title: Somatosensory Cortex, Female, P0, KO, replicate 1

description: Library name: S1.1621.P0.F.KO


title: Somatosensory Cortex, Female, P0, WT, replicate 1

status: Public on Dec 01 2025

type: SRA

city: New York

first: Jacquelyn

last: Salzbank

state: NY

department: Pediatrics

country: USA

institute: Columbia University Irving Medical Center

description: Library name: S1.1614.P0.F.WT

library_source: transcriptomic

data_processing:
rRNA abundance was measured by mapping with Bowtie2.
Quality control was performed using Picard (v1.83) and RSeQC (v2.6.1).
Assembly: The reads were aligned with STAR (version 2.5.2a), and genes annotated in Gencode vM16 and quantified with featureCounts (v1.4.3-p1).
Supplementary files format and content: .csv file called "Processed_Counts_Matrix" includes raw counts for each sample

molecule: total RNA

organism: Mus musculus

source_name: Somatosensory Cortex

extract_protocol:
From each mouse the somatosensory cortex, the cerebellum and the hippocampus were collected. Tissues were homogenized in TRIzol Reagent (Thermo Fisher Scientific); total RNA was extracted with the RNeasy Mini Kit. (Qiagen, no. 74104). A total of 500 ng of RNA was used for sequencing.
Libraries were prepared using the Illumina TruSeq Stranded mRNA Library prep (Illumina, catalog number 20020595) in accordance with manufacturer recommendations, and using IDT for Illumina TruSeq DNA UD Indices (Illumina, catalog number 20022370) for adapters.

tag: tissue

value: Somatosensory Cortex

tag: genotype

value: WT

tag: Sex

value: Female

tag: age


title: Somatosensory Cortex, Male, P30, WT, replicate 3

description: Library name: S1.CM846.P30.M.WT

value: Male


title: Somatosensory Cortex, Male, P0, WT, replicate 1

description: Library name: S1.1620.P0.M.WT


title: DSP-1001660019973-E-A12

city: Dallas

first: Chengsong

last: Zhu

state: TX

address: 5323 Harry Hines Blvd

department: Immunology

institute: UT Southwestern Medical Center

data_processing:
/opt/illumina/Isas/1.37.0/bcl2fastq2/bin/bcl2fastq  --ignore-missing-bcls --ignore-missing-filter --ignore-missing-positions --ignore-missing-controls --auto-set-to-zero-barcode-mismatches --find-adapters-with-sliding-window --adapter-stringency 0.9 --mask-short-adapter-reads 35 --minimum-trimmed-read-length 35 -R  /data/scratch/workspace/RunFolder --sample-sheet "/data/scratch/workspace/RunFolder/SampleSheet.csv" -o "/data/scratch/workspace/RunFolder/Analysis/Temp_01.01-GenerateFASTQ.FastqGeneration"
raw sequencing data  were processed using Illumina basespace pipeline to generate fastq files
Run Nanostring GeoMx NGS pipeline ( version 3.1.1.6)  to generate DCC files
Upload DCC files to GeoMx DSP platform and create the study
Perfom standand QC using default parameters setting recommended by the manufacture
Q3 normalization was carried out to generate Q3 normalization datasets  which are for the all downstream analysis
Assembly: GRCh38
Supplementary files format and content: raw_dcc.tar:  raw read counts in DCC of tar
Supplementary files format and content: processed_data.txt.gz:  normalization gene expression matrix by Q3 normalization recommended by manufacture which are used for all the downstream analysis in txt format
Library strategy: Spatial transcriptomic

organism: Homo sapiens

source_name: 42444 is an early onset cancer

extract_protocol:
FFPE tissues were parafilm embedded, 5 µM sections were cut with cryostat
Spatial transcritpome sequencing libraries were prepared with Nanostring GeoMx DSP NGS library preparation kit according to manufacturer's instruction

value: 42444 is an early onset cancer

tag: rnapanel

tag: treatment

tag: cancer

value: Yes

tag: scan name

value: Slide1_S21-26292 A7_42444-4_Vimentin 1:150  and CD45-AF647(5 ug/mL), Pan CK and SYTO13

tag: roi

tag: segment


title: DSP-1001660019973-E-A10


title: Somatosensory Cortex, Female, P0, WT, replicate 2

description: Library name: S1.1653.P0.F.WT


title: Somatosensory Cortex, Male, P15, WT, replicate 4

description: Library name: S1.1547.P15.M.WT


title: DSP-1001660019973-E-A07

value: Vimentin


title: DSP-1001660019973-E-A08


title: Somatosensory Cortex, Female, P15, KO, replicate 2

description: Library name: S1.1546.P15.F.KO

value: KO


title: Somatosensory Cortex, Female, P15, WT, replicate 3

description: Library name: S1.1544.P15.F.WT


title: Somatosensory Cortex, Male, P15, WT, replicate 3

description: Library name: S1.1542.P15.M.WT


title: DSP-1001660019973-E-A06


title: DSP-1001660019973-E-B09

source_name: 42444-NL is the normal counterpart of 42444 cancer

value: No


title: Somatosensory Cortex, Female, P30, KO, replicate 4

description: Library name: S1.1467.P30.F.KO


title: DSP-1001660019973-E-A05


title: Somatosensory Cortex, Male, P15, KO, replicate 4

description: Library name: S1.1540.P15.M.KO


title: DSP-1001660019973-E-A09


title: Somatosensory Cortex, Female, P7, KO, replicate 5

description: Library name: S1.1381.P7.M.KO


title: DSP-1001660019973-E-A04


title: Somatosensory Cortex, Female, P30, WT, replicate 3

description: Library name: S1.1465.P30.F.WT


title: Somatosensory Cortex, Male, P7, KO, replicate 3

description: Library name: S1.1414.P7.M.KO


title: Somatosensory Cortex, Female, P7, WT, replicate 4

description: Library name: S1.1410.P7.F.WT


title: Somatosensory Cortex, Female, P30, WT, replicate 4

description: Library name: S1.1466.P30.F.WT


title: Somatosensory Cortex, Male, P7, WT, replicate 4

description: Library name: S1.1380.P7.M.WT


title: DSP-1001660019973-E-A03


title: hiPSC-ExN full deletion bio rep 2

city: San Francisco

first: Katherine

middle: S

last: Pollard

state: CA

address: 1650 Owens St

institute: Gladstone Institutes

library_source: genomic

data_processing:
Reads were mapped to GRCh38 using bwa v0.7.18.
Valid HiC alignments were filtered using pairtools v1.0.3 and returned to a pairs file.
Biological replicates were merged using https://github.com/4dn-dcic/docker-4dn-hic/blob/master/scripts/run-merge-pairs.sh.
The pairs files were converted to cool files using cooler v0.9.3.
Assembly: hg38
Supplementary files format and content: WT.mcool is an mcool file for both WT cell line replicates.
Supplementary files format and content: ctcf_deletion.mcool is an mcool file for both CTCF deletion cell line replicates.
Supplementary files format and content: full_deletion.mcool is an mcool file for both full deletion cell line replicates.

molecule: genomic DNA

source_name: WTC11 hIPSC-ExN

growth_protocol: The WTC11 i3N iPSC line with doxycycline-inducible Ngn2 integrated at the AAVS1 safe harbor locus was used. The WTC11 i3N iPSCs were cultured on Matrigel-coated (Corning, 354277) plates and maintained in mTeSR Plus media (STEMCELL Technologies, 100-0276), and passaged with Accutase (STEMCELL Technologies, 07920) and 10-μM ROCK inhibitor Y-27632 (STEMCELL Technologies, 72302). The cells were grown with 5% CO2 at 37℃ and verified mycoplasma-free using the MycoAlert Mycoplasma Detection Kit (Lonza, LT07-218).

extract_protocol:
HiC libraries were generated using the Arima-HiC+ kit (P/N A101020) according to the manufacturer’s protocol. Briefly, differentiated ExNs were fixed in culture plates with 2% PFA (Fisher Scientific F79-500) at room temperature for 10 min. About 0.5 million cells were used as input for each HiC library. The crosslinked chromatin DNA was treated with restriction digestion, biotinylation, proximal ligation. The proximally ligated chromatin was sheared with a Covaris S220 sonicator to fragments between 300 and 1,000 bp. The shared chromatin was then indexed with the Accel-NGS 2S Plus DNA Library Kit (Swift Biosciences, 21024) and amplified with KAPA Library Amplification Kit (Roche, KK2620).
The final libraries were purified with AMPure XP beads (Beckman Coulter, A63881) and sequenced on NovaSeq with paired-end 100bp sequencing.

treatment_protocol:
The designed sgRNAs were in vitro transcribed using the Precision gRNA Synthesis Kit (Invitrogen, A29377), and Cas9-NLS protein was ordered from QB3 MacroLab at the University of California, Berkeley. We assembled the Cas9/sgRNA complex by incubating the in vitro transcribed sgRNAs and Cas9-NLS protein at 20-25℃ for 15 min and delivered the complex into WTC11 i3N iPSCs using nucleofection (Lonza, VPH-5012). After nucleofection, the cells were seeded into Matrigel-coated (Corning, 354277) wells for recovery. 3-4 days later, we sorted live cells into 96-well plates with one cell per well using fluorescence-activated cell sorting (FACS) to generate clonal cell lines. About two weeks later, the viable clones were expanded.
We differentiated the iPSCs into excitatory neurons by using a two-step differentiation protocol. First, we cultured iPSCs on Matrigel-coated plates with pre-differentiation media with doxycycline (2 µg/mL; Sigma-Aldrich, D9891) for three days and changed the media daily. Three days later, the pre-differentiated cells were dissociated with Accutase (STEMCELL Technologies, 07920) and subplated on Poly-L-Ornithine-coated (15 µg/mL; Sigma-Aldrich, P3655) plates with maturation media with doxycycline. Then, the maturation media was changed seven days later by removing half of the media from each well and adding the same amount of fresh media without doxycycline.

tag: cell line

value: WTC11 hIPSC-ExN

value: full deletion

value: excitatory neuron differentiation


title: hiPSC-ExN full deletion bio rep 1


title: DSP-1001660019973-E-A02


title: Somatosensory Cortex, Female, P7, KO, replicate 4

description: Library name: S1.1344.P7.F.KO


title: hiPSC-ExN CTCF deletion bio rep 1

value: CTCF deletion


title: hiPSC-ExN CTCF deletion bio rep 2


title: hiPSC-ExN WT bio rep 2


title: Somatosensory Cortex, Male, P7, WT, replicate 3

description: Library name: S1.1370.P7.M.WT


title: Somatosensory Cortex, Female, P7, WT, replicate 3

description: Library name: S1.1336.P7.F.WT


title: EHE 001 Late (2)

city: Iowa City

first: Michael

last: Chimenti

state: IA

address: 431 Newton Road

department: Iowa Institute of Human Genetics

institute: University of Iowa

description: 10X Genomics

library_source: transcriptomic single cell

data_processing:
Barcoded samples were pooled and sequenced using an Illumina NovaSeq 6000 in the Iowa Institute of Human Genetics (IIHG) Genomics Core Facility. Paired-end reads were demultiplexed and converted from the native Illumina BCL format to FASTQ format using a custom python workflow wrapper to Illumina’s ‘bcl2fastq’ conversion utility.  FASTQ data were processed with 10X CellRanger (7.1.0) with reference "GRCh38-2020-A" using Single Cell Chemistry 3' V3.  Include introns was set to "TRUE."
Samples were loaded into R and Seurat (v5) library was used to perform filtering, normalization, and data integration using the "RPCA" method.
Assembly: GRCh38
Supplementary files format and content: filtered feature barcode (hdf5); loupe brower (cloupe)
Supplementary files format and content: loupe browser file contains integrated data object after seurat processing

molecule: polyA RNA

source_name: Primary Cell Culture

growth_protocol: Cells were cultured on 10 cm tissue culture dishes gown in Lonza EGM-2 Media supplemented to 15% FBS, and 1% Pen/Strep.

extract_protocol:
10X GEM
10X 3' chemistry

value: Primary Cell Culture

value: EHE 001

tag: cell type


title: EHE 001 Late (1)

description: 10X Genomics


title: Somatosensory Cortex, Male, P30, WT, replicate 1

description: Library name: S1.1265.P30.M.WT


title: Somatosensory Cortex, Male, P7, WT, replicate 2

description: Library name: S1.1330.P7.M.WT


title: Somatosensory Cortex, Male, P30, KO, replicate 2

description: Library name: S1.1266.P30.M.KO


title: HPAEC 3

data_processing:
Barcoded samples were pooled and sequenced using an Illumina NovaSeq 6000 in the Iowa Institute of Human Genetics (IIHG) Genomics Core Facility. Paired-end reads were demultiplexed and converted from the native Illumina BCL format to FASTQ format using a custom python workflow wrapper to Illumina’s ‘bcl2fastq’ conversion utility.  FASTQ data were processed with nf-core/rnaseq (v3.12), a best-practices pipeline available at the open-source ‘nf-core’ project (https://nf-co.re/, Nextflow version 22.10). Reads from the samples were aligned against the mouse reference genome ‘GRCh38’ using the STAR aligner and quantified with ‘salmon’. Samtools was used in conjunction with Qualimap and MultiQC to inspect alignment results. Length-normalized gene-level counts from the STAR/salmon pipeline were used for differential gene expression analysis with DESeq2.
nextflow run nf-core/rnaseq -r 3.10 -profile argon --igenomes_base /Users/mchiment/igenomes/references --input samplesheet_NOSKEL4.csv --outdir nf_NOSKEL4 --genome GRCh38 --email michael-chimenti@uiowa.edu --save_merged_fastq FALSE --skip_markduplicates TRUE --skip_preseq TRUE --skip_dupradar TRUE --skip_stringtie TRUE
Assembly: GRCh38
Supplementary files format and content: counts data

source_name: Extended Primary Cell Culture

extract_protocol:
RNA was harvested following Invitrogen Pure Link Mini extraction kit protocol
Illumina TruSeq

value: Extended Primary Cell Culture

value: HPAEC 3


title: Somatosensory Cortex, Female, P30, KO, replicate 3

description: Library name: S1.1264.P30.F.KO

value: Somatosensory Cortex


title: EHE 001 Early (1)

description: 10X Genomics


title: Somatosensory Cortex, Female, P30, WT, replicate 2

description: Library name: S1.1262.P30.F.WT

value: WT

value: Female


title: HPAEC 2

value: HPAEC 2


title: HPAEC 1

value: HPAEC 1


title: DSP-1001660019973-E-A11

value: 42444 is an early onset cancer

value: Yes

value: Slide1_S21-26292 A7_42444-4_Vimentin 1:150  and CD45-AF647(5 ug/mL), Pan CK and SYTO13


title: Somatosensory Cortex, Female, P30, KO, replicate 2

description: Library name: S1.1257.P30.F.KO

value: KO


title: Somatosensory Cortex, Male, P30, KO, replicate 3

description: Library name: S1.1341.P30.M.KO

value: Male


title: EHE 061 (1)


title: hiPSC-ExN WT bio rep 1

value: WTC11 hIPSC-ExN


title: Somatosensory Cortex, Female, P30, WT, replicate 1

description: Library name: S1.1258.P30.F.WT


title: EHE 061 (2)


title: EHE 061 (3)


title: EHE 061 Tumor

source_name: Primary Tumor

value: Primary Tumor

value: EHE 061 Tumor


title: EHE 053 (1)


title: EHE 053 (2)


title: Somatosensory Cortex, Female, P30, KO, replicate 1

description: Library name: S1.1254.P30.F.KO


title: EHE 053 (3)


title: Somatosensory Cortex, Male, P15, KO, replicate 2

description: Library name: S1.1223.P15.M.KO


title: EHE 001 Early (2)

description: 10X Genomics

value: Primary Cell Culture


title: Somatosensory Cortex, Male, P15, KO, replicate 3

description: Library name: S1.1231.P15.M.KO


title: Somatosensory Cortex, Male, P15, KO, replicate 1

description: Library name: S1.1210.P15.M.KO


title: Somatosensory Cortex, Female, P15, WT, replicate 1

description: Library name: S1.1212.P15.F.WT


title: EHE 036 Tumor

value: EHE 036 Tumor


title: EHE 036 (1)

value: Extended Primary Cell Culture


title: Somatosensory Cortex, Male, P30, KO, replicate 1

description: Library name: S1.1255.P30.M.KO


title: Somatosensory Cortex, Female, P7, KO, replicate 3

description: Library name: S1.1193.P7.F.KO


title: EHE 001 (2)


title: EHE 001 (1)


title: Somatosensory Cortex, Male, P15, WT, replicate 2

description: Library name: S1.1233.P15.M.WT


title: Somatosensory Cortex, Male, P7, KO, replicate 2

description: Library name: S1.1191.P7.M.KO


title: Somatosensory Cortex, Female, P7, WT, replicate 2

description: Library name: S1.1196.P7.F.WT


title: EHE 001 (3)


title: Somatosensory Cortex, Male, P7, KO, replicate 1

description: Library name: S1.1185.P7.M.KO


title: Somatosensory Cortex, Female, P7, KO, replicate 2

description: Library name: S1.1183.P7.F.KO


title: TCR_BM9_455_479_491_4

city: Seoul

first: Sojeong

last: Kim

address: 50-1 Yonsei-ro, Seodaemun-gu

department: Blood Cancer Research Institute

country: South Korea

institute: Yonsei University College of Medicine

data_processing:
To demultiplex the sequenced RNA data, the ‘mkfastq’ function (Cell Ranger, 10X Genomics, v3.0.1) was used to generate fastq files
Demultiplexed fastq files for gene expression were aligned to the reference human genome (GRCh38; 10X Cell Ranger reference GRCh38 v3.0.0) using Cell Ranger (v6.1.1).
The sequenced TCR data were aligned to the reference human genome (vdj_GRCh38_alts_ensembl-5.0.0)
Assembly: GRCh38
Supplementary files format and content: barcodes.tsv.gz for scRNAseq
Supplementary files format and content: features.tsv.gz  for scRNAseq
Supplementary files format and content: matrix.mtx.gz  for scRNAseq
Supplementary files format and content: TCR.csv for scTCRseq
Supplementary files format and content: demuxlet.best for demultiplexing
Library strategy: scTCR-seq

source_name: pooling of sorted CD4+ T cells obtained from BM455, BM479,BM491,BM4

growth_protocol: Primary human BMMCs were cryopreserved and subsequently thawed for use

extract_protocol:
BMMCs were isolated from bone marrow aspirates using Ficoll, cryopreserved, thawed, stained with anti-CD4 antibody, and sorted by FACS
Performed according to the manufacturer's protocol using Chromium Next GEM Single Cell 5' HT v2 Reagents
Single-cell RNA sequencing (scRNA-seq) and single-cell T-cell receptor sequencing (scTCR-seq) were performed simultaneously using multiplexing techniques.

treatment_protocol: No treatment

value: bone marrow

value: primary cells

value: mononuclear cells

value: No treatment


title: TCR_BM8_2_513_460_416

description: Chromium Next GEM Single Cell 5' HT v2 Reagents

source_name: pooling of sorted CD4+ T cells obtained from BM2, BM513,BM460,BM416


title: EHE 036 (3)


title: Somatosensory Cortex, Female, P7, KO, replicate 1

description: Library name: S1.1170.P7.F.KO

value: Somatosensory Cortex

value: Female


title: EHE 001 Tumor

source_name: Primay Tumor

value: Primay Tumor

value: EHE 001 Tumor


title: TCR_BM6_471_526_476_469

source_name: pooling of sorted CD4+ T cells obtained from BM471, BM526,BM476,BM469


title: Somatosensory Cortex, Male, P15, WT, replicate 1

description: Library name: S1.1220.P15.M.WT

value: WT


title: Somatosensory Cortex, Female, P7, WT, replicate 1

description: Library name: S1.1181.P7.F.WT


title: TCR_BM7_476_469_480_483

source_name: pooling of sorted CD4+ T cells obtained from BM476, BM469,BM480,BM483


title: Somatosensory Cortex, Female, P15, WT, replicate 2

description: Library name: S1.1221.P15.F.WT


title: Somatosensory Cortex, Female, P15, KO, replicate 1

description: Library name: S1.1215.P15.F.KO

value: KO


title: Somatosensory Cortex, Male, P7, WT, replicate 1

description: Library name: S1.1171.P7.M.WT

value: Male


title: EHE 036 (2)


title: TCR_BM5_489_450_465_470

source_name: pooling of sorted CD4+ T cells obtained from BM489, BM450,BM465,BM470


title: Cerebellum, Male, P30, WT, replicate 4

description: Library name: CB.CM847.P30.M.WT

source_name: Cerebellum

value: Cerebellum


title: Cerebellum, Male, P30, WT, replicate 3

description: Library name: CB.CM846.P30.M.WT


title: TCR_BM4_8_10_442_477

source_name: pooling of sorted CD4+ T cells obtained from BM8, BM10,BM442,BM477


title: Cerebellum, Male, P30, KO, replicate 4

description: Library name: CB.CM839.P30.M.KO


title: TCR_BM3_800_504_5_7

source_name: pooling of sorted CD4+ T cells obtained from BM800, BM504,BM5,BM7


title: TCR_BM2_400_500_600_700

source_name: pooling of sorted CD4+ T cells obtained from BM400, BM500,BM600,BM700


title: TCR_BM10_480_483_1_3

source_name: pooling of sorted CD4+ T cells obtained from BM480, BM483,BM1,BM3


title: Cerebellum, Male, P30, WT, replicate 2

description: Library name: CB.CM838.P30.M.WT


title: Cerebellum, Female, P15, KO, replicate 4

description: Library name: CB.1891.P15.F.KO


title: Cerebellum, Female, P0, WT, replicate 4

description: Library name: CB.1743.P0.F.WT


title: TCR_BM1_415_503_506_528

source_name: pooling of sorted CD4+ T cells obtained from BM415, BM503,BM506,BM528


title: GEX_BM9_455_479_491_4

data_processing:
To demultiplex the sequenced RNA data, the ‘mkfastq’ function (Cell Ranger, 10X Genomics, v3.0.1) was used to generate fastq files
Demultiplexed fastq files for gene expression were aligned to the reference human genome (GRCh38; 10X Cell Ranger reference GRCh38 v3.0.0) using Cell Ranger (v6.1.1).
The sequenced TCR data were aligned to the reference human genome (vdj_GRCh38_alts_ensembl-5.0.0)
Assembly: GRCh38
Supplementary files format and content: barcodes.tsv.gz for scRNAseq
Supplementary files format and content: features.tsv.gz  for scRNAseq
Supplementary files format and content: matrix.mtx.gz  for scRNAseq
Supplementary files format and content: TCR.csv for scTCRseq
Supplementary files format and content: demuxlet.best for demultiplexing


title: GEX_BM8_2_513_460_416


title: Cerebellum, Female, P0, KO, replicate 4

description: Library name: CB.1742.P0.F.KO


title: Cerebellum, Male, P0, WT, replicate 4

description: Library name: CB.1741.P0.M.WT


title: Cerebellum, Female, P0, WT, replicate 3

description: Library name: CB.1734.P0.F.WT


title: GEX_BM7_476_469_480_483


title: Cerebellum, Male, P0, WT, replicate 3

description: Library name: CB.1713.P0.M.WT


title: Cerebellum, Male, P0, KO, replicate 4

description: Library name: CB.1712.P0.M.KO


title: GEX_BM5_489_450_465_470


title: GEX_BM3_800_504_5_7


title: Cerebellum, Male, P0, KO, replicate 3

description: Library name: CB.1704.P0.M.KO


title: GEX_BM2_400_500_600_700


title: PTPRZ-Si_3_raw

city: changsha

first: ruijiang

last: Zeng

address: No.139 Renmin Road Central

country: China

institute: The Second Xiangya Hospital of Central South University

data_processing:
Total RNA qualification
mRNA enrichment
Double-strand cDNA synthesis
End repair, ploy-A & adaptor addition
Fragment selection and PCR
Library qualty assessement
illumina sequencing
Assembly: hg38
Supplementary files format and content: tab-delimited text files include read count values for each Sample

source_name: Kidney

growth_protocol: A498 cells were cultured in MEM medium supplemented with 10% fetal bovine serum (FBS) and incubated at 37 °C in 5% CO2.

extract_protocol:
RNA was harvested using Rneasy mini plus kit (Qiagen). 1.3 ug of total RNA was used for the construction of sequencing libraries.
RNA libraries for RNA-seq were prepared using NEBNext® Ultra™ Directional RNA Library Prep Kit for Illumina® following manufacturer's protocols.

value: Kidney

value: A498 cells

value: renal cancer cells

value: the treat group of knockdown of PTPRZ1 by siRNA

value: transfection infection


title: Cerebellum, Male, P0, WT, replicate 2

description: Library name: CB.1700.P0.M.WT


title: Cerebellum, Male, P0, KO, replicate 2

description: Library name: CB.1702.P0.M.KO


title: GEX_BM10_480_483_1_3

value: bone marrow


title: Cerebellum, Female, P0, KO, replicate 2

description: Library name: CB.1654.P0.F.KO


title: Cerebellum, Female, P15, WT, replicate 5

description: Library name: CB.1892.P15.F.WT


title: PTPRZ-Si_2_raw


title: Cerebellum, Female, P0, WT, replicate 2

description: Library name: CB.1653.P0.F.WT


title: PTPRZ-Si_1_raw


title: Cerebellum, Female, P0, KO, replicate 1

description: Library name: CB.1621.P0.F.KO


title: Cerebellum, Male, P0, KO, replicate 1

description: Library name: CB.1650.P0.M.KO


title: PTPRZ-nc_3_raw

value: the control group of knockdown of PTPRZ1 by plasmid


title: PTPRZ-nc_2_raw


title: Cerebellum, Female, P0, WT, replicate 1

description: Library name: CB.1614.P0.F.WT


title: GEX_BM6_471_526_476_469

value: primary cells

value: mononuclear cells


title: PCa-Inter-patient object

city: Toronto

first: Mathieu

last: Lupien

state: Ontario

address: 101 College Street

country: Canada

institute: University Health Network

description:
nuclear RNA, genomic DNA
inter- patient analysis, processed with Seurat and Signac, with the following versions: R=4.1.0, Signac=1.4.0, Seurat=4.1.0. Cells were filtered if one of the following criteria was met: nFeature_ATAC > 500, nFeature_RNA > 500, percent.mt < 20, TSS.enrichment > 2. Cells were removed if both of the following conditions were met: nFeature_RNA<8000 and nFeature_ATAC<80000. ATAC data from each sample was then reprocessed using a binned genome approach with 5kb window sizes across hg38 using the Signac::FeatureMatrix function

library_source: other

data_processing:
The generated fastq files were processed using cellranger-arc v2.0.0 count function for read trimming, alignment, duplicate marking (ATAC), and UMI counting (GEX) (Cell Ranger ARC, 10x Genomics). The reads were aligned to the pre-built human reference genome GRCh38—v2020-A-2.0.0 (3 May 2021) provided by 10x Genomics.
For each sample, output files from Cell Ranger Arc were processed with Seurat and Signac, with the following versions: R=4.1.0, Signac=1.4.0, Seurat=4.1.0. Cells were filtered if one of the following criteria was met: nFeature_ATAC > 500, nFeature_RNA > 500, percent.mt < 20, TSS.enrichment > 2. Cells were removed if both of the following conditions were met: nFeature_RNA<8000 and nFeature_ATAC<80000. ATAC data from each sample was then reprocessed using a binned genome approach with 5kb window sizes across hg38 using the Signac::FeatureMatrix function. Downstream analyses were performed on the resulting Seurat object, containing an RNA and tiled genome matrix and were merged across patients.
Assembly: human reference genome GRCh38—v2020-A-2.0.0 (3 May 2021)
Supplementary files format and content: all the files are the output files from cellranger-arc pipeline (see detailed information here: https://www.10xgenomics.com/support/software/cell-ranger-arc/latest/analysis/outputs/understanding-output)
Supplementary files format and content: RDS objects, are SEURAT objects per patient, described in the paper and the data processing step (see above, benchmark method: https://doi.org/10.1016/j.cell.2021.04.048)
Library strategy: Single Cell Multiome ATAC + Gene Expression

molecule: other

source_name: Prostate, Lymph node

extract_protocol:
The nuclei were isolated following the adapted protocol for clinically relevant frozen tissues described previously (https://doi.org/10.1038/nmeth.4396). We kept the samples on dry ice until use and weighed them individually before starting. The range in weight was between 7-24mg. To perform single-cell multiome ATAC + Gene expression, we added 0.2 U/ µl of Protector RNAse-Inhibitor (Sigma Aldrich PN-3335399001) to the Homogenization Buffer (HB) (according to the 3'GEX assay). In brief, we thawed the frozen tissue in a pre-chilled dounce with 1ml Homogenization buffer for 5 minutes. We then dounced with pestle A for 10 stokes on ice and continued with pestle B for another 10 stokes. We next filtered the solution through a 40µm tip into a prechilled 1.5ml Eppendorf tube and spun the nuclei (5min, 500 x g, 4 °C) in a fixed angle centrifuge. Then, we removed all but the pellet with 50µl of supernatant and re-suspended it in 350µl HB to have a total volume of 400µl. We transferred it to a 2ml Lo-Bind Eppendorf tube and added 1 volume (400µl) of 50% Iodixanol solution to give a final concentration of 25% Iodixanol and mixed by pipetting. Following, we slowly layered 600µl of 30% Iodixanol on top of 600µl prepared 40% Iodixanol and put 800µl of 25% Iodixanol/ sample mixture carefully on top. We collected 200µl of nuclei from the 30%-40% interface into a chilled 1.5ml tube. Afterwards, we aliquoted 32500 nuclei (to aim eventually for 10000 nuclei) into a 1.5ml tube. We again spun (10min, 600 x g, 4 °C) and discarded the supernatant. We next resuspended the pellet in ~6µl diluted nuclei buffer + RNase Inhibitor (see user guide, Chromium Next GEM Single Cell Multiome ATAC + Gene Expression from 10x).
Single-nucleus libraries were generated using the 10x Chromium Single-Cell Instrument and NextGEM Single Cell Multiome ATAC + Gene Expression kit (10x Genomics) according to the manufacturer’s protocol (Chromium Next GEM Single Cell Multiome ATAC + Gene Expression Reagent Kits User Guide; CG000338 Rev E). To minimize PCR biases during ATAC library construction (Section 5.1), we performed an extra short qPCR to assess how many cycles are needed to amplify our libraries without reaching saturation (1.: 72 ℃ for 5 min, 2: 98 ℃ for 30s, 3: 98 ℃ 10s, 4: 63 ℃ for 30s, 5: 72 ℃ for 1 min, 6: go to 3 -20 times). At the end of the qPCR run, we determined the number of cycles that should be used by looking at the plot of fluorescence vs. the cycle numbers to find out what the maximum fluorescence was, and at what cycle number ¼ of that maximum fluorescence was reached and continued with the ATAC library construction by PCR with 7-9 cycles.

value: Prostate, Lymph node

tag: disease

value: Prostate Cancer


title: GEX_BM4_8_10_442_477

value: No treatment


title: PTPRZ-nc_1_raw


title: Cerebellum, Female, P15, KO, replicate 3

description: Library name: CB.1546.P15.F.KO

value: Female


title: PCa-Patient5_ICGC_PCAL37

description:
nuclear RNA, genomic DNA
per patient analysis, processed with Seurat and Signac, with the following versions: R=4.1.0, Signac=1.4.0, Seurat=4.1.0. Cells were filtered if one of the following criteria was met: nFeature_ATAC > 500, nFeature_RNA > 500, percent.mt < 20, TSS.enrichment > 2. Cells were removed if both of the following conditions were met: nFeature_RNA<8000 and nFeature_ATAC<80000. ATAC data from each sample was then reprocessed using a binned genome approach with 5kb window sizes across hg38 using the Signac::FeatureMatrix function


title: Cerebellum, Female, P15, WT, replicate 4

description: Library name: CB.1544.P15.F.WT

value: WT


title: Cerebellum, Female, P0, KO, replicate 3

description: Library name: CB.1733.P0.F.KO

value: KO


title: PCa-Patient4_ICGC_PCAL34


title: Cerebellum, Male, P15, WT, replicate 3

description: Library name: CB.1542.P15.M.WT

value: Male


title: PCa-Patient2_ICGC_PCAL10


title: GEX_BM1_415_503_506_528


title: Cerebellum, Male, P15, KO, replicate 4

description: Library name: CB.1540.P15.M.KO

value: Cerebellum


title: Cerebellum, Female, P30, KO, replicate 4

description: Library name: CB.1467.P30.F.KO


title: Cerebellum, Female, P30, WT, replicate 4

description: Library name: CB.1466.P30.F.WT


title: PCa-Patient1_ICGC_PCAL03


title: Cerebellum, Female, P30, WT, replicate 3

description: Library name: CB.1465.P30.F.WT


title: PCa-Patient5_ICGC_PCAL37_Tu8

description:
nuclear RNA, genomic DNA
preprocessed with cellranger-arc count v2.0.0; files from the "outs" folder

source_name: Prostate

value: Prostate


title: PCa-Patient5_ICGC_PCAL37_Tu9


title: PCa-Patient5_ICGC_PCAL37_Tu7


title: Cerebellum, Male, P7, KO, replicate 3

description: Library name: CB.1414.P7.M.KO


title: Cerebellum, Female, P7, WT, replicate 4

description: Library name: CB.1410.43525.F.WT


title: Cerebellum, Male, P15, WT, replicate 4

description: Library name: CB.1547.P15.M.WT


title: Cerebellum, Female, P7, KO, replicate 4

description: Library name: CB.1381.P7.M.KO


title: Cerebellum, Male, P0, WT, replicate 1

description: Library name: CB.1620.P0.M.WT


title: Cerebellum, Male, P7, WT, replicate 4

description: Library name: CB.1380.P7.M.WT


title: PCa-Patient5_ICGC_PCAL37_Tu3


title: PCa-Patient3_ICGC_PCAL25


title: PCa-Patient5_ICGC_PCAL37_Tu4


title: Cerebellum, Female, P7, WT, replicate 3

description: Library name: CB.1374.P7.F.WT


title: Cerebellum, Male, P7, WT, replicate 3

description: Library name: CB.1370.P7.M.WT


title: PCa-Patient5_ICGC_PCAL37_Tu2


title: PCa-Patient5_ICGC_PCAL37_LN4

source_name: Lymph node

value: Lymph node


title: Cerebellum, Female, P15, WT, replicate 3

description: Library name: CB.1344b.P15.F.WT


title: PCa-Patient5_ICGC_PCAL37_Tu10


title: Cerebellum, Male, P30, KO, replicate 3

description: Library name: CB.1341.P30.M.KO


title: Cerebellum, Male, P30, KO, replicate 2

description: Library name: CB.1266.P30.M.KO


title: Cerebellum, Male, P7, WT, replicate 2

description: Library name: CB.1330.P7.M.WT


title: PCa-Patient5_ICGC_PCAL37_LN2


title: PCa-Patient4_ICGC_PCAL34_Tu8


title: PCa-Patient4_ICGC_PCAL34_Tu9


title: PCa-Patient5_ICGC_PCAL37_Tu5


title: Cerebellum, Male, P30, WT, replicate 1

description: Library name: CB.1265.P30.M.WT


title: Cerebellum, Female, P30, WT, replicate 2

description: Library name: CB.1262.P30.F.WT


title: Cerebellum, Female, P30, KO, replicate 3

description: Library name: CB.1264.P30.F.KO


title: PCa-Patient4_ICGC_PCAL34_Tu6


title: PCa-Patient4_ICGC_PCAL34_Tu5


title: PCa-Patient4_ICGC_PCAL34_LN1


title: PCa-Patient3_ICGC_PCAL25_Tu8


title: Cerebellum, Male, P30, KO, replicate 1

description: Library name: CB.1255.P30.M.KO


title: PCa-Patient3_ICGC_PCAL25_Tu6


title: Cerebellum, Female, P30, KO, replicate 2

description: Library name: CB.1257.P30.F.KO


title: Cerebellum, Female, P30, WT, replicate 1

description: Library name: CB.1258.P30.F.WT


title: PCa-Patient2_ICGC_PCAL10_Tu6


title: Cerebellum, Male, P15, WT, replicate 2

description: Library name: CB.1233.P15.M.WT


title: Cerebellum, Male, P15, KO, replicate 3

description: Library name: CB.1231.P15.M.KO


title: Cerebellum, Female, P7, WT, replicate 2

description: Library name: CB.1336.P7.F.WT


title: Cerebellum, Female, P15, KO, replicate 2

description: Library name: CB.1225.P15.F.KO


title: PCa-Patient2_ICGC_PCAL10_Tu4


title: PCa-Patient3_ICGC_PCAL25_Tu1


title: PCa-Patient5_ICGC_PCAL37_LN3


title: Cerebellum, Female, P15, WT, replicate 2

description: Library name: CB.1221.P15.F.WT


title: Cerebellum, Male, P15, KO, replicate 2

description: Library name: CB.1223.P15.M.KO


title: PCa-Patient2_ICGC_PCAL10_Tu3


title: PCa-Patient2_ICGC_PCAL10_Tu2


title: PCa-Patient2_ICGC_PCAL10_Tu1


title: PCa-Patient2_ICGC_PCAL10_LN6


title: Cerebellum, Female, P30, KO, replicate 1

description: Library name: CB.1254.P30.F.KO


title: PCa-Patient2_ICGC_PCAL10_Tu5


title: Cerebellum, Female, P15, KO, replicate 1

description: Library name: CB.1215.P15.F.KO


title: Cerebellum, Male, P15, WT, replicate 1

description: Library name: CB.1220.P15.M.WT


title: Cerebellum, Female, P15, WT, replicate 1

description: Library name: CB.1212.P15.F.WT


title: PCa-Patient2_ICGC_PCAL10_LN4


title: PCa-Patient2_ICGC_PCAL10_LN5


title: PCa-Patient2_ICGC_PCAL10_LN1


title: Cerebellum, Male, P7, KO, replicate 2

description: Library name: CB.1191.P7.M.KO


title: Cerebellum, Male, P15, KO, replicate 1

description: Library name: CB.1210.P15.M.KO


title: PCa-Patient1_ICGC_PCAL03_Tu4


title: PCa-Patient1_ICGC_PCAL03_Tu3


title: PCa-Patient2_ICGC_PCAL10_LN2


title: Cerebellum, Male, P7, KO, replicate 1

description: Library name: CB.1185.P7.M.KO


title: PCa-Patient1_ICGC_PCAL03_Tu7


title: Cerebellum, Female, P7, WT, replicate 1

description: Library name: CB.1181.P7.F.WT


title: Cerebellum, Female, P7, KO, replicate 3

description: Library name: CB.1183.P7.F.KO


title: Cerebellum, Female, P7, KO, replicate 2

description: Library name: CB.1180.43523.F.KO


title: Cerebellum, Female, P7, KO, replicate 1

description: Library name: CB.1170.P7.F.KO


title: Cerebellum, Male, P7, WT, replicate 1

description: Library name: CB.1171.P7.M.WT


title: PCa-Patient1_ICGC_PCAL03_LN1


title: PCa-Patient1_ICGC_PCAL03_Tu10


title: PCa-Patient1_ICGC_PCAL03_Tu2


title: PCa-Patient1_ICGC_PCAL03_Tu1


title: PCa-Patient1_ICGC_PCAL03_LN3


title: KS_9

city: La Plata

first: Martin

middle: Carlos

last: Abba

state: Buenos Aires

country: Argentina

institute: School of Medical Sciences - UNLP

data_processing:
The raw short-read sequences  were preprocessed using the Rfastp R/Bioconductor package Rsubread package. The raw short-read sequences  were quality-checked and trimmed to remove adapters and low-quality bases using the Rfastp R/Bioconductor package.
The preprocessed reads were then aligned and mapped to the human genome reference GRCh38 using the Subread aligner algorithm provided by the Rsubread R/Bioconductor package. The remaining non-human reads were aligned to the KSHV reference sequence NC_009333 for the KSHV GK18 strain.
The aligned reads (BAM files) from each sample were used to calculate gene expression abundance at the whole-genome level using the featureCounts function provided by the Rsubread package.
Assembly: Human genome: hg38 and KSHV genome: NC_009333
Supplementary files format and content: Tab-delimited csv file of the raw counts per sample

source_name: Skin

extract_protocol:
Total RNA was isolated from the collected samples using the miRNeasy Tissue/Cells Advanced Kits (Qiagen) following standard manufacturer's protocol. RNA concentration and integrity were measured on a Agilent 2100 Bioanalyzer (Agilent Technologies).
RNA samples with RNA integrity number (RIN) over 5 were considered for RNA sequencing. The RNA samples were processed for directional RNA-seq library construction using the Illumina Total RNA Prep with Ribo-Zero Plus library preparation kit according to the manufacturer's protocol.
We performed  101 nt paired-end sequencing using an Illumina Novaseq 6000 platform and obtained ~80 million clusters per sample with 92% >Q30.

value: Skin

tag: tumor type

value: Kaposi’s Sarcoma

tag: subject group

value: MSM

tag: hiv seroprevalence

value: Positive

tag: art treatment

value: No


title: KS_8

tag: tissue


title: DPCP Bulge-3

city: Taipei

first: Kai-Rong

last: Huang

address: No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan

department: Biomedical Engineering

country: Taiwan

institute: National Taiwan University

description: Library name: Sample18

data_processing:
Raw reads were checked with FastQC (v0.11.9), and adaptor sequences were trimmed using cutadapt (v3.5). The clean reads were aligned to the mouse reference genome GRCm38 using STAR (v2.7.6a) with two-pass mode.
Differential expression analysis was conducted using the R package limma (v3.60.6). Genes with an absolute value of log2fold change ≥ 1 and p-value < 0.05 were considered as significantly differentially expressed genes.
To identify enriched biological processes and pathways, over-representation analysis (ORA) and gene set enrichment analysis (GSEA) were performed on gene-set from MSigDB (v7.4) using ClusterProfiler (v4.12.6).
Assembly: Mouse mm10
Supplementary files format and content: TS231116003_DPCP.deg_by_limma.xlsx
Supplementary files format and content: csv file include TPM values of each samples

source_name: skin

extract_protocol:
Hair follicle stem cells were isolated by dissecting mouse dorsal skin and removing the fat layer. The skin was incubated in trypsin-EDTA at 37 °C for 20 minutes to separate the epidermal layer. Cell sorting was performed using the BD FACSAria™ III Sorter to isolate the desired cell populations.
Library construction for all samples utilized the Illumina TruSeq Stranded mRNA kit for 150 bp paired-end sequencing on the NovaSeq 6000 platform. Sequencing was performed using sequencing-by-synthesis technology with the NovaSeq 6000 S4 Reagent Kit v1.5 (300 cycles). Raw sequence data were obtained from the Illumina Pipeline Software.

value: skin

value: dermal keratinocytes


title: KS_7

value: Yes


title: DPCP day2 vs Control day0

description:
Library name: DPCP CD45 scRNA-seq cell plex
CellPlex

data_processing:
Raw data were processed using CellRanger (version 6.1.1, 10X Genomics) by aligning reads to the mouse reference genome (gex-mm10-2020-A, 10X Genomics). Data processing and analysis were conducted using Seurat (version 4.0.1).
Assembly: Mouse mm10
Supplementary files format and content: barcodes.tsv.gz
Supplementary files format and content: matrix.mtx.gz
Supplementary files format and content: features.tsv.gz
Supplementary files format and content: filtered_feature_bc_matrix.h5

extract_protocol:
Full-thickness skin samples were harvested and subjected to Liberase TM digestion. Cell sorting was performed using the BD FACSAria™ III Sorter to isolate CD45+ cell populations.
Single-cell RNA sequencing (scRNA-seq) of skin CD45+ immune cells was performed using the 10X Genomics Chromium 3' Solution platform. Libraries were sequenced on an Illumina NextSeq with paired-end sequencing.

value: immune cells


title: DPCP Germ-3

description: Library name: Sample15


title: DPCP Bulge-2

description: Library name: Sample17


title: KS_4

value: TGW


title: KS_5


title: DPCP EpSCs-3

description: Library name: Sample12


title: DPCP Bulge-1

description: Library name: Sample16


title: DPCP Germ-2

description: Library name: Sample14


title: DPCP Germ-1

description: Library name: Sample13


title: DPCP EpSCs-2

description: Library name: Sample11


title: DPCP EpSCs-1

description: Library name: Sample10


title: KS_2


title: CD45 DPCP day2, Control day0

description:
Library name: DPCP CD45 scRNA-seq
WTA
mixed sample


title: KS_6


title: nuclei, PEA4

city: Kobe

first: Takuo

last: Emoto

state: Hyogo

address: 7-5-1 Kusunoki-cho, Chuo-ku

department: Division of Cardiovascular Medicine, Department of Internal Medicine

country: Japan

institute: Kobe University Graduate School of Medicine

description: 10x Genomics

data_processing:
Cell Ranger Single Cell Software (v 6.0.1) by 10X Genomics against the GRCh38 human reference genome with default parameter
Assembly: GRCh38
Supplementary files format and content: Tab separated value files and matrix files

source_name: pulmonary endoatherectomy

extract_protocol:
Nuclei isolation was performed by using Minute™ Detergent-Free Single Nuclei Isolation Kit (Invent biotech, NI-024) with RNAse inhibitor (Invitrogen AM2694)
Single cell sequencing libraries were prepared as outlined in the 10x Genomics Single Cell 3’Reagent Kits v3.1 for snRNA-seq or 5’Reagent Kits v2 for scRNA-seq.

treatment_protocol: Each sample was washed, chopped into small pieces, and digested in enzymatic digestion buffer with 450 U/ml collagenase I (Sigma, C0130), 125 U/ml collagenase XI (Sigma, C7657), 60 U/ml DNase I (Roche, 04536282001) and 60 U/ml hyaluronidase (Sigma, H3506) at 37 °C for 30 minutes while shaking.1 The digested samples were filtered through 40-μm cell strainers (BD, 352340), washed, and centrifuged at 300g for 10 minutes.

value: pulmonary endoatherectomy

value: immune cell


title: Control Bulge-3

description: Library name: Sample9


title: nuclei, PEA3

description: 10x Genomics


title: nuclei, PEA2

description: 10x Genomics


title: Control Bulge-2

description: Library name: Sample8


title: nuclei, PEA1

description: 10x Genomics


title: Control Germ-3

description: Library name: Sample6


title: Control Germ-2

description: Library name: Sample5


title: Control Germ-1

description: Library name: Sample4


title: Control Bulge-1

description: Library name: Sample7


title: Control EpSCs-3

description: Library name: Sample3


title: cell, PEA4

description: 10x Genomics


title: cell, PEA3

description: 10x Genomics


title: KS_3


title: cell, PEA1

description: 10x Genomics


title: D13_sgRNA_SCR1_4

city: Zürich

first: Valdemar

middle: Jacob Sven-Åke

last: Priebe

address: Lengghalde 5

country: Switzerland

institute: Kindersptal Zürich/University of Zurich

data_processing:
Nextflow 23.04.4 nf-core/rnaseq 3.12.0 pipeline
Sequenced reads were trimmed for adapter sequences/low-quality reads with trimmgalore 0.6.7 (parameters --phred33 --length 30 -j 4).
Trimed sequences were aligned using STAR aligment 2.7.9a (parameters --alignIntronMax 1000000 --alignIntronMin 20 --alignMatesGapMax 1000000 --alignSJoverhangMin 8 --outFilterMismatchNmax 999 --outFilterMultimapNmax 20 --outFilterType BySJout --outFilterMismatchNoverLmax 0.1 --clip3pAdapterMMp 0.1 0.1 --clip3pAdapterSeq AAAAAAAA AAAAAAAA)
Read count quantification and normalization was done with Salmon 1.10.1.
Assembly: GCA_000001405.15_GRCh38_no_alt_analysis_set
Supplementary files format and content: Tab-separated values file includes counts for each sample
Supplementary files format and content: Tab-separated values file includes TPM values for each sample

growth_protocol: Cell lines were grown in RPMI 1634 Media (GIBCO) supplemented with 10% fetal bovine serum (FBS), 1% glutamine (GIBCO), penicillin (100U/mL) and streptomycin (100 μg/mL) at 37°C and 5% CO2. Mycoplasma tests were routinely performed.

extract_protocol:
Total RNA was extracted  by harvesting cells in TRIzol and using the Direct-zol RNA Miniprep Kit from Zymo Research.
RNA libraries for RNA-seq were generated usign lllumina Truseq mRNA Kit according to manufacturere's protocols.

treatment_protocol: HAL-01 cells stably expressing Cas9GFP, were  introduced with sgRNA targeting the TCF3::HLF bound MEF2C enhancer or control sgRNA.

value: Leukemia cell line

tag: genotype

value: Cas9GFP, Ctr_SCR

tag: time


title: KS_1


title: cell, PEA2

description: 10x Genomics


title: D13_sgRNA_SCR1_3


title: D13_sgRNA_SCR1_1


title: Control EpSCs-1

description: Library name: Sample1


title: B3

city: taiyuan

first: Zemin

last: Liu

state: shanxi

address: wuyi street number 382

department: Orthopedics

institute: Second Hospital of Shanxi Medical University

description: Library name: Sample6

data_processing:
The raw paired end reads were trimmed and quality controlled by fastp with default parameters.Then clean reads were separately aligned to reference genome with orientation mode using HISAT2 software. The mapped reads of each sample were assembled by StringTie in a reference-based approach.
To identify DEGs (differential expression genes) between two different samples, the expression level of each transcript was calculated according to the transcripts per million reads (TPM) method.
RSEM was used to quantify gene abundances.
Assembly: GRCm39
Supplementary files format and content: The table file contains the normalized expression levels of each gene in the samples, measured in TPM (Transcripts Per Million).

source_name: femur

extract_protocol:
Total RNA was extracted from the tissue using TRIzol® Reagent according the manufacturer’s instructions
The RNA-seq transcriptome librariy was prepared following Illumina® Stranded mRNA Prep, Ligation (San Diego, CA) using 1μg of total RNA. Shortly, messenger RNA was isolated according to polyA selection method by oligo(dT) beads and then fragmented by fragmentation buffer firstly. Secondly double-stranded cDNA was synthesized using a SuperScript double-stranded cDNA synthesis kit (Invitrogen, CA) with random hexamer primers. Then the synthesized cDNA was subjected to end-repair, phosphorylation and adapter addition according to library construction protocol. Libraries were size selected for cDNA target fragments of 300 bp on 2% Low Range Ultra Agarose followed by PCR amplified using Phusion DNA polymerase (NEB) for 15 PCR cycles. After quantified by Qubit 4.0, the sequencing library was performed on NovaSeq X Plus platform(PE150) using NovaSeq Reagent Kit.

value: femur

value: corn oil - injected control group


title: D13_sgRNA_97_4

value: Cas9GFP, MEF2C Enhancer KO


title: DPCP Visium HD D0-D3

description: Library name: DPCP Visium HD

data_processing:
Raw sequencing data were processed with Space Ranger (version 1.3.0, 10X Genomics) for read alignment, barcode assignment, and UMI counting
Assembly: Mouse mm10
Supplementary files format and content: barcodes.tsv.gz
Supplementary files format and content: features.tsv.gz
Supplementary files format and content: matrix.mtx.gz
Supplementary files format and content: aligned_fiducials.jpg
Supplementary files format and content: detected_tissue_image.jpg
Supplementary files format and content: scalefactors_json.json
Supplementary files format and content: tissue_hires_image.png
Supplementary files format and content: tissue_lowres_image.png
Supplementary files format and content: tissue_positions.parquet
Library strategy: Spatial Transcriptomics

extract_protocol:
All samples were embedded in one paraffin block. FFPE tissue sections (6 µm thick) were cut on Superfrost Plus adhesive microscope slides
Spatial gene expression libraries were generated according to the instructions of the Visium HD Spatial Gene Expression Kit from 10X Genomics (CG000685).

value: Skin


title: D13_sgRNA_96_3


title: D13_sgRNA_96_4


title: A3

description: Library name: Sample3

value: tamoxifen - induced FGF21 knockout group


title: B2

description: Library name: Sample5


title: A1

description: Library name: Sample1


title: A2

description: Library name: Sample2


title: B1

description: Library name: Sample4


title: D13_sgRNA_97_1


title: HAL-01, TCF3_KO, HiChIP, replicate1

data_processing:
*library strategy: HiChIP-seq
Paired-end read files were trimmed with TrimGalore v0.6.6 and filtered to eliminate short and low-quality reads (<50bp, phred 33), outputs of biological replicates were merged.
Trimmed and merged sequence reads were aligned to the hg38 genome using the bwa-mem algorithm from Burrows Wheeler Aligner, with settings as described in the HiChIP documentation release 0.1 by Dovetail®.
Interaction events are extracted with the parse module of pairtools  followed by sorting and splitting of the generated .pairsam file into .mapped.pairs and .mapped.bam files, the pairtools dedup step was omitted.
We used mapped.bam files to generate primary aligned bed files for 1D MACS2 peak calling as reference when calling genomic interactions with FitHiChIP, using 5kb bin size and 50kb to 3Mb range settings.
Assembly: GCA_000001405.15_GRCh38_no_alt_analysis_set
Supplementary files format and content: bigWig, hic, FitHiChIP interactions bed file

extract_protocol:
Genomic DNA was extracted in accordance with Dovetail®-HiChIP-MNase-Kit-User-Guide-Version-1.3.
HiChIP Library were generated using the Dovetail® Library module Kit according to instructions in Dovetail®-HiChIP-MNase-Kit-User-Guide-Version-1.3.

treatment_protocol: HAL-01 cells stably expressing Cas9GFP, were  introduced with sgRNA targeting wtTCF3 and selected for stable KO.

value: Cas9GFP, wt-TCF3 KO, t(17;19)

tag: chip antibody


title: Control EpSCs-2

description: Library name: Sample2


title: LS region, BALB/c nude

city: Shanghai

first: xia

middle: wen

last: Gao

state: Shanghai

address: No. 500 Zhen Nan Road

department: School of Medicine

institute: Tongji University

description:
Library name: Nude
10x Genomics

data_processing:
The sequenced reads were aligned to the mouse genome (mm10), using the Cellranger 7.0.1 software.
Assembly: Mouse mm10
Supplementary files format and content: Tab-separated values files and matrix files

source_name: brain tissue

extract_protocol:
Nuclei were isolated from fresh-frozen tissue, according to the published protocol with the several modifications. Briefly, frozen tissue was dunce homogenized with 10 strokes of a loose pestle followed by 10 strokes with a tight pestle at 4°C in a low sucrose buffer (0.32 M sucrose, 1 mM KH2PO4, 1 mM MgCl2, 0.2 mM EDTA, 0.1 mM DTT, 3 μM Actinomycin D and Protease/RNase inhibitor) with 0.25% Triton X-100 added. After homogenizing, they were filtered through a 40 μm strainer and mixed with equal volume of high sucrose buffer (2.2 M sucrose). The filtered and mixed crude nuclei preps were gently loaded in high sucrose buffer. Samples were centrifuged at 13,000 × g for 45 min at 4°C. Pellets were rehydration in concentration gradient sucrose solution with 0.4 U/μL RNase Inhibitor, transferred in new Eppendorf tubes and centrifuged for 5 min at 1,200 × g at 4°C. Finally, purified nuclei were re-suspended in 0.4% BSA PBS Buffer with 0.4 U/μl RNase Inhibitor, stained with trypan blue and counted using cell counting plate.
A total of 16,000 estimated nuclei from each sample were loaded on the 10X Single Cell work platform. Library construction was accomplished using the Chromium Single Cell 3' Library according to the manufacturer’s guidelines. Finally, libraries were sequenced using the Illumina Novaseq 6000 System platform.

value: brain tissue

value: brain cell

tag: age

value: 6-8 weeks old

tag: Sex

value: male

tag: batch


title: D13_sgRNA_96_1


title: RB1_22RV1_NC

data_processing:
Basecalls were performed using bcl2fastq v2.17 for Novaseq output.
CUT&tag reads were trimmed from 3' end until the final base had a quality score > 30, using Trimmomatic v0.33, discarding reads left with < 20 bp
CUT&tag reads were aligned to the UCSC hg38 genome using Bowtie version 2. Only uniquely mapping reads with at most two mismatches were retained.
To create CUT&tag coverage plots, the locations of the mapped CUT&tag reads were extended to 150 bp to represent sequenced fragments, renormalized (to reads per million, rpm) and reformatted in the bigWig file format.
Peaks were called uing MACS v2.1.0 with the significance cut-off p-value <=0.05
Assembly: hg38
Supplementary files format and content: bigwig,narrowPeak (except for Input sample)
Library strategy: CUT&tag

source_name: prostate gland

growth_protocol: 22RV1 cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) and incubated at 37 °C in 5% CO2.

extract_protocol:
Cells were fixed with 1% formaldehyde for 10 minutes. After quenching and cell lysis, chromatin was sonicated using a E220 focused-ultrasonicator (Covaris).
CUT&tag libraries were prepared using the KAPA HTP Library Preparation Kit complemented with NEXTflex DNA Barcodes from Bioo Scientific. 10 ng of DNA was used as starting material for input and ip samples. Libraries were amplified using 13 cycles on the thermocycler. Post amplification libraries were size selected at 250-450bp in length using Agencourt AMPure XP beads from Beckman Coulter. Libraries were validated using the Agilent High Sensitivity DNA Kit.

value: prostate gland

value: prostate cancer

value: the control group of knockdown of RB by siRNA


title: D30_PIMQ_scATAC

first: Luis

middle: F

last: Soto-Ugaldi

institute: The Rockefeller University

description:
Library name: Sample 51
Raw scATAC-seq reads were aligned using CellRanger ATAC (v2.0) to generate fragment files, and data processing was performed with ArchR (v1.0.2). Arrow files were constructed using default parameters, including gene score and tile matrices. Only fragments shorter than 600 bp were considered for all scATAC-se pre-processing steps and downstream analyses. Preprocessing of the D30 scATAC-seq dataset was carried out using ArchR (v1.0.2). Fragment files generated by CellRanger ATAC were used to construct Arrow files containing both TileMatrix and GeneScoreMatrix representations. To ensure data quality, cells were filtered based on three criteria: a minimum of 2,000 fragments per cell, a transcription start site (TSS) enrichment score greater than 5.5, and exclusion of cells identified as doublets. Doublet detection was performed using ArchR’s addDoubletScores() followed by filterDoublets(). In addition, immune cells were removed based on high PTPRC gene scores, resulting in a filtered dataset comprising 11,034 high-quality epithelial cells, with 5,399 from the Control group and 5,635 from the PIMQ group. Dimensionality reduction was performed using Iterative Latent Semantic Indexing (LSI) applied to the TileMatrix. The LSI procedure involved three iterations, using 20,000 variable features and retaining the top 30 principal components. Clustering was carried out using the Seurat method with a resolution of 0.2. A two-dimensional UMAP embedding was then computed using cosine distance with 30 neighbors and a minimum distance of 0.5. All filtering thresholds and dimensionality reduction parameters were selected based on diagnostic visualizations and gene score patterns, ensuring robust and reproducible separation of epithelial subpopulations for downstream analysis.

library_source: genomic single cell

data_processing:
Preprocessing of the D30 scATAC-seq dataset was carried out using ArchR (v1.0.2). Fragment files generated by CellRanger ATAC were used to construct Arrow files containing both TileMatrix and GeneScoreMatrix representations. To ensure data quality, cells were filtered based on three criteria: a minimum of 2,000 fragments per cell, a transcription start site (TSS) enrichment score greater than 5.5, and exclusion of cells identified as doublets. Doublet detection was performed using ArchR’s addDoubletScores() followed by filterDoublets().
The LSI procedure involved three iterations, using 20,000 variable features and retaining the top 30 principal components. Clustering was carried out using the Seurat method with a resolution of 0.2. A two-dimensional UMAP embedding was then computed using cosine distance with 30 neighbors and a minimum distance of 0.5. All filtering thresholds and dimensionality reduction parameters were selected based on diagnostic visualizations and gene score patterns, ensuring robust and reproducible separation of epithelial subpopulations for downstream analysis.
To define a reproducible peak set across cells, we used Macs3 through ArchR to perform peak calling independently for each dataset (D30 and Y1). First, pseudo-bulk replicates were generated by grouping cells by condition using addGroupCoverages function, restricting fragment lengths to a maximum of 600 bp to enrich for nucleosome-free regions. Peak calling was then performed using addReprodicublePeakset function with default parameters. The resulting peak set was used to construct a binary peak-by-cell accessibility matrix, again restricting fragments to a maximum length of 600 bp.  This resulted in 112211 and 164945 peaks for D30 and Y1 scATAC-seq, respectively
To address the sparsity of scATAC-seq data, we applied SEACell independently to the Control and PIMQ datasets for both D30 and Y1. Inputs included de novo peak-by-cell accessibility matrices (PeakMatrix), reduced-dimensional embeddings from iterative latent semantic indexing (LSI), and gene score matrices exported from ArchR. The kernel for SEACell inference was constructed using the LSI representation (X_svd). The number of SEACells was determined heuristically at approximately one SEACell per ~75 cells. A neighborhood graph was initialized using the top 10 waypoint eigenvectors, and metacell fitting was performed iteratively (up to 500 iterations) until convergence. Initialization and convergence diagnostics were visually inspected to ensure that SEACell archetypes were well distributed across the phenotypic space and that the model had stabilized. Both hard (each cell assigned to a single SEACell) and soft assignments (weight distribution across SEACells per cell) were computed. The weight distribution was analyzed to confirm that most cells had 1–4 SEACells with non-trivial contributions (weight > 0.1), indicating a sparse and interpretable clustering. The strength of the top five assignment weights per cell was also examined. SEACell purity was evaluated by comparing assignments to pre-existing ArchR clusters, revealing that most SEACells were predominantly composed of a single cell type, consistent with biological coherence.
Assembly: GRCm38 (mm10)
Supplementary files format and content: Pickle files

extract_protocol:
EpdSCs (CD49f+, Sca-1+, CD29+, CD34-, CD45-, CD117-, CD140a-, CD31-) were FACS isolated and nuclei extracted using 10x protocol for nuclei extraction. Following nuclei extraction downstream processing was performed by the Integrated Genomics Operation (IGO) at Memorial Sloan Kettering Cancer Center where single cell ATAC-seq was performed.
Single-cell ATAC-seq libraries were prepared using the 10x Genomics Chromium Single Cell ATAC Solution (v1.1) according to the manufacturer’s protocol. Briefly, nuclei were isolated from fresh/frozen tissue, tagmented with a Tn5 transposase loaded with sequencing adapters, and then encapsulated into Gel Bead-In Emulsions (GEMs) for barcoding. Following barcoding, libraries were PCR-amplified and purified. Final libraries were quantified and sequenced on an Illumina platform using paired-end sequencing.

value: Epidermal Stem Cell

value: wildtype

tag: treatment

value: 2-3 postnatal day 60  murine backskin was treated with Imiquimod for 6 consecutive days


title: pal_22RV1_NC

value: the control group of inhibition of CDK4/6 by PD0332991


title: LS region, BALB/c

description:
Library name: BC
10x Genomics


title: Y1_Naive_scATAC

description:
Library name: Sample 48
Raw scATAC-seq reads were aligned using CellRanger ATAC (v2.0) to generate fragment files, and data processing was performed with ArchR (v1.0.2). Arrow files were constructed using default parameters, including gene score and tile matrices. Only fragments shorter than 600 bp were considered for all scATAC-se pre-processing steps and downstream analyses. The Y1 dataset underwent the same preprocessing pipeline in ArchR, with adjusted quality control parameters to account for differences in sequencing depth and signal characteristics. Arrow files were generated with TileMatrix and GeneScoreMatrix for each sample. Cells were retained if they showed a TSS enrichment score of at least 13, had a minimum of 12,000 fragments, and were not classified as doublets by the addDoubletScores() and filterDoublets() functions, using UMAP as the neighborhood graph for doublet detection. These thresholds were selected based on manual inspection of UMAP projections colored by fragment counts and gene activity, allowing the selection of dense clusters representing high-confidence epithelial cells. After filtering, the final dataset included 4,476 epithelial cells, composed of 2,181 from the Control group and 2,295 from the PIMQ group. Dimensionality reduction was performed using Iterative LSI with three iterations and 20,000 variable features, retaining the top 30 components. Cells were clustered using the Seurat method at a resolution of 0.2, and UMAP was computed using 30 neighbors, a cosine distance metric, and a minimum distance of 0.5. To further assess the robustness of the low-dimensional embedding, a second round of LSI was performed using an expanded feature set of 30,000 tiles, followed by re-clustering and UMAP recalculation. Visual validation of cluster structure, fragment enrichment, and gene score patterns confirmed the stability and reproducibility of the embedding and ensured the integrity of the filtered dataset for subsequent analyses.

value: non-treated


title: LS region, C57BL/6JNifdc2

description:
Library name: C57_2
10x Genomics


title: LS region, C57BL/6JNifdc1

description:
Library name: C57_1
10x Genomics


title: PROseq_p300KO_CTRL_rep2

city: Miami

first: Carolina

middle: Paula

last: Banuelos

state: Florida

address: 1580 NW 10th Ave

department: Medicine

institute: University of Miami

data_processing:
*library strategy: PRO-seq
Raw fastq data underwent trimming using Cutadapt 1.14 and Trimmomatic v0.32 53,54followed by alignment using bowtie 1.1.2 to either the hg19 or dm3 genome 55. Strand-specific single nucleotide ends of aligned reads were constructed using BEDTools v2.28 with genomecov 56,and bedgraph data were normalized by the number of reads mapped to the spike-in dm3 genome before being transformed into bigwig data for further analysis.
Assembly: hg19
Supplementary files format and content: Tab-delimited tables with the comparision values between control and treatment using DESEQ2 and spike-in normalization and the read count of the last 40% of each gene
Supplementary files format and content: Bigwig files

source_name: cell line

extract_protocol:
Nuclear run-on assays were conducted using ten million nuclei, incubated for 3 minutes at 30 °C with 25 μM Biotin-11-ATP/UTP/CTP/GTP (PerkinElmer). Subsequently, total RNA was extracted and fragmented using 0.2 M NaOH for 10 minutes on ice, followed by purification of biotinylated nascent RNAs using streptavidin beads M-280 (Invitrogen, cat. no. 112.06D). Enzymatic steps involving RppH (NEB, cat. no. M0356S) and PNK (NEB, cat. no. M0201) were employed to remove the 5' cap, repair the triphosphate, and repair the 5' hydroxyl, respectively.
Adapter ligation and reverse transcription using SuperScript III (Invitrogen, cat. no. 56575) were performed, followed by PCR amplification. Size selection of libraries ranging from 140 to 350 bp was achieved using AMpure XP (Beckman Coulter #A63882), and sequencing was conducted on a NovaSeq 6000 (Illumina) platform with single-read runs.

value: cell line

value: HeLa

value: human cervical cancer

value: p300 knock-out

value: Ctrl


title: C57BL/6J female oocytes, Tubacin rescue, Repeat 2

city: Nanjing

first: Jianhua

last: Chen

state: Jiangsu

address: 101 Longmian Road

department: State Key Laboratory of Reproductive Medicine

institute: Nanjing Medical University

description: Library name: T2

data_processing:
Sequence reads were mapped to mouse genome by STAR software and then quantified using featureCounts.
The differential gene expression was analyzed with the R package DESeq2.  Genes with |log2 FC| > 1 and adjusted P value (by the Benjamini–Hochberg method) < 0.05 were considered DEGs
Assembly: GRCm38
Supplementary files format and content: excel file include FPKM for each Sample and Fold Change value.

source_name: oocyte

extract_protocol:
Five oocytes per sample were collected from the Control, DON-treated, and DON+Tubacin for RNA-sequencing. Each sample was lysed with 1 µL lysis buffer, and immediately used for cDNA synthesis via the SMART-seq2 method
Five oocytes per sample were collected from the Control, DON-treated, and DON+Tubacin for RNA-sequencing. Each sample was lysed with 1 µL lysis buffer, and immediately used for cDNA synthesis via the SMART-seq2 method

value: oocyte

value: WT


title: D13_sgRNA_97_3

value: Leukemia cell line

value: Cas9GFP, MEF2C Enhancer KO


title: Y1_PIMQ_scATAC

description:
Library name: Sample 49
Raw scATAC-seq reads were aligned using CellRanger ATAC (v2.0) to generate fragment files, and data processing was performed with ArchR (v1.0.2). Arrow files were constructed using default parameters, including gene score and tile matrices. Only fragments shorter than 600 bp were considered for all scATAC-se pre-processing steps and downstream analyses. The Y1 dataset underwent the same preprocessing pipeline in ArchR, with adjusted quality control parameters to account for differences in sequencing depth and signal characteristics. Arrow files were generated with TileMatrix and GeneScoreMatrix for each sample. Cells were retained if they showed a TSS enrichment score of at least 13, had a minimum of 12,000 fragments, and were not classified as doublets by the addDoubletScores() and filterDoublets() functions, using UMAP as the neighborhood graph for doublet detection. These thresholds were selected based on manual inspection of UMAP projections colored by fragment counts and gene activity, allowing the selection of dense clusters representing high-confidence epithelial cells. After filtering, the final dataset included 4,476 epithelial cells, composed of 2,181 from the Control group and 2,295 from the PIMQ group. Dimensionality reduction was performed using Iterative LSI with three iterations and 20,000 variable features, retaining the top 30 components. Cells were clustered using the Seurat method at a resolution of 0.2, and UMAP was computed using 30 neighbors, a cosine distance metric, and a minimum distance of 0.5. To further assess the robustness of the low-dimensional embedding, a second round of LSI was performed using an expanded feature set of 30,000 tiles, followed by re-clustering and UMAP recalculation. Visual validation of cluster structure, fragment enrichment, and gene score patterns confirmed the stability and reproducibility of the embedding and ensured the integrity of the filtered dataset for subsequent analyses.

value: Skin


title: PROseq_WT_UV_rep2


title: pal_22RV1_add

value: prostate gland

value: prostate cancer

value: the treat group of inhibition of CDK4/6 by PD0332991


title: D30_Naive_scATAC

description:
Library name: Sample 50
Raw scATAC-seq reads were aligned using CellRanger ATAC (v2.0) to generate fragment files, and data processing was performed with ArchR (v1.0.2). Arrow files were constructed using default parameters, including gene score and tile matrices. Only fragments shorter than 600 bp were considered for all scATAC-se pre-processing steps and downstream analyses. Preprocessing of the D30 scATAC-seq dataset was carried out using ArchR (v1.0.2). Fragment files generated by CellRanger ATAC were used to construct Arrow files containing both TileMatrix and GeneScoreMatrix representations. To ensure data quality, cells were filtered based on three criteria: a minimum of 2,000 fragments per cell, a transcription start site (TSS) enrichment score greater than 5.5, and exclusion of cells identified as doublets. Doublet detection was performed using ArchR’s addDoubletScores() followed by filterDoublets(). In addition, immune cells were removed based on high PTPRC gene scores, resulting in a filtered dataset comprising 11,034 high-quality epithelial cells, with 5,399 from the Control group and 5,635 from the PIMQ group. Dimensionality reduction was performed using Iterative Latent Semantic Indexing (LSI) applied to the TileMatrix. The LSI procedure involved three iterations, using 20,000 variable features and retaining the top 30 principal components. Clustering was carried out using the Seurat method with a resolution of 0.2. A two-dimensional UMAP embedding was then computed using cosine distance with 30 neighbors and a minimum distance of 0.5. All filtering thresholds and dimensionality reduction parameters were selected based on diagnostic visualizations and gene score patterns, ensuring robust and reproducible separation of epithelial subpopulations for downstream analysis.

value: Epidermal Stem Cell

value: wildtype


title: PROseq_p300KO_UV_rep2


title: C57BL/6J female oocytes, Tubacin rescue, Repeat 1

description: Library name: T1


title: PROseq_WT_CTRL_rep2


title: C57BL/6J female oocytes, DON treated, Repeat 1

description: Library name: D1


title: PROseq_p300KO_CTRL_rep1


title: PROseq_p300KO_UV_rep1


title: RB1_22RV1_Si

value: the treat group of knockdown of RB by siRNA


title: PROseq_WT_CTRL_rep1


title: C57BL/6J female oocytes, Control, Repeat 1

description: Library name: C1


title: C57BL/6J female oocytes, Control, Repeat 2

description: Library name: C2


title: EAC119_Mav_2_TCR

city: Cambridge

first: Elizabeth

last: Cooper

address: Li Ka Shing Centre, Robinson Way

country: United Kingdom

institute: CRUK Cambridge Institute

description:
Library name: SITTC7
10x Genomics 5' TCR

data_processing:
Single-cell gene expression data from Cell Ranger (v.7) output was analysed using standard scanpy (v.1.8.2) workflow. Doublet detection was performed using scrublet (v.0.2.3) with adaptations outlined previously. In brief, after scrublet was performed, the data were iteratively subclustered, and a median scrublet score for each subcluster was computed. Median absolute deviation scores were computed from the cluster scrublet scores and a one-tailed t-test was performed with Benjamini–Hochberg correction applied and cells with significantly outlying cluster scrublet scores (Benjamini–Hochberg-corrected P < 0.1) were flagged as potential doublets. Quality control and filtering were performed in Scanpy using the sc-dandelion pre-processing module (dandelion.pp,recipe_scanpy_qc) with max. genes = 6000, min. genes = 200 and a Gaussian mixture model distribution to determine mitochondrial filtering value .Genes were retained if they were expressed by at least three cells. Gene counts for each cell were normalized to contain a total count equal to 10,000 counts per cell. This led to a working dataset of 18630 cells. Highly variable genes were selected based on the following parameters: minimum and maximum mean expression are ≥0.0125 and ≤3 respectively; minimum dispersion of genes = 0.5. Batch correction was performed using harmonypy (v.0.0.5) after principal component analysis. Clustering was performed using the Leiden algorithm (v.0.8.2) with the resolution set at 1.0. The size of local neighbourhoods was set at 10. Uniform manifold approximation and projection (UMAP; v.0.5.1) was used for dimensional reduction and visualization, the minimum distance was set at 0.3 and all other parameters as per default settings in scanpy. Cell type identification was guided by manual inspection of canonical marker gene expression and top marker genes identified with Wilcoxon rank-sum tests.
Raw sequencing data were processed with Cell Ranger (v7.1.0) to generate V(D)J contigs. Annotated clonotype data were further analysed using Dandelion (v0.1.5)46. TCR α and β chains were matched per cell, and only high-confidence, productive clonotypes were retained. Clonotype expansion, overlap, and diversity metrics were computed using Dandelion’s built-in functions. Clonotype integration with transcriptomic data was performed by mapping TCR metadata onto the corresponding cell barcodes from RNA-seq datasets.
Genome_build: mm10 (ver. 3.0.0 provided by 10X Genomics)
Assembly: mm10
Supplementary files format and content: Cell ranger output files: barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz
Supplementary files format and content: Cell ranger output files: all_contig_annotations.csv, all_contig_fastq
Library strategy: scTCR-Seq

source_name: Brain

extract_protocol:
Tumour/brain samples from age-matched 6-8 week-old EPZFTA-RELA  (NestinCreERT2;Fus1;RFPTdT) mice were mechanically dissociated using sterile surgical scalpels into ∼1 mm3 cubes, and dissociated using the mouse tumour dissociation kit (Miltenyi Biotec) using the gentleMACS Octo Dissociator (Miltenyi Biotec). After dissociation, the samples were then filtered through 100 µm meshes and washed with 2% fetal bovine serum in RPMI, spun down 420 g for 5 minutes. Samples were resuspended in 40% percoll and centrifuged at 600 x g for 10 minutes. Supernatant was removed and washed with 2% fetal bovine serum in RPMI and resuspended on 0.05% BSA PBS solution. Samples were stained with DAPI (0.2 µg/ml). Samples were centrifuged, resuspended in FACS buffer with anti-CD16/32 (FC block; Biolegend) diluted 1:50 in FACS buffer and fluorescently conjugated antibodies (CD45-PE and anti-Ter 119 FITC)  at 4°C, followed by for 20 minutes. Cells were sorted using the Influx Cell Sorter (BD Biosciences) or FACsAria II (BD Biosciences) into 1% BSA coated 1.5 mL Eppendorf tubes with 500 μL of DMEM
Single-cell gene expression (GEX) and TCR/BCR libraries were constructed using the 10x Genomics Chromium platform. Cells were partitioned into Gel Bead-In-Emulsions (GEMs) with barcoded oligonucleotides for cell and molecular indexing. For GEX libraries, mRNA was reverse-transcribed, cDNA was amplified, and sequencing libraries were prepared. For TCR/BCR libraries, cDNA was enriched for V(D)J regions using target-specific primers before library preparation. Libraries were indexed, quantified, and sequenced on an Illumina platform. Paired-end sequencing enabled capture of transcriptomes and full-length V(D)J sequences, linking receptor information to gene expression profiles for each cell. Data were processed with 10x Genomics Cell Ranger pipelines.

treatment_protocol: EPZFTA-RELA (NestinCreERT2;Fus1;RFPTdT) tumour-bearing mice were randomised at 3 weeks old, confirmed by bioluminescence exploiting the endogenous NestinCre-ZFTA-RELA-IRES-Luciferase allele in EPZFTA-RELA. Mice received a single intrathecal injection of mavrilimumab (5 mg/kg; an anti-GM-CSF receptor alpha antibody) or control antibody, and were monitored with bi-weekly bioluminescence imaging to monitor tumour burden until mice reached a humane endpoint based on the accumulation of clinical signs.

value: Brain

value: Mavrilimumab


title: HAL-01, TCF3_KO, HiChIP, replicate2

value: Cas9GFP, wt-TCF3 KO, t(17;19)


title: PROseq_WT_UV_rep1

value: cell line

value: HeLa

value: human cervical cancer


title: hiOL_engrafted_in_LPC_lesion-young-12wpg [168]

city: Paris

first: Nadjet

last: Gacem

address: 47 BD de l'Hôpital, Hôpital de la Pitié Salpêtrière

country: France

institute: Paris Brain Institute

data_processing:
Quality of raw data has been evaluated with FastQC
Poor quality sequences has been trimmed or removed with Trimmomatic software to retain only good quality paired reads
Illumina DRAGEN bio-IT Plateform (v3.10.4) was used for mapping on hg38 reference genome and quantification with gencode v41 annotation gtf file.
Library orientation, library composition and coverage along transcripts were checked with Picard tools.
Supplementary files format and content: hg38
Supplementary files format and content: tab-delimited text files including expecting counts and TPM

source_name: iPSC

growth_protocol: hiOL expressing O4 and RFP were engrafted in LPC-induced lesions of young and aged animals and sacrificed at 12wpg

extract_protocol:
RNA extraction and RNA sequencing were performed with the NetSeq Illumina System
RNA libraries for RNA-seq were prepared using QuantSeq 3’ mRNA-Seq V2 Library Prep Kit with UDI Kit from Lexogen  following manufacturer's protocols.

treatment_protocol: The grafted spinal cord were dissociated with the Adult brain Dissociation kit (Miltenyi Biotec) and FACS-sorted to collect RFP+

value: iPSC

tag: group

value: Young


title: EAC119_Mav_1_TCR

description:
Library name: SITTA7
10x Genomics 5' TCR


title: hiOL_engrafted_in_LPC_lesion-young-12wpg [167]

value: WT


title: EAC119_Veh_1_TCR

description:
Library name: SITTB7
10x Genomics 5' TCR

value: Vehicle IgG


title: hiOL_engrafted_in_LPC_lesion-young-12wpg [166]


title: hiOL_engrafted_in_LPC_lesion-young-12wpg [163]


title: EAC119_Mav_2_GEX

description:
Library name: SITTH2
10x Genomics 5' GEX

data_processing:
Single-cell gene expression data from Cell Ranger (v.7) output was analysed using standard scanpy (v.1.8.2) workflow. Doublet detection was performed using scrublet (v.0.2.3) with adaptations outlined previously. In brief, after scrublet was performed, the data were iteratively subclustered, and a median scrublet score for each subcluster was computed. Median absolute deviation scores were computed from the cluster scrublet scores and a one-tailed t-test was performed with Benjamini–Hochberg correction applied and cells with significantly outlying cluster scrublet scores (Benjamini–Hochberg-corrected P < 0.1) were flagged as potential doublets. Quality control and filtering were performed in Scanpy using the sc-dandelion pre-processing module (dandelion.pp,recipe_scanpy_qc) with max. genes = 6000, min. genes = 200 and a Gaussian mixture model distribution to determine mitochondrial filtering value .Genes were retained if they were expressed by at least three cells. Gene counts for each cell were normalized to contain a total count equal to 10,000 counts per cell. This led to a working dataset of 18630 cells. Highly variable genes were selected based on the following parameters: minimum and maximum mean expression are ≥0.0125 and ≤3 respectively; minimum dispersion of genes = 0.5. Batch correction was performed using harmonypy (v.0.0.5) after principal component analysis. Clustering was performed using the Leiden algorithm (v.0.8.2) with the resolution set at 1.0. The size of local neighbourhoods was set at 10. Uniform manifold approximation and projection (UMAP; v.0.5.1) was used for dimensional reduction and visualization, the minimum distance was set at 0.3 and all other parameters as per default settings in scanpy. Cell type identification was guided by manual inspection of canonical marker gene expression and top marker genes identified with Wilcoxon rank-sum tests.
Raw sequencing data were processed with Cell Ranger (v7.1.0) to generate V(D)J contigs. Annotated clonotype data were further analysed using Dandelion (v0.1.5)46. TCR α and β chains were matched per cell, and only high-confidence, productive clonotypes were retained. Clonotype expansion, overlap, and diversity metrics were computed using Dandelion’s built-in functions. Clonotype integration with transcriptomic data was performed by mapping TCR metadata onto the corresponding cell barcodes from RNA-seq datasets.
Genome_build: mm10 (ver. 3.0.0 provided by 10X Genomics)
Assembly: mm10
Supplementary files format and content: Cell ranger output files: barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz
Supplementary files format and content: Cell ranger output files: all_contig_annotations.csv, all_contig_fastq


title: hiOL_engrafted_in_LPC_lesion-young-12wpg [160]


title: hiOL_engrafted_in_LPC_lesion-aged-12wpg [125]

value: Aged


title: EAC119_Veh_1_GEX

description:
Library name: SITTB2
10x Genomics 5' GEX


title: hiOL_engrafted_in_LPC_lesion-young-12wpg [161]


title: EAC119_Veh_2_GEX

description:
Library name: SITTG2
10x Genomics 5' GEX


title: hiOL_engrafted_in_LPC_lesion-aged-12wpg [115]


title: EAC119_Mav_1_GEX

description:
Library name: SITTA2
10x Genomics 5' GEX


title: EAC074_Endoint_T_5

description:
Library name: SITTH12
10x Genomics 5' GEX

data_processing:
Single-cell gene expression data from Cell Ranger (v.7) output was analysed using standard scanpy (v.1.8.2) workflow. Doublet detection was performed using scrublet (v.0.2.3) with adaptations outlined previously. In brief, after scrublet was performed, the data were iteratively subclustered, and a median scrublet score for each subcluster was computed. Median absolute deviation scores were computed from the cluster scrublet scores and a one-tailed t-test was performed with Benjamini–Hochberg correction applied and cells with significantly outlying cluster scrublet scores (Benjamini–Hochberg-corrected P < 0.1) were flagged as potential doublets. Quality control and filtering were performed in Scanpy using the sc-dandelion pre-processing module (dandelion.pp,recipe_scanpy_qc) with max. genes = 6000, min. genes = 200 and a Gaussian mixture model distribution to determine mitochondrial filtering value .Genes were retained if they were expressed by at least three cells. Gene counts for each cell were normalized to contain a total count equal to 10,000 counts per cell. This led to a working dataset of 125,000 cells. Highly variable genes were selected based on the following parameters: minimum and maximum mean expression are ≥0.0125 and ≤3 respectively; minimum dispersion of genes = 0.5. Batch correction was performed using harmonypy (v.0.0.5) after principal component analysis. Clustering was performed using the Leiden algorithm (v.0.8.2) with the resolution set at 1.0. The size of local neighbourhoods was set at 10. Uniform manifold approximation and projection (UMAP; v.0.5.1) was used for dimensional reduction and visualization, the minimum distance was set at 0.3 and all other parameters as per default settings in scanpy. Cell type identification was guided by manual inspection of canonical marker gene expression and top marker genes identified with Wilcoxon rank-sum tests.
Genome_build: mm10 (ver. 3.0.0 provided by 10X Genomics)
Assembly: mm10
Supplementary files format and content: Cell ranger output files: barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz
Supplementary files format and content: Cell ranger output files: all_contig_annotations.csv, all_contig_fastq

extract_protocol:
Tumour/brain samples from age-matched 6-8 week-old EPZFTA-RELA (NestinCreERT2;Fus1) and NestinCreERT2 mice were mechanically dissociated using sterile surgical scalpels into ∼1 mm3 cubes, and dissociated using the mouse tumour dissociation kit (Miltenyi Biotec) using the gentleMACS Octo Dissociator (Miltenyi Biotec). After dissociation, the samples were then filtered through 100 µm meshes and washed with 2% fetal bovine serum in RPMI, spun down 420 g for 5 minutes. Samples were resuspended in 40% percoll and centrifuged at 600 x g for 10 minutes. Supernatant was removed and washed with 2% fetal bovine serum in RPMI and resuspended on 0.05% BSA PBS solution. Samples were stained with DAPI (0.2 µg/ml). Samples were centrifuged, resuspended in FACS buffer with anti-CD16/32 (FC block; Biolegend) diluted 1:50 in FACS buffer and fluorescently conjugated antibodies (anti-Ter 119 FITC)  at 4°C, followed by for 20 minutes. Cells were sorted using the Influx Cell Sorter (BD Biosciences) or FACsAria II (BD Biosciences) into 1% BSA coated 1.5 mL Eppendorf tubes with 500 μL of DMEM
Single-cell gene expression (GEX) and TCR/BCR libraries were constructed using the 10x Genomics Chromium platform. Cells were partitioned into Gel Bead-In-Emulsions (GEMs) with barcoded oligonucleotides for cell and molecular indexing. For GEX libraries, mRNA was reverse-transcribed, cDNA was amplified, and sequencing libraries were prepared. For TCR/BCR libraries, cDNA was enriched for V(D)J regions using target-specific primers before library preparation. Libraries were indexed, quantified, and sequenced on an Illumina platform. Paired-end sequencing enabled capture of transcriptomes and full-length V(D)J sequences, linking receptor information to gene expression profiles for each cell. Data were processed with 10x Genomics Cell Ranger pipelines.


title: hiOL_engrafted_in_LPC_lesion-aged-12wpg [107]


title: EAC074_Endoint_T_2

description:
Library name: SITTC4
10x Genomics 5' GEX


title: hiOL_engrafted_in_LPC_lesion-aged-12wpg [209]


title: EAC074_Endoint_T_4

description:
Library name: SITTF2
10x Genomics 5' GEX


title: EAC074_Endoint_T_1

description:
Library name: SITTB7
10x Genomics 5' GEX


title: TJ-1_ESCs_primed_WGBS

first: Tao

last: Wu

address: Tongji University Siping Road Campus

department: school of life science and technology

data_processing:
All sequenced reads were checked for quality control by using FastQC (v0.11.9) with default parameters.
All sequencing reads were first trimmed to remove adaptors and low quality bases using trim_galore (v0.6.6) (parameters: --quality 20 --clip_R1 10 --clip_R2 10 --paired)
The processed reads were mapped to human hg38 genome using bismark (version: 2.5.1) for bisulfite sequencing reads with with default parameters.
For each CpG site, the numbers of methylated and unmethylated reads were counted.
Assembly: hg38
Supplementary files format and content: Methylation over mapped CGs. Column 1: chrbase; column 2: base; column 3: base; column 4: strand; column 5: coverage; column 6: freqC; column 7: freqT

source_name: primed

extract_protocol:
the Whole-Genome Bisulfite Sequencing libraries were constructed by following the manufacturer’s instructions.
WGBS libraries were prepared for sequencing using standard Illumina protocols

value: pluripotent stem cells

value: primed state


title: TJ-1_ESCs_naive_WGBS

source_name: cultured in 5iLAF

value: naive state


title: LKPY_WGBS_rep1

source_name: induce and maintain in LKPY medium


title: C57BL/6J female oocytes, DON treated, Repeat 2

description: Library name: D2

value: oocyte


title: LUDY_WGBS_rep2

source_name: induce and maintain in LUDY medium


title: LKPY_WGBS_rep2


title: EAC074_Endoint_NT_1

description:
Library name: SITTC3
10x Genomics 5' GEX


title: EAC074_Endoint_NT_4

description:
Library name: SITTF3
10x Genomics 5' GEX


title: EAC074_Endoint_NT_3

description:
Library name: SITTE3
10x Genomics 5' GEX


title: LUDY_WGBS_rep1


title: EAC074_Endoint_NT_2

description:
Library name: SITTD3
10x Genomics 5' GEX


title: LADY_WGBS_rep2

source_name: induce and maintain in LADY medium


title: EAC119_Veh_2_TCR

description:
Library name: SITTD7
10x Genomics 5' TCR


title: Sham-3, IP

city: WUHAN

first: chao

last: zhang

state: HUBEI

address: donghu

institute: Zhongnan Hospital of Wuhan University

description: Library name: sample 11

data_processing:
Briefly, Paired-end reads were harvested from Illumina Novaseq 6000 sequencer, and were quality controlled by Q30. After 3’ adaptor-trimming and low quality reads removing by cutadapt software (v1.9.3). First, clean reads of input libraries were aligned to reference genome (UCSC mm10) by STAR software. Then circRNAs were identified by DCC software using the STAR alignment results. After that, clean reads of all libraries were aligned to the reference genome by Hisat2 software (v2.0.4). Methylated sites on RNAs (peaks) were identified by MACS software. Differentially methylated sites were identified by diffReps. These peaks identified by both softwares overlapping with exons of mRNA, LncRNA and circRNA were figured out and chosen by home-made scripts. GO and Pathway enrichment analysis were performed by the differentially methylated protein coding genes, the associated genes of differentially methylated LncRNAs and the source genes of differentially methylated circRNAs separately.
Assembly: UCSC MM10
Supplementary files format and content: tab-delimited text file includes raw counts for each Sample
Library strategy: MeRIP-Seq

source_name: brain

growth_protocol: Male C57 mice (SPF-grade, 12-14 weeks old) used in this study were housed at the Animal Experiment Center of Zhongnan Hospital of Wuhan University. All mice were maintained in an environment with the temperature kept at 22-28°C, humidity maintained at 45-75%, and a 12-hour light/dark cycle. All mice had free access to food and water.

extract_protocol:
Total RNA was subjected to immunoprecipitation with the GenSeq® m5C-IP Kit (GenSeq Inc.) by following the manufacturer’s instructions. Briefly, RNA was randomly fragmented to ~200 nt by RNA Fragmentation Reagents. Protein A/G beads were coupled to the m5C antibody by rotating at room temperature for 1 h. The RNA fragments were incubated with the bead-linked antibodies and rotated at 4°C for 4 h. After incubation, the RNA/antibody complexes were washed for several times, and then, captured RNA was eluted from the complexes and purified.
RNA libraries for IP and input samples were then constructed with GenSeq® Low Input Whole RNA Library Prep Kit (GenSeq, Inc.) by following the manufacturer’s instructions. Libraries were qualified using Agilent 2100 bioanalyzer and then sequenced in a NovaSeq platform (Illumina).

treatment_protocol: The mice were divided into a sham-operated group (Sham) and a stroke model group (MCAO); to prepare the MCAO model, mice were first anesthetized by intraperitoneal injection of 1.3% pentobarbital sodium, then the neck area was shaved and disinfected, followed by a midline incision in the neck to expose the right common carotid artery (CCA), internal carotid artery (ICA), and external carotid artery (ECA); the distal end of the ECA was ligated using 6-0 silk suture, another 6-0 silk suture was passed through the ECA and secured as a loose knot near the CCA bifurcation; the CCA was temporarily clamped using an arterial clip, then a small incision was made in the ECA; a nylon monofilament suture with a silicone-coated tip was inserted into the ECA and advanced into the ICA until it reached the middle cerebral artery (MCA); after 60 minutes of ischemia, the suture was withdrawn and the proximal end of the ECA was ligated; the neck incision was sutured and disinfected, and mice were allowed to recover consciousness before returning to standard housing; at 24 hours post-surgery, mice were re-anesthetized via intraperitoneal injection and brain tissue was extracted for staining.

value: brain

value: Sham


title: LADY_WGBS_rep1


title: hiOL_engrafted_in_LPC_lesion-aged-12wpg [110]


title: Sham-1, inut

description: Library name: sample 8


title: Sham-2, inut

description: Library name: sample 10


title: Sham-3, inut

description: Library name: sample 12


title: Sham-1, IP

description: Library name: sample 7


title: LAY_WGBS_rep2

source_name: induce and maintain in LAY medium


title: prolong_LUDY_replicate2

data_processing:
All sequenced reads were checked for quality control by using FastQC (v0.11.9) with default parameters.
Sequenced reads was removed adapters and low-quality sequence by using trim_galore (v0.6.6 )with the default parameters.
The processed mRNA-Seq reads were mapped to hg38 genome using HISAT2(v2.2.0). Refseq genes were quantified to rawcount using featureCounts(v2.0.3).
Assembly: hg38
Supplementary files format and content: Tab-delimited text file includes rawcounts for each sample

source_name: induce in 5iLAF medium and maintain in LUDY medium

extract_protocol:
the mRNA sequencing libraries were constructed by following the manufacturer’s instructions.
mRNA-seq libraries were prepared for sequencing using standard Illumina protocols


title: MCAO-3,IP

description: Library name: sample 5

value: middle cerebral artery occlusion


title: Sham-2, IP

description: Library name: sample 9


title: EAC074_Endoint_T_3

description:
Library name: SITTE6
10x Genomics 5' GEX

value: Brain


title: prolong_LKPY_replicate1

source_name: induce in 5iLAF medium and maintain in LKPY medium


title: prolong_LKPY_replicate2


title: LAY_WGBS_rep1


title: MCAO-3,input

description: Library name: sample 6


title: prolong_LUDY_replicate1


title: MCAO-2,IP

description: Library name: sample 3


title: prolong_LADY_replicate2

source_name: induce in 5iLAF medium and maintain in LADY medium


title: MCAO-2,input

description: Library name: sample 4


title: MCAO-1,input

description: Library name: sample 2


title: E16.5_1

city: Zurich

first: Anamaria

last: Balic

address: Plattenstr. 11

department: Institute of Oral Biology

institute: University of Zurich Center for Dental Medicine

description: Library name: E16.5_1

data_processing:
Cellranger v4.0.0
Assembly: refdata-gex-mm10-2020-A
Supplementary files format and content: barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz

source_name: developing incisor

extract_protocol:
Chromium single cell 3' library & gel bead Kit v3 (10x Genomics)
Illumina Novaseq 6000 (Mus musculus)

value: developing incisor


title: E14.5_4

description: Library name: E14.5_4


title: E14.5_3

description: Library name: E14.5_3


title: LUDY_replicate2


title: prolong_LAY_replicate1

source_name: induce in 5iLAF medium and maintain in LAY medium


title: prolong_LAY_replicate2


title: LKPY_replicate2


title: MCAO-1,IP

description: Library name: sample 1


title: E16.5_2

description: Library name: E16.5_2


title: E14.5_1

description: Library name: E14.5_1


title: LKPY_replicate1


title: LADY_replicate1


title: E14.5_2

description: Library name: E14.5_2


title: LUDY_replicate1


title: LAY_replicate2


title: E11.5_4

description: Library name: E11.5_4


title: E11.5_2

description: Library name: E11.5_2


title: E11.5_3

description: Library name: E11.5_3


title: prolong_LADY_replicate1


title: E11.5_1

description: Library name: E11.5_1


title: Mixed-Het / 12454-JC-0022

city: Nashville

first: Shristi

last: Shrestha

address: 2213 Garland Ave

institute: Vanderbilt University

description:
Library name: 12454-JC-0022
Mouse (in vivo)

data_processing:
Real Time Analysis Software (RTA) and NovaSeq Control Software (NCS) (1.8.0; Illumina) were used for base calling. MultiQC (v1.7; Illumina) was used for data quality assessments. Genialis General RNA-seq analysis pipeline (STAR, v2.7.10b) was used. Analysis steps thus include trimming (BBDuk), mapping (STAR), expression quantification (STAR) and normalization (rnanorm).
Assembly: mm39
Supplementary files format and content: csv file include TPM counts per sample

source_name: Isolated islets

extract_protocol:
RNA was harvested using RNEasy mini plus kit (Qiagen), 1.3ug used for construction of sequencing libraries
A Quality Control analysis was performed on the RNA samples using the Agilent Bioanalyzer to assess quality and an RNA Qubit assay was used to determine quantity.  Poly(A) RNA enrichment was conducted using NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB), and the sequencing library was constructed by using the NEBNext Ultra II RNA Library Prep Kit (NEB) (P/N: E7765L, NEB, Ipswich, MA) following the manufacturer’s instructions.  End repair, A-tailing, and adapter ligation was performed to generate the final cDNA library. The library quality was assessed using a Bioanalyzer and quantified using a qPCR-based method with the KAPA Library Quantification Kit (P/N: KK4873) and the QuantStudio 12K instrument.  Prepared libraries were pooled in equimolar ratios, and the resulting pool was subjected to cluster generation using the NovaSeq 6000 System, following the manufacturer's protocols. 150 bp paired-end sequencing was performed on the NovaSeq 6000 platform targeting 50M reads per sample.  Raw sequencing data (FASTQ files) obtained from the NovaSeq 6000 was subjected to quality control analysis, including read quality assessment.

value: Isolated islets

value: Mouse (in vivo)

value: pancreatic islets

value: Mixed male MafA S64F (Het)

value: male


title: Mixed-Het / 12454-JC-0020

description:
Library name: 12454-JC-0020
Mouse (in vivo)


title: IARS1 mutation 1

first: Weitao

last: Zhou

state: Minhang district

address: Block 8, Children's Hospital of Fudan University, Wanyuan Road, Minhang District, Shanghai, China

institute: Children's Hospital of Shanghai Jiaotong University

description: 10× Genomics

data_processing:
The raw sequencing data were analyzed by the Cell Ranger pipeline (v3.0.1, 10x Genomics),
The gene-barcode matrix of UMI counts was then subjected to analysis with Seurat (v3.0.2) for quality control, normalization, dimensional reduction, batch effect removal, clustering and visualization
The uniform manifold approximation and projection (UMAP) was created based on the top 30 dimensions resulted from principal component analysis (PCA).
The cell clusters were identified from PCA-reduced data, and then determined with SingleR (v1.0.6) and automatic assignment.
Assembly: hg18
Supplementary files format and content: Tab-separated values files and matrix files

source_name: PBMC

extract_protocol:
the PBMCs were isolated through density gradient centrifugation using Ficoll-Paque Plus medium (GE Healthcare) and processed within 1 hour.
With survival rate of over 85%, the single cell suspensions were washed and resuspended at a concetration of 700-1200 cells/ul using the Chromium Next GEM Single Cell V(D)J Reagent Kits(10x Genomics) according to the manufacturer’s instructions. Based on a target cell count of 10,000-13,000, GEMs (Gel Bead in Embusion) were created for single cell isolation.
These GEMs were collected by oil breaking treatment and subjected to reverse transcription PCR for labeling. Subsequently, cDNA, along with cell barcodes, underwent PCR amplification. The single-cell RNA sequencing (scRNA-seq) libraries were prepared using the 5’ Library Kits (PN-1000165, PN-1000020)

value: PBMC

value: primary cells

value: mutation

value: no treatment