with 350 uM 5-fluorouracil (Sigma) 24 h before harvesting the cells. Briefly, fresh formaldehyde-crosslinked chromatin from GP5d cells was used to immunoprecipitate DNA using Dynal-bead coupled antibodies for TFs or histone modifications and for normal rabbit, mouse and goat IgG, followed by standard ChIP-seq library preparation for Illumina sequencing. The libraries were single-read sequenced on HiSeq4000.
The immunoprecipiated DNA was end-repaired, dA tailed and adapter ligated followed by PCR enrichment of adapter-ligated ChIP DNA as described in Sahu et al. EMBO J. 2011
Illumina TruSeq library strategy

treatment_protocol: Treatment when required for the cells were with DMSO as control, STARR-seq library transfection using Transfex (ATCC) in GP5d cells and Transfectin (Biorad) in HepG2 cells and 350 uM 5-fluorouracil (5-FU) for 24 hours.

value: liver cancer cell line

tag: treatment

value: Mock control

value: HepG2 cell line


title: lung cancer tissue without metastasis, biological rep5

value: lung


title: lung cancer tissue without metastasis, biological rep6


title: 38_I_epi_G9a-Glp


title: 37_III_ExE_G9a-Glp


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p16


title: STARR-seq random binary DNA library

description: sequenced random promoter enhancer pairs that can be used to connect the promoters to the sequences enhancers

tag: input

value: random binary DNA library


title: 41_III_ExE_G9a-Glp


title: Mouse IgG for HepG2-SS for ChIP-seq

value: STARR-seq (SS) library transfection for 24 hours

tag: antibody

value: Santa-Cruz, sc-2025


title: 37_I_epi_G9a-Glp


title: Mouse IgG for HepG2-5-FU for ChIP-seq

value: 350 uM 5-fluorouracil (5-FU) treatment for 24 hours


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p13

value: Control


title: lung cancer tissue without metastasis, biological rep4


title: lung cancer tissue without metastasis, biological rep2


title: lung cancer tissue without metastasis, biological rep3


title: 36_III_ExE_G9a-Glp

value: ExE (Extraembryonic Ectoderm)

value: M


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p32

value: Primary Human Fibroblast (forearm)


title: lung cancer tissue without metastasis, biological rep1


title: SURF1_2_sp2_SURF1_Mutation_Control_ox21_p10


title: Rabbit IgG for HepG2-5-FU for ChIP-seq

value: Santa-Cruz, sc-2027


title: Rabbit IgG for HepG2-SS for ChIP-seq


title: 35_III_ExE_G9a-Glp


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p26


title: 36_I_epi_G9a-Glp

value: Epiblast


title: lung cancer tissue with initial brain metastasis, biological rep5

description: Gene expression data from lung cancer tissue with initial brain metastasis


title: lung cancer tissue with initial brain metastasis, biological rep4


title: lung cancer tissue with initial brain metastasis, biological rep3


title: Rabbit IgG for HepG2-Control for ChIP-seq


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p20

value: male


title: ChIP-seq HepG2-5-FU IRF3

description: Warning: IRF3 ChIP-seq signals were weak in HepG2 cells based on the lack of peak overlaps with motif sites and the manual inspection of the top peaks.

value: Santa-Cruz sc-33641x


title: 35_I_epi_G9a-Glp

value: F


title: Mouse IgG for HepG2-Control for ChIP-seq

value: liver cancer cell line


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p17


title: lung cancer tissue with initial brain metastasis, biological rep2


title: 34_III_ExE_G9a-Glp


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p14


title: ChIP-seq HepG2-5-FU TP53

value: Santa-Cruz, sc-126x


title: 46_III_ExE_Dnmt1


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p11


title: 34_I_epi_G9a-Glp


title: lung cancer tissue with non initial brain metastasis, biological rep11

description: Gene expression data from lung cancer tissue with non initial brain metastasis


title: lung cancer tissue with initial brain metastasis, biological rep1


title: 45_III_ExE_Dnmt1


title: 46_I_epi_Dnmt1


title: ChIP-seq HepG2-SS H3K27ac

value: Diagenode, #C15410196

value: HepG2 cell line


title: ChIP-seq HepG2-SS IRF3


title: Work-2-2

city: Daegu

first: JA WOOK

last: KOO

address: 61 Cheomdan-ro, Dong-gu

country: South Korea

institute: Korea Brain Research Institute

data_processing:
Low quality reads were filtered according to the following criteria; reads contain more than 10% of skipped bases (marked as ‘N’s), reads contain more than 40% of bases whose qualityscores are less than 20 and reads whose average quality scores of each read is less than 20. The whole filtering process was performed using the in-house scripts.
Filtered reads were mapped to the mouse reference genome (Ensembl release 77) using the aligner Tophat
Gene expression level was measured with Cufflinks v2.1.1 (Trapnell C. et al, 2012) using the gene annotation database of Ensembl release 77.
Non-coding gene region was removed with -mask option. To improve the accuracy of measurement, multi-read-correction and fragbias-correct options were applied. '-max-bundle-frags' option was set to 10,000,000 to estimate the highly expressed genes.
All other options were set to default values. Differentially expressed genes were identified using Cuffdiff tool with default parameter setting with a significance of p-value < 0.05
Genome_build: version 77 of Rattus norvegicus reference genome Rnor_5.0
Supplementary_files_format_and_content: tab-delimited text files include FPKM for each sample derived from Cufflinks.

organism: Rattus norvegicus

source_name: brain cells

growth_protocol: Young-adult male Sprague-Dawley rats (~8–10 weeks old) were individually housed in a climate-controlled colony room. After one week of free access to food and water and habituation to handling, animals were placed on standard food restriction to gradually reach and maintain 80–85% normal weight. All tests were performed during the dark phase of a 12-h light/dark cycle

extract_protocol:
Animals were rapidly decapitated 18~19 h after the worker-parasite relationship transpired in group testing. Additional four animals not exposed to the Skinner box were sacrificed as home-cage controls. Brains were removed and coronal slices (2 mm) were fleshly dissected in a cold brain matrix. ACC were then microdissected, using a dissecting microscope and reference coordinates obtained from the Paxinos and Watson rat brain atlas. RNA was isolated with TriZol reagent (Invitrogen) and purified with RNeasy Micro Kits (Qiagen). All RNA samples were determined to have RIN values > 8.5 (BioAnalyzer, Agilent) for RNA-sequencing.
RNA quality was assessed by analysis of rRNA band integrity on an Agilent RNA 6000 Nano  kit (Agilent Technologies, CA). Ahead of cDNA library construction, the 1ug of total RNA and magnetic beads with Oligo (dT) were used to enrich poly (A) mRNA from it. Then, the purified mRNAs were disrupted into short fragments, and the double-stranded cDNAs were immediately synthesized. The cDNAs was subjected to end-repair, poly (A) addition, and connected with sequencing adapters using the TruSeq RNA sample prep Kit (Illumina, CA). The suitable fragments automatically purified by BluePippin 2% agarose gel cassette (Sage Science, MA) were selected as templates for PCR amplification. The final library sizes and qualities were evaluated electrophoretically with an Agilent High Sensitivity DNA kit (Agilent Technologies, CA) and the fragment was found to be between 350–450 bp. Subsequently, the library was sequenced using an Illumina NovaSeq sequencer (Illumina, CA).

treatment_protocol: Animals underwent successive 90 min sessions of habituation (2 days of chamber familiarization in customized Skinner boxes (60x60x60 cm) and shaping-continuous reinforcement schedule training (variable days to reach 100 lever presses/session for 3+ days) prior to group testing. On the first day of group testing, the lever-pressing behavior rapidly plummeted in all rats (stalemate phase). The length of stalemate days varied between groups before a worker-parasite relationship emerged where one rat performed most of the lever presses, while the other two members consumed most of the food pellets. The criterion for worker-parasite phase was defined as > 200 lever presses by the worker rat, exceeding two parasites’ lever presses by > 150 for 3+ consecutive sessions.

tag: strain

value: Sprague dawley rats

value: anterior cingulate cortex

tag: behavioral phenotype

value: Worker in a social dilemma setting


title: Work-2-1


title: SURF1_1_sp2_SURF1_Mutation_Control_ox21_p23


title: 45_I_epi_Dnmt1


title: ChIP-seq HepG2-SS TP53

value: STARR-seq (SS) library transfection for 24 hours


title: lung cancer tissue with non initial brain metastasis, biological rep10

value: lung


title: ChIP-seq HepG2-Control TP53

value: Mock control


title: ChIP-seq HepG2-5-FU H3K27ac

value: 350 uM 5-fluorouracil (5-FU) treatment for 24 hours


title: 44_I_epi_Dnmt1

value: M


title: ChIP-seq HepG2-Control IRF3


title: Work-1-1


title: lung cancer tissue with non initial brain metastasis, biological rep6


title: 44_III_ExE_Dnmt1

value: ExE (Extraembryonic Ectoderm)


title: lung cancer tissue with non initial brain metastasis, biological rep5


title: lung cancer tissue with non initial brain metastasis, biological rep8


title: Work-1-2


title: 55_III_ExE_Bdf1xCast

value: WT


title: lung cancer tissue with non initial brain metastasis, biological rep9


title: 55_I_epi_Bdf1xCast

value: Epiblast


title: lung cancer tissue with non initial brain metastasis, biological rep4


title: Para-1-2

value: male

value: Parasite in a social dilemma setting


title: HepG2-5FU-48h replicate 3

data_processing:
The transcript level counts were estimated with kallisto (version 0.46.1) in strand-specific mode (option --rf-stranded) using Ensembl transcript annotation (Ensembl GRCh37 release-101 cDNA file)
Differential expression analysis was then done with sleuth (version 0.30.0). Each treatment and time combination was treated as separate condition and all conditions where put one model. Then differential expression was estimated by comparing individual conditions to control condition using wald test.
Genome_build: hg19
Supplementary_files_format_and_content: sleuth differential expression results as tab delimited text file, columns are: target_id (Ensembl gene id) , ext_gene (gene symbol), num_aggregated_transcripts (number of transcripts used in gene level analysis), pval (p-value of gene differential expression), qval (false discovery rate adjusted p-value, using Benjamini-Hochberg), qval_log10 (-log10 of q-val),  transcript_target_id (the Ensembl identifier of the transcript with the smallest p-value),  transcript_pval (the p-value of the transcript with the smallest p-value),  transcript_qval (the q-value of the transcript with the smallest p-value), transcript_b_log2 (log2 transformed fold change estimate of the transcript with the smallest p-value). In the table RNA_seq_2020-12-17_HepG2_5FU_SS_sleuth_genes_summary.tsv column suffix indicates the condition tested against mock. In the table  RNA_seq_2020-12-17_HepG2vsGP5dSS_sleuth_genes_summary.tsv GP5d expression is compared against HepG2 expression.

extract_protocol:
RNA was isolated after 24 and 48 hours using Qiagen RNeasy kit following manufacturer's instruction
Stranded RNA-seq library was preapred using KAPA stranded mRNA-seq library preparation kit following manufacturer's instruction
Illumina Tru-seq library strategy

treatment_protocol: Treatment for the cells were with DMSO as control, STARR-seq library transfection using Transfex (ATCC) in GP5d cells and Transfectin (Biorad) in HepG2 cells and 350 uM 5-fluorouracil (5-FU) for 24 hours.

tag: cell type

value: liver cancer cell line

value: 350 uM 5-fluorouracil (5-FU) treatment for 48 hours


title: HepG2-5FU-48h replicate 2

description: RNA_seq_2020-12-17_HepG2_5FU_SS_sleuth_genes_summary.tsv


title: lung cancer tissue with non initial brain metastasis, biological rep7


title: lung cancer tissue with non initial brain metastasis, biological rep3


title: HepG2-5FU-48h replicate 1


title: lung cancer tissue with non initial brain metastasis, biological rep2


title: 54_I_epi_Bdf1xCast


title: Para-1-1


title: Control-2-2

value: Home cage control


title: HepG2-SS-48h replicate 3

value: STARR-seq (SS) library transfection for 48 hours

value: HepG2 cell line


title: Control-2-1

value: Sprague dawley rats

value: anterior cingulate cortex


title: ChIP-seq HepG2-Control H3K27ac

value: Diagenode, #C15410196


title: 53_III_ExE_Bdf1xCast

value: F


title: 53_I_epi_Bdf1xCast


title: Control-1-2


title: lung cancer tissue with non initial brain metastasis, biological rep1

value: lung


title: HepG2-SS-48h replicate 1


title: Control-1-1


title: Gp5d-SS-24h replicate 3

description: RNA_seq_2020-12-17_HepG2vsGP5dSS_sleuth_genes_summary.tsv

source_name: GP5d cell line

value: colon cancer cell line

value: STARR-seq (SS) library transfection for 24 hours

value: GP5d cell line


title: 54_III_ExE_Bdf1xCast

value: ExE (Extraembryonic Ectoderm)

value: WT

value: M


title: 51_III_ExE_Bdf1xCast


title: 51_I_epi_Bdf1xCast

value: Epiblast


title: Gp5d-SS-24h replicate 2


title: 50_III_ExE_Bdf1xCast


title: HepG2-SS-48h replicate 2

value: liver cancer cell line


title: VA_2h_rep2

city: Beijing

first: Luming

last: Zou

state: PR

address: Haidian strict, Xiang Mountain South Road, Xiang Mountain South Village 20#

department: Institute of Botany

institute: University of Chinese Academy of Sciences

data_processing:
Raw sequence reads were initially processed by FASTQC for quality control, and then adapter sequences and poor quality reads were removed by using CUTADAPT
Quality filtered reads were then mapped to grape genome using BWA
Peak-calling were calculated by using MACS2
Genome_build: 12X grape genome of IGGP
Supplementary_files_format_and_content: bed files generated by MACS2

organism: Vitis amurensis

source_name: in vitro plants

growth_protocol: In vitro plants of V. amurensis were subcultured monthly in half strength B5 medium (PhytoTech Lab, USA)supplemented with 0.2 mg/L IBA under 16/8 (light/dark) condition

extract_protocol:
Harvest and count cells;Centrifuge 50,000 cells 5 min at 500 × g, 4°C;Wash cells once with 50 μl of cold PBS buffer. Centrifuge 5 min at 500 × g, 4°C;Gently pipet up and down to resuspend the cell pellet in 50 μl of cold lysis buffer. Centrifuge immediately for 10 min at 500 × g, 4°C;Discard the supernatant, and immediately continue to transposition reaction;Transposition reaction using transposition reaction mix;Resuspend nuclei pellet (from step 5) in the transposition reaction mix;Incubate the transposition reaction at 37°C for 30 min;Immediately following transposition, purify using a Qiagen MinElute PCR Purification Kit;Elute transposed DNA in 10 μl elution buffer (Buffer EB from the MinElute kit consisting of 10 mM Tris·Cl, pH 8);PCR amplification.
ATAC-seq libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: in vitro plants with uniform growth status were transferred to a prechilled incubator set to 4°C and constant light (approximately 100 μmol m-2 s-1). Samples were collected at 2 h after cold treatment (CT2). Untreated plants cultured at 26°C under the same light condition were sampled as the control (WT0).

tag: stress

value: cold

value: leaf

value: Wild-type

value: one-month-old


title: Gp5d-SS-24h replicate 1


title: 50_I_epi_Bdf1xCast

tag: Sex


title: HepG2-5FU-24h replicate 3

value: 350 uM 5-fluorouracil (5-FU) treatment for 24 hours

value: HepG2 cell line


title: 49_I_epi_Bdf1xCast


title: HepG2-5FU-24h replicate 2


title: 49_III_ExE_Bdf1xCast


title: VA_0h_rep3

value: control


title: VA_2h_rep3


title: HepG2-SS-24h replicate 3


title: HepG2-5FU-24h replicate 1


title: ∆UR1-EBNA1_3

city: Madison

first: Bill

last: Sugden

state: WI

address: 1111 Highland Ave

institute: University of Wisconsin-Madison

description: Biological replicate 3 of 3. Donor 27 B-cells infected with ΔUR1-EBNA1-EBV

hyb_protocol: Equal masses of Cy3- and Cy5-labeled samples were co-hybridized to microarrays.

scan_protocol: Scanned on an Agilent G2505B Scanner

data_processing: Agilent Feature Extraction Software (v 9.1.3.1) was used for background subtraction and LOWESS normalization.

source_name: ∆UR1-EBNA1-EBV Bcells

label_protocol: 150 ng of RNA was reverse transcribed with an oligo d(T) promoter primer into cDNA using the Agilent Quick Amp Kit, Two Color per manufacturer's protocol.  The cDNA was then transcribed into cRNA containing Cy3 or Cy5 using the Agilent T7 RNA polymerase transcription kit.

growth_protocol: Cells were grown in RPMI-1640 and 10% fetal bovine serum (supplemented with penicillin and streptomycin).

extract_protocol: Total RNA was extracted using TRIzol reagent per manufacturer's protocol

treatment_protocol: There were no additional treatments applied to these cells.

tag: donor

value: unrelated third donor

tag: cell strain

value: B-cell strain

tag: ebv status

value: {delta}UR1-EBNA1 EBV Positive

source_name: Donors 20 and 27 ΔEBNA1-EBV infected cells; pooled

value: {delta}EBNA1-EBV Positive


title: VA_0h_rep2

tag: tissue

tag: age


title: Donor 27 ∆EBNA1_1

description: Biological replicate 1 of 3. Donor 27 B-cells infected with ΔEBNA1-EBV

source_name: Donor 27 ∆EBNA1-EBV Bcells


title: ∆UR1-EBNA1_2

description: Biological replicate 2 of 3. Donor 27 B-cells infected with ΔUR1-EBNA1-EBV


title: Donor 27 ∆EBNA1_3

description: Biological replicate 3 of 3. Donor 27 B-cells infected with ΔEBNA1-EBV


title: Donor 27 ∆EBNA1_2

description: Biological replicate 2 of 3. Donor 27 B-cells infected with ΔEBNA1-EBV


title: Para-2-2

value: Sprague dawley rats

value: male

value: anterior cingulate cortex

value: Parasite in a social dilemma setting


title: ∆UR1-EBNA1_1

description: Biological replicate 1 of 3. Donor 27 B-cells infected with ΔUR1-EBNA1-EBV


title: 48_III_ExE_Bdf1xCast

value: ExE (Extraembryonic Ectoderm)

tag: background

tag: genotype

value: WT

value: M


title: Donor 20 ∆EBNA1_2

description: Biological replicate 2 of 3. Donor 20 B-cells infected with ΔEBNA1-EBV

source_name: Donor 20 ∆EBNA1-EBV Bcells


title: HepG2-SS-24h replicate 2

value: liver cancer cell line

value: STARR-seq (SS) library transfection for 24 hours


title: VA_0h_rep1

value: leaf

value: Wild-type

value: one-month-old


title: VA_2h_rep1

value: cold


title: Donor 20 ∆EBNA1_3

description: Biological replicate 3 of 3. Donor 20 B-cells infected with ΔEBNA1-EBV


title: 59_III_ExE_CastxBdf1

value: F

tag: embryo


title: 48_I_epi_Bdf1xCast

value: Epiblast


title: Control cells Replicate 3 Batch 2

city: New Haven

first: Yong

last: Zhu

state: CT

address: 60 College Street

institute: Yal University

hyb_protocol: Oligoarray control targets and hybridization buffer were added, and samples were applied to Affymetrix GeneChip arrays.

scan_protocol: After hybridization, slides were washed and scanned by GeneChip Scanner 3000.

data_processing: The Expression Console software also acquires and converts hybridization intensity data into a presence/absence call for each gene using appropriate algorithms. normalization method: SST-RMA

source_name: Control  cells

label_protocol: 5 µg of total RNA was primed with 2 µl of 100 µM T16N2 DNA primer at 70°C for 10 min, then reversed transcribed at 42°C for 1 h in the presence of 400 U SuperScript II RTase (Invitrogen), and 100 µM each dATP, dTTP, dGTP, with 25 µM dCTP, 25 µM Cy3-labe

growth_protocol: Cells were grown in Eagle's Minimum Essential Medium (EMEM) with 10% fetal bovine serum and were maintained at 37°C and 5% CO2.

extract_protocol: After 48 h treatment, total RNA extracted using Trizol following manufacturer's instructions.

treatment_protocol: Valeric acid (Sigma-Aldrich, USA) was added to each well of 6-well culture plates (2ml culture medium/well) to a final concentration of 850 µM.

tag: cell line

value: Hep3B (human liver cancer)


title: HepG2-SS-24h replicate 1

tag: treatment

value: HepG2 cell line


title: 59_I_epi_CastxBdf1


title: HepG2-Control replicate 3

value: Mock control


title: HepG2-Control replicate 1


title: 58_III_ExE_CastxBdf1


title: HepG2-Control replicate 2


title: 57_III_ExE_CastxBdf1


title: Control cells Replicate 2 Batch 2


title: Donor 27 WT EBV_1

description: Biological replicate 1 of 3. Donor 27 B-cells infected with WT-EBV

source_name: Donor 27 WT EBV Bcells

value: B-cell strain

value: WT-Positive

value: {delta}EBNA1-EBV Positive


title: Donor 27 WT EBV_2

description: Biological replicate 2 of 3. Donor 27 B-cells infected with WT-EBV


title: Donor 27 WT EBV_3

description: Biological replicate 3 of 3. Donor 27 B-cells infected with WT-EBV


title: 58_I_epi_CastxBdf1


title: MDA18010031_N711

first: Honglei

last: Dang

address: 18 Life Science Parkway, Changping District

institute: National Engineering Research Center for Beijing Biochip Technology

data_processing:
Raw image data files obtained from high-throughput sequencing was delivered to Phred base calling.
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to whole genome using HISAT2 software.
Fragments Per Kilobase of exon per Million fragments (FPKM) were calculated. In short, exons from all isoforms of a gene were merged to create one meta-transcript. The number of reads falling in the exons of this meta-transcript were counted and normalized by the size of the meta-transcript and by the size of the library.
Genome_build: hg19 (GRCh37)
Supplementary_files_format_and_content: *_ENSEMBL.count.txt: Tab-delimited text files include raw read counts for each Sample.
Supplementary_files_format_and_content: *.fpkm.txt: Tab-delimited text files include FPKM values for each Sample.

growth_protocol: MDA-MB-231 cells were seeded at 5x10^5 cells/well in 6-well plates.

extract_protocol:
RNA was harvested using Trizol reagent.
RNA libraries were prepared for sequencing using standard Illumina protocols.

treatment_protocol: Treated with 1μg/mL CCE for 24 h.

value: Breast cancer cell line

value: Carpesium cernuum extract (CCE)


title: ATAC-seq HepG2-5-FU

data_processing:
The samples were demultiplexed and paired-end fastq files were processed using an in-house pipeline comprising of TrimGalore (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/), BWA aligner, Picard (http://broadinstitute.github.io/picard/) and broad-peak calling by MACS2.
Genome_build: hg19
Supplementary_files_format_and_content: MACS2 broad peak format

extract_protocol:
The cells were extracted and processed as per ATAC-seq protocol (Buenrostro et al. Nature Methods 2013)
The ATAC-seq library was prepared as per the ATAC-seq protocol (Buenrostro et al. Nature Methods 2013)

value: 350 uM 5-fluorouracil (5-FU) treatment for 24 hours


title: MDA18010029_N709

value: Control


title: 56_III_ExE_CastxBdf1

source_name: ExE

value: ExE (Extraembryonic Ectoderm)

value: WT


title: Donor 20 ∆EBNA1_1

description: Biological replicate 1 of 3. Donor 20 B-cells infected with ΔEBNA1-EBV

source_name: Donor 20 ∆EBNA1 Bcells


title: Control cells Replicate 2 Batch 1


title: Donor 20 WT EBV_3

description: Biological replicate 3 of 3. Donor 20 B-cells infected with WT-EBV

source_name: Donor 20 WT EBV Bcells


title: 57_I_epi_CastxBdf1

source_name: Epiblast

value: M


title: Donor 20 WT EBV_1

description: Biological replicate 1 of 3. Donor 20 B-cells infected with WT-EBV


title: Donor 20 WT EBV_2

description: Biological replicate 2 of 3. Donor 20 B-cells infected with WT-EBV


title: Control cells Replicate 1 Batch 1


title: Control cells Replicate 1 Batch 2


title: ATAC-seq HepG2-SS

value: liver cancer cell line

value: STARR-seq (SS) library transfection for 24 hours


title: ATAC-seq HepG2-Control


title: STARR-seq TF motif input library, pCpG-free- EF1alpha-SS vector and pGL4.10-Sasaki-SS vector

description: DNA input library, CpG-free E1alpha promoter and Sasaki promoter

data_processing:
Library strategy: STARR-seq
For each TF motif consensus pattern (see the publication for details of the synthetic sequence design), the reads containing the pattern were counted for the two sequence contexts and promoters
The fold change between RNA and input DNA was estimated using the function PsiLFC in R package lfc for each combination of motif pattern, sequence context, and promoter
Supplementary_files_format_and_content: tab-delimited file with the following columns (see the publication for details of the synthetic sequence design): pfm  (motif embedded in the sequence),  tf (TF of the motif),   configuration (C=consensus, R=reverse complement of consensus),  gap (gap between the instances of the motif), context (UMI length and the context sequence name), input.count (count of the motif pattern in input DNA), rna.count (count of the motif pattern in the STARR-seq RNA),  effect (log2fold change compared to input estimated using R lfc package),  promoter (name of the promoter, E1a=E1alpha)

organism: synthetic construct

growth_protocol: GP5d cells were cultured in DMEM with 10% FBS, 2 mM L-glutamine and 1% penicillin-streptocmycin. Cells were checked for mycoplasma contamination and were passaged at 80% confluency. For each motif STARR-seq experiment, a total of 50 and 35 million GP5d cells were transfected for the libraries in pGL4.10-Sasaki-SS (a) and pCpG-free-EF1α-SS (b) vectors, respectively.

extract_protocol:
Total RNA was isolated Qiagen RNeasy maxi kit after 24 hours of transfection followed by polyA(+) purification using direct mRNA purfication beads (ThermoFisher).
First strand cDNA synthesis was done with 2.5-5 ug of polyA(+) RNA and with Superscript III (Invitrogen, #18080-044) using a reporter-RNA specific primer. This was followed by RNase A treatment for 1 h at 37˚C and purification. cDNA amplification was performed with reporter-specific nested cDNA primers corresponding to the respective STARR-seq reporter construct using KAPA HiFi PCR Master mix (Roche) in the same number of reactions as done for the reverse transcription. The final PCR reactions to produce Illumina-compatible sequencing libraries were prepared from the entire amplified cDNA using KAPA HiFi PCR Master mix (Roche) as descriubed in Arnold et al. Science 2013. All purifications were done using AMPure XP beads as per manufacturer’s instruction unless otherwise mentioned.
Illumina sequencing strategy adapted for STARR-seq and for custom CpG-free vector using custom adapters, sequencing and index primers.

treatment_protocol: The cells were transfected with moitf STARR-seq library using transfex (ATCC) in GP5d cells and one ug of library was used per one million cells.

tag: library

value: TF motif input


title: RNA_mut_Tg500

status: Public on Nov 11 2021

city: Wako

first: Shintaro

last: Iwasaki

state: Saitama

address: 2-1, Hirosawa

department: Center for Pioneering Research

country: Japan

institute: RIKEN

description: RNA-Seq

data_processing:
Basecalling with Illumina Casava 1.8 software
3' adapter trimming with Fastp
Library sorting based on sample barcode sequence with custom script
Random barcode triming with custom script
Alignment to rRNA and other non-coding RNA with STAR v2.7.0a
Alignment to genome with STAR v2.7.0a
Read quantitation using custom scripts
Genome_build: hg38
Supplementary_files_format_and_content: text files contain three columns: 1. transcript name; 2. CDS region (nt) used for read counting; 3. read counts

source_name: HEK293 T-REx

growth_protocol: DMEM + GlutaMAX-I with 10% FBS at 5% CO2, 37°C

extract_protocol:
Cells were directly lysed in lysis buffer on culture dishes.
For ribosome profiling, RNase I treatment, ribosome pelleting, size selection, preadenylated linker ligation, rRNA depeletion, reverse transcription, cDNA circularization, and PCR amplification. For RNA-Seq, TruSeq Stranded mRNA Library Prep Kit (Illumina).
Ribosome profiling and RNA-seq

treatment_protocol: Cells were transfected with 6 µg of plasmids using TransIT-293 Reagent, incubated for 48 h, and treated with thapsigargin for 30 min at 37 °C.

value: HEK293 T-REx

value: naive

tag: plasmid

value: Thapsigargin 500 nM


title: 56_I_epi_CastxBdf1

value: Epiblast

value: F


title: RNA_mut_Tg50

description: RNA-Seq

value: Thapsigargin 50 nM


title: RNA_mut_DMSO2

description: RNA-Seq

value: DMSO


title: scRNAseq_Sox10_Cre_bact_BtR_150dpf_rep_2

city: Los Angeles

first: Gage

last: Crump

state: CA

address: 1425 San Pablo St.

department: Stem Cell

institute: USC

data_processing:
For scRNAseq libraries, Cellranger v3.0.0 (10X Genomics) was used for demultiplexing, alignment, and raw count matrix generation. The alignment was performed against zebrafish genome index (built with GRCz11.fa and GRCz11.98.gtf). For snATACseq libraries, Cellranger ATAC v1.2.0 (10X Genomics) was used for alignment against zebrafish genome index (built with GRCz11.fa, JASPAR2020, and GRCz11.98.gtf), peak calling, and peak-by-cell count matrix generation with default parameters. QC step for the library was performed along with the Cellranger or Cellranger ATAC alignment process.
We performed a second round of peak calling for our snATACseq data using package Snaptools and SnapATAC. We first removed cell debris, low-quality cells, and cell duplicates, by setting cutoffs based on percentage of reads in peaks (> 30 for 60 dpf, > 45 for 210 dpf, and > 50 for the rest) and fragment number within peaks (5,000 – 30,000 for 5 dpf, 1,000 – 11,000 for 14 dpf, and 1,000 – 20,000 for the rest).  To  recover every aligned fragment, we binned the genome into 5 kb sections and constructed the bin-by-cell matrices (bmats) for each library by Snaptools from the positional-sorted bam files generated by cellranger-atac. The cells were filtered, dimensionally reduced by diffusion map, and clustered with inputs of the first 34 dimensions followed the SnapATAC vignette. The specific peaks were called for each cluster by the wrapped MACS2 function in SnapATAC with parameter gsize = 1.5e9, shift = 100, ext = 200, and qval = 5e-2. The finalized and refined peak profile was derived by collapsing and merging all 175 individual peak files to about 450K peaks.
The count matrices of both scRNAseq and snATACseq data were analyzed by R package Seurat and Signac. The count matrices of each sample were aggregated if there is any replicate. For scRNAseq data, the matrices are normalized (NormalizeData) and scaled for the top 2,000 variable genes (FindVariableFeatures and ScaleData). The scaled matrices were dimensional reduced to 50 principal components (60 components for 150 dpf), which then subjected to neighbor finding (FindNeighbors, k = 20) and clustering (FindClusters, resolution = 0.8). The data were visualized through UMAP with 50 principal components as input. For snATACseq data, the matrices are dimensionally reduced 30 latent semantic indices (LSIs) through RunTFIDF and RunSVD functions. The neighbor finding, clustering, and visualization are performed with the second to the thirtieth LSIs as input (algoritm = 3 for FindClusters).
Genome_build: GRCz11
Supplementary_files_format_and_content: Each sample comes with four processed data files: a tab-delimited cell barcode file (tsv), a tab-delimited feature file with genes for scRNAseq or peaks for snATACseq (tsv), a sparse matrix of count table (mtx), and a cluster table (tsv). The previous three files are suffice for creating a single cell count matrix. The cluster table can be further added to recreat the corresponding cluster information as published.

molecule: polyA RNA

organism: Danio rerio

source_name: Cranial neural crest derived cells

growth_protocol: The Institutional Animal Care and Use Committee of the University of Southern California approved all animal experiments (Protocol 20771). Zebrafish embryos (Danio rerio) were raised in embryo media at 28.5°C. For adults, in the institute vivarium according to Protocol 20771.

extract_protocol:
Dissected heads from converted Sox10:cre; bactin:loxP-eGFP-loxP-DsRed fish were incubated in fresh Ringer’s solution 5-10 min, followed by mechanical and enzymatic dissociation by pipetting every 5 minutes in protease solution (0.25% trypsin (Life Technologies, 15090-046)), 1 mM EDTA, and 400 mg/ml Collagenase D (Sigma, 11088882001 in PBS) and incubated at 28.5°C for 20-30 minutes or until full dissociation. Reaction was stopped by 6X stop solution (6 mM CaCl2 and 30% fetal bovine serum (FBS) in PBS). Cells were pelleted (2000 rpm, 5 minute, 4 °C) and resuspended in suspension media (1% FBS, 0.8 mM CaCl2, 50 U/ml penicillin, and 0.05 mg/ml streptomycin (Sigma-Aldrich, St. Louis, MO) in phenol red-free Leibovitz’s L15 medium (Life Technologies)) twice. Final volumes of 500 µl resuspended cells were placed on ice and sorted by fluorescence activated cell sorting (FACS) to isolate live cells that excluded the cytoplasmic stain Zombie green (BioLegend, 423111) or the nuclear stain DAPI. Live cells were sorted into PBS solution containing 0.04% BSA and loaded to 10X Genomics microfluidic chips. The version 2 of Chromium Single Cell 3' Reagent Kits was used for RNA extraction. For snATACseq library construction, we used the same cell dissociation and sorting protocol as for scRNAseq, with isolation of live cells that excluded the cytoplasmic stain Zombie green (product information). Nuclei isolation was performed per manufacturer’s instructions (10X Genomic, protocol CG000169). Cells were incubated with lysis buffer on ice for 90 second, followed by integrity check of nuclei under fluorescence microscope with DAPI before library synthesis.
For scRNAseq, the cell lysis, polyA pull down, tagging with cell barcode, and RNA:DNA hybrid synthesis were performed in the GEMs per manufacturer's instruction. GEMs containing barcoded single-cell cDNA  were lysis for further fragmentation and ligation of illumina P5 and P7 ends. Libraries were sequenced to depths of at least 1,000,000 reads per cell for each library. For snATACseq, the open chromatins of the isolated nuclei were targeted and tagged by transposase, barcoded and ligated with Illumina P5 sequence in the individually-encapsulated GEMs per manufacturer's instruction. Barcoded single-nucleus genomic DNA were released from GEMs and pulled down for further ligation of library-specific index and Illumina P7 sequence. Libraries were sequenced to depths of at least 75,000 read pairs per nucleus for each library.

value: Cranial neural crest derived cells

tag: developmental stage

value: 150 dpf

tag: facs markers

value: Zombie- / dsRed+


title: scRNAseq_Sox10_Cre_bact_BtR_150dpf_rep_3

tag: cell type


title: scRNAseq_fliIa_eGFP_Sox10_dsRed_1.5dpf_rep_1

description: This dataset was use to identify common mesenchymal populations and specific cells derived in the Sox10:cre+  lineage.

value: 1.5 dpf

value: DAPI- / dsRed+/eGFP+


title: RNA_NSs_Tg50

description: RNA-Seq


title: RNA_NSs_DMSO2

description: RNA-Seq


title: RNA_NSs_Tg500

description: RNA-Seq


title: RNA_mut_DMSO1

description: RNA-Seq


title: scRNAseq_Sox10_Cre_bact_BtR_3dpf_rep_1

value: 3 dpf


title: scRNAseq_Sox10_Cre_bact_BtR_1.5dpf_rep_1


title: RNA_NSs_DMSO1

description: RNA-Seq


title: Valeric acid treated cells Replicate 2

source_name: Valeric acid treated cells

value: Hep3B (human liver cancer)


title: RNA_vec_Tg500

description: RNA-Seq


title: Valeric acid treated cells Replicate 1


title: Valeric acid treated cells Replicate 3


title: Ribo_mut_DMSO1

description: Ribosome profiling


title: Ribo_NSs_Tg500

description: Ribosome profiling


title: RNA_vec_DMSO2

description: RNA-Seq


title: RNA_vec_DMSO1

description: RNA-Seq


title: Ribo_mut_Tg500

description: Ribosome profiling


title: Ribo_mut_DMSO2

description: Ribosome profiling


title: Ribo_NSs_Tg50

description: Ribosome profiling


title: Ribo_vec_Tg50

description: Ribosome profiling


title: Ribo_vec_Tg500

description: Ribosome profiling


title: RNA_vec_Tg50

description: RNA-Seq


title: Ribo_NSs_DMSO2

description: Ribosome profiling


title: Ribo_NSs_DMSO1

description: Ribosome profiling


title: Ribo_vec_DMSO2

description: Ribosome profiling


title: Ribo_vec_DMSO1

description: Ribosome profiling


title: BAT preadipocyte differentiation day 8 EGCG replicate 3

city: Xinyang

first: pengpeng

last: Zhang

state: Henan

address: No.237 Nanhu Road Shihe District

institute: Xinayang Normal University

description:
mBE83
sample3_FPKM.txt

data_processing:
Quality control of sequences was examined with FastQC version 0.11.9. The clean data were obtained using the Fastp version 0.20.1 to remove reads with adapters, reads containing ploy-N and reads with low quality.
The clean reads were subjected to mapping with Mus musculus mm9 reference genome by HISAT2 version 2.2.0.
The reads numbers mapped to each gene were counted by HTSeq v0.11. The normalized expression level of each gene was calculated by the fragments per kilobase of exon per million reads (FPKM)
Genome_build: mm9
Supplementary_files_format_and_content: sample3_FPKM.txt: Matrix table with FPKM values for every gene and every sample.

source_name: BAT preadipocyte

growth_protocol: Primary WAT and BAT SVF cells were isolated using collagenase digestion as we previously described. Briefly, the inguinal WAT and interscapular BAT were collected from 6-week-old mice. Adipose tissue was cut into small pieces and digested with 1.5 mg ml-1 collagenase at 37 ℃ for 30-50 min. The digestions were terminated with DMEM containing 20% FBS, and filtered through 100-μm and 70-μm cells trainer to remove tissue debris. Cells were then centrifuged at 450g for 8 min and SVF cells pellet was resuspend. SVF cells were cultured in growth medium containing 20 % FBS, high glucose DMEM, at 37 ℃ with 5% CO2, culture medium was changed every 2 days. When the cells reached 90 % confluence, they were induced to adipogenic differentiation with induction medium, which contains DMEM, 10% FBS, 2.85 mM insulin, 0.3 mM dexamethasone and 0.63mM 3-isobutyl-methylxanthine for 4 days. Then the medium was switched to differentiation medium which contains DMEM, 10% FBS, 200 nM insulin and 10 nM T3 for another 4 days to induce the mature of adipocytes.

extract_protocol:
Total RNA was extracted from cells using Trizol Reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’ instructions.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: EGCG or DMSO was added into the cell medium

value: BAT preadipocyte

tag: strain

tag: time

value: post differentiation day 8

value: EGCG incubation


title: BAT preadipocyte differentiation day 8 control replicate 3

description:
mB83
sample3_FPKM.txt

value: control


title: BAT preadipocyte differentiation day 4 EGCG replicate 3

description:
mBE43
sample3_FPKM.txt

value: post differentiation day 4


title: BAT preadipocyte differentiation day 4 control replicate 3

description:
mB43
sample3_FPKM.txt


title: WAT preadipocyte differentiation day 8 EGCG replicate 3

description:
mWE83
sample3_FPKM.txt

source_name: WAT preadipocyte

value: WAT preadipocyte


title: Ribo_mut_Tg50

description: Ribosome profiling

value: HEK293 T-REx

value: naive


title: WAT preadipocyte differentiation day 4 EGCG replicate 3

description:
mWE43
sample3_FPKM.txt


title: WAT preadipocyte differentiation day 8 control replicate 3

description:
mW83
sample3_FPKM.txt


title: WAT preadipocyte differentiation day 4 control replicate 3

description:
mW43
sample3_FPKM.txt


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 9.2

city: Oslo

first: Kari

last: Guderud

address: Kirkeveien 166

department: Medical Genetics

country: Norway

institute: University of Oslo

data_processing:
Primary base calling and quality scoring was performed using BSMAP v.2.90 (-p4, -D C-CGG, -v2, -n1, -q28)
getting methylation ratios in methratio.py with samtools
Getting CGs: grep -c "CG" sorted_*.txt
Methratio format to RnBeads format were transformed with a custom R-script
Call methylation differences: RnBeads v.1.10.8  No SNPs, cov treshold=10, min.group.size=5, no sex chromosomes)
Genome_build: hg19
Supplementary_files_format_and_content: .bed file, ready for RnBeads analysis

source_name: CD4+ memory t cell

extract_protocol:
RNA/DNA/Protein Purification Kit (Norgen Biotek Corp)
Diagenode RRBS, In house mRRBS

tag: library prep kit

value: mRRBS

tag: disease state

value: Newly diagnosed Rheumatoid Arthritis

tag: replicate

tag: molecule

value: MSP1 fragmented DNA


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 11.2


title: Newly diagnosed Rheumatoid Arthritis patient CD4nai 8.2

source_name: CD4+ naïve t cell


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 11.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 7.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 10.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 5.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 9.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 8.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 5.2


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 10.2


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 8.2


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 1.2


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 3.1


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 3.2


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 1.1


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_siRNA_LINC01116_KD_rep1

city: Boston

first: Evgeny

last: Deforzh

state: MA

address: 60 Fenwood Rd, Brigham and Women's Hospital Neurology Department, 9th Floor

department: Neurology

institute: Brigham and Women's Hospital

data_processing:
Samples with raw sequencing reads (fastqsanger files) were grouped by antibody and aligned to Drosophila genome (dm6) using Bowtie2 (Langmead and Salzberg, 2012) with default parameters.
Scaling factors were generated as following: the number of uniquely mapped drosophila reads in a sample with the lowest read number    was divided by number of uniquely mapped drosophila reads in every sample. The resulting scaling factors were used to randomly subsample raw fastqsanger files with seqtk_sample tool (GitHub - lh3/seqtk: Toolkit for processing sequences in FASTA/Q formats).
Diluted fastqsanger files were aligned to the human reference genome (GRCh37/hg19) using Bowtie2 with default parameters. PCR duplicates were removed using Picard-tools (version 1.88).
The resulting aligned Bam files were transformed to bigwig format without scaling or normalization using deeptools (version 3.4.3). IGV web application (Thorvaldsdottir et al., 2013) was used for visualization.
The H3K27Ac/H3K27Me3 ChIP-Seq data shown in Figure 2 were not normalized or scaled.
Genome_build: (GRCh37/hg19)
Supplementary_files_format_and_content: bigwig

source_name: fetal human astrocytes

growth_protocol: GBM8 cells were maintained in serum‐free Neurobasal media supplemented with N-2 and B-27 Plus Supplements (Gibco™), 3 mM of Gibco® GlutaMAX™ Supplement, 50 units/ml of penicillin and 50 units/ml of streptomycin (Gibco™), 2 μg/ml of heparin (Sigma‐Aldrich), 20 ng/ml of FGF2 (Sigma-Aldrich), and 20 ng/ml of EGF (Sigma-Aldrich). The cells were passaged by dissociation using Neurocult Stem Cells chemical dissociation kit (Stem Cells Technologies). Human glioma cell line LN229 was cultured in DMEM/10% FBS (Gibco™), and passaged by trypsinization. Human primary  astrocytes were cultured in DMEM-F12/10% FBS media. NPC cultures have been maintained in Neurobasal media supplemented with growth factors as previously described (Teplyuk et al., 2016).

extract_protocol:
Lysates were clarified from sonicated nuclei and histone-DNA complexes were isolated with antibody.
Libraries were prepared according to Illumina's instructions accompanying NEBNext® Ultra™ II DNA Library Prep Kit for Illumina® (E7546S, NEB).
ChIP-Seq with Drosophila spike-in chromatin (Cat. 53083, Active Motif) and Drosophila -specific histone variant, H2Av (Cat. 61686, Active Motif) were added to each sample prior IP  for normalization.

treatment_protocol: Dharmacon Lincode SMARTpool (a mixture of 4 siRNAs) targeting HOXD-AS2 and LINC01116 have been transfected to glioma cells using Lipofectamine RNAiMAX transfection reagent for 48 hours. CRISPRa system (Dharmacon) was used for enhancer LINC01116 activation in fetal human astrocytes for 14 days.

value: fetal human astrocytes

tag: chip antibody

value: Rad21 (ab992, Abcam)

value: treated with CRISPRa system for 14 days, at day 12 - treated  with Pool of 4 siRNAs for 48 hours


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_siRNA_LINC01116_KD_Input


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_siRNA_Control_rep2


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_siRNA_Control_rep1


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_rep2

value: treated with CRISPRa system activating LINC01116 for 14 days


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_rep1


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_Input


title: Astrocytes_Rad21_CRISPRa_Control_rep2

value: treated with CRISPRa system with Control sgRNAs for 14 days


title: Para-2-1

source_name: brain cells

value: Sprague dawley rats

tag: Sex

value: male

tag: tissue

value: anterior cingulate cortex

tag: behavioral phenotype

value: Parasite in a social dilemma setting


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 2.2


title: Astrocytes_Rad21_CRISPRa_Control_Input


title: GBM8_Rad21_siRNA_LINC01116_KD_rep2

source_name: low-passage glioma-initiating stem-like cells (GBM8)

value: treated with Pool of 4 siRNA against LINC01116 for 48 hours


title: GBM8_Rad21_siRNA_LINC01116_KD_rep1

value: low-passage glioma-initiating stem-like cells (GBM8)


title: Newly diagnosed Rheumatoid Arthritis patient CD4mem 2.1


title: Astrocytes_Rad21_CRISPRa_Control_rep1


title: GBM8_Rad21_siRNA_HOXD-AS2_KD_rep1

value: treated with Pool of 4 siRNA against HOXD-AS2 for 48 hours


title: GBM8_Rad21_siRNA_HOXD-AS2_KD_rep2


title: GBM8_Rad21_siRNA_LINC01116_KD_Input


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_siRNA_LINC01116_KD_rep2


title: LN229_CTCF_CrispR_editing_pCTCF_rep2

source_name: tumorigenic adherent glioma cell line (LN229)

value: CTCF (#3418, Cell Signaling)

value: Treated with CrispR Cas9 HOXD-AS2 (promoter) sgRNA


title: GBM8_Rad21_siRNA_Control_rep1

value: treated with Pool of 4 Non-targeting RNA for 48 hours


title: LN229_CTCF_CrispR_editing_pCTCF_Input

value: tumorigenic adherent glioma cell line (LN229)


title: GBM8_Rad21_siRNA_HOXD-AS2_KD_Input


title: GBM8_Rad21_siRNA_Control_Input


title: LN229_CTCF_CrispR_editing_Control_Input

value: Treated with CrispR Cas9 Control sgRNA


title: LN229_CTCF_CrispR_editing_eCTCF_rep1

value: Treated with CrispR Cas9 LINC01116 (enhancer) sgRNA


title: GBM8_Rad21_siRNA_Control_rep2

value: Rad21 (ab992, Abcam)


title: LN229_CTCF_CrispR_editing_eCTCF_Input


title: Astrocytes_CTCF_Untreated_rep2

value: fetal human astrocytes

value: Untreated


title: Astrocytes_CTCF_Untreated_rep1


title: Astrocytes_Rad21_CRISPRa_LINC01116_active_siRNA_Control_Input

value: treated with CRISPRa system for 14 days, at day 12 - treated  with Pool of 4 siRNAs for 48 hours


title: LN229_CTCF_CrispR_editing_pCTCF_rep1


title: Astrocytes_CTCF_Untreated_Input


title: LN229_CTCF_CrispR_editing_eCTCF_rep2


title: Astrocytes_CTCF_CrispRa_LINC01116_active_siRNA_LINC01116_KD_Input


title: Astrocytes_CTCF_CrispRa_LINC01116_active_siRNA_LINC01116_KD_rep1


title: Astrocytes_CTCF_CrispRa_LINC01116_active_Input

value: treated with CRISPRa system activating LINC01116 for 14 days


title: Astrocytes_CTCF_CrispRa_LINC01116_active_rep1


title: LN229_CTCF_CrispR_editing_Control_rep2


title: Astrocytes_CTCF_CrispRa_LINC01116_active_siRNA_Control_rep1


title: GBM8_CTCF_siRNA_LINC01116_KD_rep2


title: Astrocytes_CTCF_CrispRa_Control_Input

value: treated with CRISPRa system with Control sgRNAs for 14 days


title: Astrocytes_CTCF_CrispRa_Control_rep2


title: Astrocytes_CTCF_CrispRa_Control_rep1


title: GBM8_CTCF_siRNA_HOXD-AS2_KD_rep1


title: GBM8_CTCF_siRNA_HOXD-AS2_KD_rep2


title: GBM8_CTCF_siRNA_LINC01116_KD_Input


title: GBM8_CTCF_siRNA_HOXD-AS2_KD_Input


title: GBM8_CTCF_siRNA_Control_rep2


title: GBM8_CTCF_siRNA_Control_rep1


title: GBM8_CTCF_siRNA_Control_Input


title: Astrocytes_CTCF_CrispRa_LINC01116_active_siRNA_LINC01116_KD_rep2


title: LN229_CTCF_CrispR_editing_Control_rep1


title: Astrocytes_H3K27Ac_CRISPRa_LINC01116_active_rep1

value: H3K27Ac (#4353, Cell Signaling)


title: Astrocytes_H3K27Ac_CRISPRa_LINC01116_active_Input


title: Astrocytes_H3K27Me3_rep2

value: H3K27Me3 (#4353, Cell Signaling)

value: untreated


title: Astrocytes_CTCF_CrispRa_LINC01116_active_rep2


title: Astrocytes_CTCF_CrispRa_LINC01116_active_siRNA_Control_Input


title: Astrocytes_CTCF_CrispRa_LINC01116_active_siRNA_Control_rep2


title: Astrocytes_H3K27Ac_CRISPRa_Control_Input


title: Astrocytes_H3K27Ac_CRISPRa_Control_rep1


title: Astrocytes_H3K27Me3_rep1


title: Astrocytes_H3K27Ac_CRISPRa_Control_rep2


title: Astrocytes_H3K27Ac_rep2


title: GBM8_CTCF_siRNA_LINC01116_KD_rep1

value: low-passage glioma-initiating stem-like cells (GBM8)

value: treated with Pool of 4 siRNA against LINC01116 for 48 hours


title: Astrocytes_chromatin_marks_Input


title: Astrocytes_H3K27Ac_rep1


title: GBM8_H3K27Me3_rep1


title: GBM8_H3K27Me3_rep2


title: Astrocytes_H3K27Ac_CRISPRa_LINC01116_active_rep2


title: GBM8_H3K27Ac_rep2


title: GBM8_H3K27Ac_rep1


title: Neuroprogenitors_NlaIII_Untreated_rep2

data_processing:
Library strategy: 4C-Seq
all reads were trimmed to remove first 18 nucleotides (viewpoint primer sequence) before raw data deposition.
trimmed reads were aligned with bowtie2 against hg19 reference genome with defaults settings.
generated bams were processed with r3Cseq (Thongjuea S, bioconductor) with defaults
Genome_build: (GRCh37/hg19)
Supplementary_files_format_and_content: bedGraph with normalised interaction peaks (reads per million)

source_name: human neuroprogenitors

extract_protocol: Extraction was and library construction were performed according to Matelot M et al., 2016

value: human neuroprogenitors


title: Astrocytes_4C_CRISPRa_LINC01116_active_siRNA_LINC01116_KD_rep1


title: Astrocytes_4C_CRISPRa_LINC01116_active_siRNA_Control_rep1


title: Astrocytes_4C_CRISPRa_LINC01116_active_rep2

value: treated with CRISPRa system for 14 days


title: Astrocytes_4C_CRISPRa_LINC01116_active_siRNA_Control_rep2


title: Astrocytes_4C_CRISPRa_LINC01116_active_rep1


title: Astrocytes_4C_CRISPRa_Control_rep2


title: Neuroprogenitors_NlaIII_Untreated_rep1


title: Astrocytes_4C_Untreated_rep1


title: Astrocytes_4C_Untreated_rep2


title: Astrocytes_4C_CRISPRa_LINC01116_active_siRNA_LINC01116_KD_rep2


title: U251_4C_LINC01116_KD_rep2

value: treated with Pool of 4 siRNAs for 48 hours


title: Astrocytes_4C_CRISPRa_Control_rep1


title: U251_4C_LINC01116_KD_rep1

value: tumorigenic adherent glioma cell line (LN229)


title: U251_4C_HOXD-AS2_KD_rep1


title: U251_4C_HOXD-AS2_KD_rep2


title: U251_4C_Untreated_rep1


title: LN229_4C_LINC01116_KD_rep2


title: U251_4C_siRNA_Control_rep2


title: LN229_4C_LINC01116_KD_rep1


title: LN229_4C_HOXD-AS2_KD_rep2


title: LN229_4C_siRNA_Control_rep2


title: GBM8_chromatin_marks_Input


title: LN229_4C_Untreated_rep2


title: LN229_4C_Untreated_rep1


title: GBM4_4C_siRNA_LINC01116_KD_rep2

source_name: low-passage glioma-initiating stem-like cells (GBM4)


title: LN229_4C_siRNA_Control_rep1


title: GBM4_4C_siRNA_LINC01116_KD_rep1

value: low-passage glioma-initiating stem-like cells (GBM4)


title: GBM4_4C_siRNA_HOXD-AS2_KD_rep1


title: GBM4_4C_siRNA_Control_rep1


title: GBM6_4C_siRNA_LINC01116_KD_rep2

source_name: low-passage glioma-initiating stem-like cells (GBM6)


title: GBM4_4C_Untreated_rep1


title: GBM4_4C_Untreated_rep2


title: GBM6_4C_siRNA_HOXD-AS2_KD_rep2

value: low-passage glioma-initiating stem-like cells (GBM6)


title: U251_4C_siRNA_Control_rep1


title: GBM6_4C_siRNA_LINC01116_KD_rep1


title: GBM6_4C_siRNA_Control_rep1


title: U251_4C_Untreated_rep2


title: GBM6_4C_siRNA_Control_rep2


title: GBM6_4C_siRNA_HOXD-AS2_KD_rep1


title: GBM6_4C_Untreated_rep2


title: GBM8_4C_siRNA_Control_rep2


title: GBM8_4C_Untreated_rep1


title: LN229_4C_HOXD-AS2_KD_rep1


title: GBM6_4C_Untreated_rep1


title: GBM8_4C_siRNA_LINC01116_KD_rep2


title: GBM4_4C_siRNA_Control_rep2


title: GBM8_4C_siRNA_LINC01116_KD_rep1


title: GBM8_4C_siRNA_HOXD-AS2_KD_rep1


title: GBM8_4C_siRNA_Control_rep1


title: GBM8_4C_Untreated_rep2


title: dendritic_cells_24h_B_input (ChIP-seq)

city: Badalona, Barcelona

first: Esteban

last: Ballestar

state: N/A = Not Applicable

address: Ctra de Can Ruti, Camí de les Escoles s/n

country: Spain

institute: Josep Carreras Research Institute (IJC)

description: Input ChIP DNA from Dendritic cells differentiated from monocytes with GM-CSF/IL4 for 24h

data_processing:
Read trimming using Cutadapt 1.18
Alignment to the GRCh38 genome using the BWA-MEM algorithm (bwa 0.7.17)
MAPQ lower than 30 were filtered using samtools (1.9)
Peak calling was performed using MACS2 (2.2.7.1) with the options (--nomodel –extsize 200)
Biological duplicates were aggregated using MSPC (4.0.1)
Bigwigs were generated using Deeptools () with the bins per million mapped reads (BPM) method and  ‘--binSize 20 --extendReads 150 --smoothLength 60 --centerReads’  options.
Genome_build: GRCh38
Supplementary_files_format_and_content: bigwig files generated with deeptools (bins per million mapped reads)
Supplementary_files_format_and_content: narrowPeak files generated with MACS2

source_name: Dendritic cells differentiated from monocytes 24 hours (replicate B)

growth_protocol: Monocytes were isolated from buffy coats by CD14 positive selection (MACS) and cultured 4h or 24h in Roswell Park Memorial Institute (RPMI) Medium 1640 + GlutaMAX™ containing 10% fetal bovine serum, 100 units/mL penicillin, 100 mg/mL streptomycin

extract_protocol:
Cells were directly fixed in the cell plate for 12min with 1% formaldehyde methanol-free and chromatin was prepared for sonication following the Covaris truChIP Shearing kit instructions. Chromatin in Shearing D3 Buffer was sonicated using the Covaris M220 sonicator. Chromatin size distribution was checked using an agarose gel electrophoresis (250-150bp)
ChIP-seq libraries were prepared for sequencing using the Illumina TruSeq ChIP Library Preparation Kit

treatment_protocol: At the beginning of the differentiation process, 10ng/mL Granulocyte Macrophage Colony-Stimulating Factor and 10ng/mL Interleukin 4 were added to the cell medium. Moreover, cells were treated with or without Dexamethasone (100nM).

value: DC

tag: individual

value: donor B

value: 24 hours differentiation

value: none (Input)


title: tolerogenic_dendritic_cells_4h_B_input (ChIP-seq)

description: Input ChIP DNA from Tolerogenic Dendritic cells differentiated from monocytes with Dex + GM-CSF/IL4 for 4h

source_name: Tolerogenic dendritic cells differentiated from monocytes 4 hours (replicate B)

value: tolDC

value: 4 hours differentiation


title: GBM4_4C_siRNA_HOXD-AS2_KD_rep2

tag: treatment


title: dendritic_cells_24h_A_input (ChIP-seq)

source_name: Dendritic cells differentiated from monocytes 24 hours (replicate A)

value: donor A


title: tolerogenic_dendritic_cells_24h_B_MAFB (ChIP-seq)

description: MAFB ChIP DNA from Tolerogenic Dendritic cells differentiated from monocytes with Dex + GM-CSF/IL4 for 24h

source_name: Tolerogenic dendritic cells differentiated from monocytes 24 hours (replicate B)


title: dendritic_cells_4h_B_input (ChIP-seq)

description: Input ChIP DNA from Dendritic cells differentiated from monocytes with GM-CSF/IL4 for 4h

source_name: Dendritic cells differentiated from monocytes 4 hours (replicate B)


title: tolerogenic_dendritic_cells_24h_A_MAFB (ChIP-seq)

source_name: Tolerogenic dendritic cells differentiated from monocytes 24 hours (replicate A)


title: dendritic_cells_24h_B_MAFB (ChIP-seq)

description: MAFB ChIP DNA from Dendritic cells differentiated from monocytes with GM-CSF/IL4 for 24h


title: tolerogenic_dendritic_cells_24h_A_input (ChIP-seq)

description: Input ChIP DNA from Tolerogenic Dendritic cells differentiated from monocytes with Dex + GM-CSF/IL4 for 24h


title: dendritic_cells_24h_B_glucocorticoid_receptor (ChIP-seq)

description: GR ChIP DNA from Dendritic cells differentiated from monocytes with GM-CSF/IL4 for 24h


title: dendritic_cells_24h_A_MAFB (ChIP-seq)


title: dendritic_cells_4h_A_input (ChIP-seq)

source_name: Dendritic cells differentiated from monocytes 4 hours (replicate A)


title: GBM8_4C_siRNA_HOXD-AS2_KD_rep2


title: tolerogenic_dendritic_cells_4h_B_MAFB (ChIP-seq)

description: MAFB ChIP DNA from Tolerogenic Dendritic cells differentiated from monocytes with Dex + GM-CSF/IL4 for 4h


title: tolerogenic_dendritic_cells_4h_A_glucocorticoid_receptor (ChIP-seq)

description: GR ChIP DNA from Tolerogenic Dendritic cells differentiated from monocytes with Dex + GM-CSF/IL4 for 4h

source_name: Tolerogenic dendritic cells differentiated from monocytes 4 hours (replicate A)


title: tolerogenic_dendritic_cells_4h_A_MAFB (ChIP-seq)


title: tolerogenic_dendritic_cells_4h_A_input (ChIP-seq)


title: dendritic_cells_4h_A_MAFB (ChIP-seq)

description: MAFB ChIP DNA from Dendritic cells differentiated from monocytes with GM-CSF/IL4 for 4h


title: dendritic_cells_4h_B_glucocorticoid_receptor (ChIP-seq)

description: GR ChIP DNA from Dendritic cells differentiated from monocytes with GM-CSF/IL4 for 4h


title: tolerogenic_dendritic_cells_24h_A_glucocorticoid_receptor (ChIP-seq)

description: GR ChIP DNA from Tolerogenic Dendritic cells differentiated from monocytes with Dex + GM-CSF/IL4 for 24h


title: dendritic_cells_4h_A_glucocorticoid_receptor (ChIP-seq)


title: dendritic_cells_24h_A_glucocorticoid_receptor (ChIP-seq)


title: P07_C20R40 Non-diabetic human islet single cell

city: Tucson

first: Hongxu

last: Ding

state: AZ

address: The University of Arizona

institute: University of Arizona

description:
P07_C20R40
counts.csv

data_processing:
After demultiplexing, the resulting raw reads were aligned to hg19 reference genome by Bowtie2-2.2.6.
Aligned reads were sorted and indexed by samtools-1.2
Counts matrix was measured with R package GenomicFeatures (1.24.5),  GenomicAlignments (1.8.4) and TxDb.Hsapiens.UCSC.hg19.knownGene (3.2.2)
Samples annotated as living singlets were kept in the counts matrix
Genome_build: hg19, UCSC annotation from R package TxDb.Hsapiens.UCSC.hg19.knownGene (3.2.2)
Supplementary_files_format_and_content: comma separated file including counts matrix

source_name: Isolated single cells from type-2 diabetes human islets

extract_protocol:
Automated Fludigm C1 800 chip standard protocol
Nextera XT Library kit standard protocol

value: inlet cells


title: P07_C20R38 Non-diabetic human islet single cell

description:
P07_C20R38
counts.csv


title: P07_C20R34 Non-diabetic human islet single cell

description:
P07_C20R34
counts.csv


title: P07_C20R36 Non-diabetic human islet single cell

description:
P07_C20R36
counts.csv


title: tolerogenic_dendritic_cells_4h_B_glucocorticoid_receptor (ChIP-seq)


title: dendritic_cells_4h_B_MAFB (ChIP-seq)


title: tolerogenic_dendritic_cells_24h_B_glucocorticoid_receptor (ChIP-seq)


title: P07_C20R33 Non-diabetic human islet single cell

description:
P07_C20R33
counts.csv


title: P07_C20R37 Non-diabetic human islet single cell

description:
P07_C20R37
counts.csv


title: P07_C20R39 Non-diabetic human islet single cell

description:
P07_C20R39
counts.csv


title: P07_C20R35 Non-diabetic human islet single cell

description:
P07_C20R35
counts.csv


title: P07_C20R27 Non-diabetic human islet single cell

description:
P07_C20R27
counts.csv


title: P07_C20R29 Non-diabetic human islet single cell

description:
P07_C20R29
counts.csv


title: P07_C20R24 Non-diabetic human islet single cell

description:
P07_C20R24
counts.csv


title: P07_C20R30 Non-diabetic human islet single cell

description:
P07_C20R30
counts.csv


title: P07_C20R32 Non-diabetic human islet single cell

description:
P07_C20R32
counts.csv


title: P07_C20R28 Non-diabetic human islet single cell

description:
P07_C20R28
counts.csv


title: P07_C20R23 Non-diabetic human islet single cell

description:
P07_C20R23
counts.csv


title: P07_C20R22 Non-diabetic human islet single cell

description:
P07_C20R22
counts.csv


title: P07_C20R20 Non-diabetic human islet single cell

description:
P07_C20R20
counts.csv


title: P07_C20R19 Non-diabetic human islet single cell

description:
P07_C20R19
counts.csv


title: P07_C20R16 Non-diabetic human islet single cell

description:
P07_C20R16
counts.csv


title: P07_C20R21 Non-diabetic human islet single cell

description:
P07_C20R21
counts.csv


title: P07_C20R15 Non-diabetic human islet single cell

description:
P07_C20R15
counts.csv


title: P07_C20R18 Non-diabetic human islet single cell

description:
P07_C20R18
counts.csv


title: P07_C20R17 Non-diabetic human islet single cell

description:
P07_C20R17
counts.csv


title: P07_C20R14 Non-diabetic human islet single cell

description:
P07_C20R14
counts.csv


title: P07_C20R13 Non-diabetic human islet single cell

description:
P07_C20R13
counts.csv


title: P07_C20R12 Non-diabetic human islet single cell

description:
P07_C20R12
counts.csv


title: P07_C20R31 Non-diabetic human islet single cell

description:
P07_C20R31
counts.csv


title: P07_C20R10 Non-diabetic human islet single cell

description:
P07_C20R10
counts.csv


title: P07_C20R11 Non-diabetic human islet single cell

description:
P07_C20R11
counts.csv


title: P07_C20R25 Non-diabetic human islet single cell

description:
P07_C20R25
counts.csv


title: P07_C20R09 Non-diabetic human islet single cell

description:
P07_C20R09
counts.csv


title: P07_C20R08 Non-diabetic human islet single cell

description:
P07_C20R08
counts.csv


title: P07_C20R07 Non-diabetic human islet single cell

description:
P07_C20R07
counts.csv


title: P07_C20R26 Non-diabetic human islet single cell

description:
P07_C20R26
counts.csv


title: P07_C20R05 Non-diabetic human islet single cell

description:
P07_C20R05
counts.csv


title: P07_C20R06 Non-diabetic human islet single cell

description:
P07_C20R06
counts.csv


title: P07_C20R04 Non-diabetic human islet single cell

description:
P07_C20R04
counts.csv


title: P07_C20R02 Non-diabetic human islet single cell

description:
P07_C20R02
counts.csv


title: P07_C20R03 Non-diabetic human islet single cell

description:
P07_C20R03
counts.csv


title: P07_C20R01 Non-diabetic human islet single cell

description:
P07_C20R01
counts.csv


title: P07_C19R39 Non-diabetic human islet single cell

description:
P07_C19R39
counts.csv


title: P07_C19R37 Non-diabetic human islet single cell

description:
P07_C19R37
counts.csv


title: P07_C19R36 Non-diabetic human islet single cell

description:
P07_C19R36
counts.csv


title: P07_C19R35 Non-diabetic human islet single cell

description:
P07_C19R35
counts.csv


title: P07_C19R34 Non-diabetic human islet single cell

description:
P07_C19R34
counts.csv


title: P07_C19R33 Non-diabetic human islet single cell

description:
P07_C19R33
counts.csv


title: P07_C19R38 Non-diabetic human islet single cell

description:
P07_C19R38
counts.csv


title: P07_C19R32 Non-diabetic human islet single cell

description:
P07_C19R32
counts.csv


title: P07_C19R30 Non-diabetic human islet single cell

description:
P07_C19R30
counts.csv


title: P07_C19R31 Non-diabetic human islet single cell

description:
P07_C19R31
counts.csv


title: P07_C19R28 Non-diabetic human islet single cell

description:
P07_C19R28
counts.csv


title: P07_C19R27 Non-diabetic human islet single cell

description:
P07_C19R27
counts.csv


title: P07_C19R26 Non-diabetic human islet single cell

description:
P07_C19R26
counts.csv


title: P07_C19R29 Non-diabetic human islet single cell

description:
P07_C19R29
counts.csv


title: P07_C19R25 Non-diabetic human islet single cell

description:
P07_C19R25
counts.csv


title: P07_C19R23 Non-diabetic human islet single cell

description:
P07_C19R23
counts.csv


title: P07_C19R21 Non-diabetic human islet single cell

description:
P07_C19R21
counts.csv


title: P07_C19R16 Non-diabetic human islet single cell

description:
P07_C19R16
counts.csv


title: P07_C19R20 Non-diabetic human islet single cell

description:
P07_C19R20
counts.csv


title: P07_C19R22 Non-diabetic human islet single cell

description:
P07_C19R22
counts.csv


title: P07_C19R14 Non-diabetic human islet single cell

description:
P07_C19R14
counts.csv


title: P07_C19R15 Non-diabetic human islet single cell

description:
P07_C19R15
counts.csv


title: P07_C19R19 Non-diabetic human islet single cell

description:
P07_C19R19
counts.csv


title: P07_C19R13 Non-diabetic human islet single cell

description:
P07_C19R13
counts.csv


title: P07_C19R40 Non-diabetic human islet single cell

description:
P07_C19R40
counts.csv


title: P07_C19R17 Non-diabetic human islet single cell

description:
P07_C19R17
counts.csv


title: P07_C19R12 Non-diabetic human islet single cell

description:
P07_C19R12
counts.csv


title: P07_C19R24 Non-diabetic human islet single cell

description:
P07_C19R24
counts.csv


title: P07_C19R18 Non-diabetic human islet single cell

description:
P07_C19R18
counts.csv


title: P07_C19R08 Non-diabetic human islet single cell

description:
P07_C19R08
counts.csv


title: P07_C19R05 Non-diabetic human islet single cell

description:
P07_C19R05
counts.csv


title: P07_C19R06 Non-diabetic human islet single cell

description:
P07_C19R06
counts.csv


title: P07_C19R03 Non-diabetic human islet single cell

description:
P07_C19R03
counts.csv


title: P07_C19R09 Non-diabetic human islet single cell

description:
P07_C19R09
counts.csv


title: P07_C19R02 Non-diabetic human islet single cell

description:
P07_C19R02
counts.csv


title: P07_C19R07 Non-diabetic human islet single cell

description:
P07_C19R07
counts.csv


title: P07_C18R38 Non-diabetic human islet single cell

description:
P07_C18R38
counts.csv


title: P07_C18R39 Non-diabetic human islet single cell

description:
P07_C18R39
counts.csv


title: P07_C19R01 Non-diabetic human islet single cell

description:
P07_C19R01
counts.csv


title: P07_C18R37 Non-diabetic human islet single cell

description:
P07_C18R37
counts.csv


title: P07_C18R40 Non-diabetic human islet single cell

description:
P07_C18R40
counts.csv


title: P07_C18R36 Non-diabetic human islet single cell

description:
P07_C18R36
counts.csv


title: P07_C18R35 Non-diabetic human islet single cell

description:
P07_C18R35
counts.csv


title: P07_C18R34 Non-diabetic human islet single cell

description:
P07_C18R34
counts.csv


title: P07_C18R31 Non-diabetic human islet single cell

description:
P07_C18R31
counts.csv


title: P07_C18R32 Non-diabetic human islet single cell

description:
P07_C18R32
counts.csv


title: P07_C18R33 Non-diabetic human islet single cell

description:
P07_C18R33
counts.csv


title: P07_C18R30 Non-diabetic human islet single cell

description:
P07_C18R30
counts.csv


title: P07_C19R11 Non-diabetic human islet single cell

description:
P07_C19R11
counts.csv


title: P07_C19R10 Non-diabetic human islet single cell

description:
P07_C19R10
counts.csv


title: P07_C18R28 Non-diabetic human islet single cell

description:
P07_C18R28
counts.csv


title: P07_C18R27 Non-diabetic human islet single cell

description:
P07_C18R27
counts.csv


title: P07_C19R04 Non-diabetic human islet single cell

description:
P07_C19R04
counts.csv


title: P07_C18R24 Non-diabetic human islet single cell

description:
P07_C18R24
counts.csv


title: P07_C18R29 Non-diabetic human islet single cell

description:
P07_C18R29
counts.csv


title: P07_C18R25 Non-diabetic human islet single cell

description:
P07_C18R25
counts.csv


title: P07_C18R26 Non-diabetic human islet single cell

description:
P07_C18R26
counts.csv


title: P07_C18R20 Non-diabetic human islet single cell

description:
P07_C18R20
counts.csv


title: P07_C18R19 Non-diabetic human islet single cell

description:
P07_C18R19
counts.csv


title: P07_C18R16 Non-diabetic human islet single cell

description:
P07_C18R16
counts.csv


title: P07_C18R17 Non-diabetic human islet single cell

description:
P07_C18R17
counts.csv


title: P07_C18R22 Non-diabetic human islet single cell

description:
P07_C18R22
counts.csv


title: P07_C18R23 Non-diabetic human islet single cell

description:
P07_C18R23
counts.csv


title: P07_C18R18 Non-diabetic human islet single cell

description:
P07_C18R18
counts.csv


title: P07_C18R15 Non-diabetic human islet single cell

description:
P07_C18R15
counts.csv


title: P07_C18R12 Non-diabetic human islet single cell

description:
P07_C18R12
counts.csv


title: P07_C18R21 Non-diabetic human islet single cell

description:
P07_C18R21
counts.csv


title: P07_C18R14 Non-diabetic human islet single cell

description:
P07_C18R14
counts.csv


title: P07_C18R13 Non-diabetic human islet single cell

description:
P07_C18R13
counts.csv


title: P07_C18R10 Non-diabetic human islet single cell

description:
P07_C18R10
counts.csv


title: P07_C18R11 Non-diabetic human islet single cell

description:
P07_C18R11
counts.csv


title: P07_C18R09 Non-diabetic human islet single cell

description:
P07_C18R09
counts.csv


title: P07_C17R39 Non-diabetic human islet single cell

description:
P07_C17R39
counts.csv


title: P07_C17R35 Non-diabetic human islet single cell

description:
P07_C17R35
counts.csv


title: P07_C18R06 Non-diabetic human islet single cell

description:
P07_C18R06
counts.csv


title: P07_C17R34 Non-diabetic human islet single cell

description:
P07_C17R34
counts.csv


title: P07_C18R03 Non-diabetic human islet single cell

description:
P07_C18R03
counts.csv


title: P07_C18R07 Non-diabetic human islet single cell

description:
P07_C18R07
counts.csv


title: P07_C17R40 Non-diabetic human islet single cell

description:
P07_C17R40
counts.csv


title: P07_C18R04 Non-diabetic human islet single cell

description:
P07_C18R04
counts.csv


title: P07_C18R02 Non-diabetic human islet single cell

description:
P07_C18R02
counts.csv


title: P07_C18R05 Non-diabetic human islet single cell

description:
P07_C18R05
counts.csv


title: P07_C18R01 Non-diabetic human islet single cell

description:
P07_C18R01
counts.csv


title: P07_C17R38 Non-diabetic human islet single cell

description:
P07_C17R38
counts.csv


title: P07_C17R33 Non-diabetic human islet single cell

description:
P07_C17R33
counts.csv


title: P07_C17R36 Non-diabetic human islet single cell

description:
P07_C17R36
counts.csv


title: P07_C17R37 Non-diabetic human islet single cell

description:
P07_C17R37
counts.csv


title: P07_C17R32 Non-diabetic human islet single cell

description:
P07_C17R32
counts.csv


title: P07_C17R29 Non-diabetic human islet single cell

description:
P07_C17R29
counts.csv


title: P07_C17R31 Non-diabetic human islet single cell

description:
P07_C17R31
counts.csv


title: P07_C17R27 Non-diabetic human islet single cell

description:
P07_C17R27
counts.csv


title: P07_C17R30 Non-diabetic human islet single cell

description:
P07_C17R30
counts.csv


title: P07_C17R28 Non-diabetic human islet single cell

description:
P07_C17R28
counts.csv


title: P07_C17R24 Non-diabetic human islet single cell

description:
P07_C17R24
counts.csv


title: P07_C17R23 Non-diabetic human islet single cell

description:
P07_C17R23
counts.csv


title: P07_C17R26 Non-diabetic human islet single cell

description:
P07_C17R26
counts.csv


title: P07_C17R25 Non-diabetic human islet single cell

description:
P07_C17R25
counts.csv


title: P07_C17R21 Non-diabetic human islet single cell

description:
P07_C17R21
counts.csv


title: P07_C17R22 Non-diabetic human islet single cell

description:
P07_C17R22
counts.csv


title: P07_C18R08 Non-diabetic human islet single cell

description:
P07_C18R08
counts.csv


title: P07_C17R20 Non-diabetic human islet single cell

description:
P07_C17R20
counts.csv


title: P07_C17R15 Non-diabetic human islet single cell

description:
P07_C17R15
counts.csv


title: P07_C17R17 Non-diabetic human islet single cell

description:
P07_C17R17
counts.csv


title: P07_C17R13 Non-diabetic human islet single cell

description:
P07_C17R13
counts.csv


title: P07_C17R16 Non-diabetic human islet single cell

description:
P07_C17R16
counts.csv


title: P07_C17R12 Non-diabetic human islet single cell

description:
P07_C17R12
counts.csv


title: P07_C17R11 Non-diabetic human islet single cell

description:
P07_C17R11
counts.csv


title: P07_C17R10 Non-diabetic human islet single cell

description:
P07_C17R10
counts.csv


title: P07_C17R14 Non-diabetic human islet single cell

description:
P07_C17R14
counts.csv


title: P07_C17R07 Non-diabetic human islet single cell

description:
P07_C17R07
counts.csv


title: P07_C17R05 Non-diabetic human islet single cell

description:
P07_C17R05
counts.csv


title: P07_C17R06 Non-diabetic human islet single cell

description:
P07_C17R06
counts.csv


title: P07_C17R08 Non-diabetic human islet single cell

description:
P07_C17R08
counts.csv


title: P07_C16R39 Non-diabetic human islet single cell

description:
P07_C16R39
counts.csv


title: P07_C17R09 Non-diabetic human islet single cell

description:
P07_C17R09
counts.csv


title: P07_C17R18 Non-diabetic human islet single cell

description:
P07_C17R18
counts.csv


title: P07_C16R38 Non-diabetic human islet single cell

description:
P07_C16R38
counts.csv


title: P07_C17R02 Non-diabetic human islet single cell

description:
P07_C17R02
counts.csv


title: P07_C16R34 Non-diabetic human islet single cell

description:
P07_C16R34
counts.csv


title: P07_C16R37 Non-diabetic human islet single cell

description:
P07_C16R37
counts.csv


title: P07_C17R01 Non-diabetic human islet single cell

description:
P07_C17R01
counts.csv


title: P07_C17R04 Non-diabetic human islet single cell

description:
P07_C17R04
counts.csv


title: P07_C17R03 Non-diabetic human islet single cell

description:
P07_C17R03
counts.csv


title: P07_C16R36 Non-diabetic human islet single cell

description:
P07_C16R36
counts.csv


title: P07_C16R40 Non-diabetic human islet single cell

description:
P07_C16R40
counts.csv


title: P07_C16R35 Non-diabetic human islet single cell

description:
P07_C16R35
counts.csv


title: P07_C17R19 Non-diabetic human islet single cell

description:
P07_C17R19
counts.csv


title: P07_C16R33 Non-diabetic human islet single cell

description:
P07_C16R33
counts.csv


title: P07_C16R32 Non-diabetic human islet single cell

description:
P07_C16R32
counts.csv


title: P07_C16R31 Non-diabetic human islet single cell

description:
P07_C16R31
counts.csv