title: Rabbit 922 (22) dehydrated

city: West Lafayette

first: Jyothi

last: Thimmapuram

state: IN

address: YONG 1022, 155 S. Grant Street

department: Bioinformatics Core

institute: Purdue University

data_processing:
Reads were aligned against Oryctolagus_cuniculus.OryCun2.0/ ENSEMBL 95 using STAR v. 2.5.4b with the following flags  --runThreadN 8 --runMode alignReads --outSAMunmapped Within --outSAMattrIHstart 0 --outFilterIntronMotifs RemoveNoncanonical --outSAMstrandField intronMotif --twopassMode Basic
Gene expression was quantitated using HTSeq (v 0.7.0) with the following flags for all libraries: -m union -s yes -t gene -i gene_id
Genome_build: Oryctolagus_cuniculus.OryCun2.0/ ENSEMBL 95
Supplementary_files_format_and_content: tab-delimited text files include count values for each Sample

organism: Oryctolagus cuniculus

source_name: larynx (vocal folds)

extract_protocol:
Total RNA of vocal folds (control, n=4; dehydrated, n=6) was extracted with commercial kit RNeasy Fibrous Tissue Mini Kit (QIAGEN).
Library construction was done using NuGEN's Universal Plus mRNA Kit. Each library was performed with 200 ng of RNA. Unique barcodes were used for each library.

treatment_protocol: Rabbits (n=6) were systemically dehydrated with 5mg/Kg furosemide (IP injection) and euthanized when 5% dehydration was achieved (body weight loss). Four control (euhydrated) rabbits were used.

tag: breed

value: New Zealand White

value: male

tag: age

value: 6 months

value: larynx (vocal folds)


title: Lung_Het_01

status: Public on Jul 09 2020

type: SRA

city: Rochester

first: Hu

last: Li

state: MN

address: 200 First Street, Gonda Building G19-408

department: Molecular Pharmacology & Experimental Therapeutics

country: USA

institute: Mayo Clinic

library_source: transcriptomic

data_processing:
Fastq files of pair-end RNA-Seq reads were aligned with Tophat 2.0.14  to the reference genome UCSC mm10 using Bowtie2 2.2.6 with default parameters.
Gene level counts were obtained using featureCounts 1.4.6 from the subRead package with gene models from mm10 UCSC annotation packages.
Genome_build: mm10
Supplementary_files_format_and_content: raw counts in tab-delimited text file

molecule: total RNA

organism: Mus musculus

source_name: Lung

extract_protocol:
RNA was column-extracted using RNeasy Mini kit (Qiagen)
RNA-seq libraries were prepared from about 200 ng high-quality RNA using TruSeq RNA Library Prep Kit v2 (Illumina)

treatment_protocol: Asynchronously growing early passage MEFs were harvest at ~90% confluence. Whole Lungs were collected from 10 day old animals.

tag: tissue

value: Lung

tag: strain

tag: genotype/variation

value: Het


title: RMG Aero Stationary RppH+ TSS-seq rep4

city: Madison

first: Robert

last: Landick

state: WI

address: 1550 Linden Dr

institute: University of Wisconsin

data_processing:
Library strategy: TSS-seq
TSS-seq: In-line barcodes were removed from the 5’ end of reads and sequencing adapter readthrough was removed using trimmomatic v0.30 with the following parameters: HEADCROP:6 ILLUMINACLIP:TruSeq3-SE.fa:2:30:10  MINLEN:25. Reads were aligned to Z. mobilis ZM4 chromosome and plasmid sequences using Bowtie v1.0.0 with the following parameters -S -m 1 --phred33-quals -v 2. Read 5'-only coverage was calculated for each position in the genome for both plus and minus strands using BEDTools v2-2.20.1 genomeCoverageBed with the following parameters: -5 -d. Positions with zero read coverage were removed and plus and minus strand data were concatenated to generate 5p.complete.bedgraph files where negative coverage values correspond to minus strand values.
Genome_build: Genbank sequences CP023715.1, CP023716.1, CP023717.1, CP023718.1, and CP023719.1
Supplementary_files_format_and_content: 5p.complete.bedgraph files contain plus and minus strand, genome-wide read coverage for the corresponding sample where only the first base in the read is counted towards read coverage; coverage values are not normalized, negative values correspond reads mapped to the minus strand and positive coverage values correspond to reads mapped to plus strand. complete.bedgraph files contain plus and minus strand, genome-wide read coverage for the corresponding sample where every base in the read is counted towards read coverage; coverage values are not normalized, negative values correspond reads mapped to the minus strand and positive coverage values correspond to reads mapped to plus strand. compiledDESeq2.results.txt is a tab-delimited text file that contains the log2 fold change and adjusted p-value (aka q-value or FDR) for pair-wise differential expression analysis of RNA-seq gene counts. RNAseq.RSEM.expectedCounts.txt is a tab-delimited text file that contains the expected reads counts per gene as determined by rsem (used as described in corresponding data processing step description) compiled from all 19 RNA-seq data sets.

organism: Zymomonas mobilis subsp. mobilis ZM4 = ATCC 31821

source_name: cell culture

growth_protocol: Zymomonas mobilis subsp. mobilis ZM4 ATCC31821 grown in rich medium with glucose (RMG) containing per L 10 g yeast extract, 2.6 g KH2PO4, 5 g K2HPO4, and 20 g glucose or minimal media with glucose (MMG) containing per L 20 g glucose, 2.6 g KH2PO4, 5 g K2HPO4, 0.5 g NaCl, 1 g (NH4)2SO4, 0.2 g MgSO4·7H2O, 25 mg Na2MoO4·2H2O, 10 mg CaCl2·2H2O, 1 mg calcium pantothenate, 25 mg FeSO4·7H2O, and 20 g glucose, and was adjusted to pH 6.4 with HCl. Cell growth was monitored in real-time by light scattering (termed OD) at 600 nM and extracellular glucose concentration was measurement by YSI 2700 Select. Overnight starter cultures of ZM4 were grown in RMG in an anaerobic chamber and used to inoculate 3L cultures of media in bioreactors (Applikon Biotechnology). Anaerobic cultures were sparged with N2/CO2 gas mix at a rate of 150mL/min and cells were agitated at 300 rpm. Aerobic cultures were sparged with atmospheric air at a rate of 700mL/min and agitated at 500 rpm. All multiomics samples were collected at 50% glucose depletion from the media (mid-glucose phase time point) and 1-hour post glucose depletion (stationary phase time point).

extract_protocol:
Ten mL of culture was added to 1.25mL of ice-cold ethanol/phenol stop solution, and RNA was extracted using hot phenol method as described in PMID:21601083; total RNA was DNase I treated prior to all library construction.
TSS-seq libraries were constructed following methods from PMID:22617957 and PMID:27120414. RNA 5’ pyrophosphohydrolase (RppH) (New England BioLabs M0356S) was used in place of tobacco acid pyrophosphatase for pre-treatment of total RNA. For RppH-treated libraries, 2.5ug total RNA was incubated with 20U RppH and 2uL 10x Reaction Buffer in a final volume of 20uL at 37°C for 2hrs. RppH-untreated samples used 4uL H2O in place of RppH. TSS-seq 5' adapters contained 4mer in-line barcodes; after 5' adapter ligation three RppH-treated and three RppH-untreated samples were pooled prior to rRNA-depletion with the Illumina RiboZero Bacteria Kit.

tag: time point

value: stationary

tag: rna-pretreatment

value: RppH-treated

tag: molecule subtype

value: rRNA-depleted RNA


title: Tumor14

type: genomic

city: Badalona

first: Carolina

last: Armengol

state: Barcelona

address: Crta Can Ruti; cami de les escoles, S/N

country: Spain

institute: Germans Trias i Pujol Health Research Institute

hyb_protocol: Bisulphite converted DNA was amplified, fragmented and hybridized to Illumina Infinium Human Methylation EPIC Beadchip using standard Illumina protocol

scan_protocol: Arrays were imaged using a HiScan and standard recommended Illumina scanner setting

data_processing: There was preprocessing using the normalization method Funnorm, recommended for tumor samples as implemented in the minfi Bioconductor Package (v 1.24). CpGs were annotated with the closer gene. Probes containing single nucleotide polymorphisms were discarded from analyses to avoid confounding.

molecule: genomic DNA

organism: Homo sapiens

source_name: Tumor

label_protocol: Standard Illumina's Infinium HD Methylation Protocol

extract_protocol: MagMAX™ DNA Multi-Sample kit was used using following manufacturer’s instructions (Thermo Fisher Scientific)

tag: individual

value: patient 14

tag: gender

value: F

tag: disease state

value: Hepatoblastoma

value: Tumor


title: WT-C-TP-1 Lib1

city: Seongnam-si

first: Joohyun

last: Jee

state: Gyeonggi-Do

address: 712 CHA Bio Complex, 335 Pangyo-Ro, Sampyeong-Dong, Bundang-Gu

department: Department of Microbiology

country: South Korea

institute: CHA University

data_processing:
Single cell RNA-Seq data were processed by align reads, generate feature-barcode matrices and perform clustering and gene expression analysis using the Cell Ranger (v.3.1.0) with default options.
Subsequently, data QC, filtering, and visualization were used for the Seurat (v.2.3) R package.
Genome_build: mm10
Supplementary_files_format_and_content: tab-delimited text files include average gene expression values by clusters.

source_name: colon

extract_protocol: RNA libraries were prepared for sequencing using standard Illumina protocols

tag: cell type

value: Colon epithelium

value: colon

tag: treatment

value: irradiation exposed after 2 weeks

tag: genotype

value: wild type


title: Tumor12

value: patient 12


title: Rabbit 919 (19) dehydrated

value: New Zealand White

tag: Sex

value: male


title: RMG Aero Stationary RppH+ TSS-seq rep3


title: Tumor15

value: patient 15


title: RMG Aero Stationary RppH+ TSS-seq rep2


title: Lung_WT_03

value: Lung

value: WT


title: Rabbit 876 (18) dehydrated

value: 6 months

value: larynx (vocal folds)


title: RMG Aero Stationary RppH+ TSS-seq rep1

value: stationary

value: RppH-treated

value: rRNA-depleted RNA


title: Lung_WT_02


title: RMG Anaer mid-Glucose RppH+ TSS-seq rep3

value: mid-glucose


title: Lung_WT_01


title: Rabbit 875 (16) dehydrated


title: RMG Aero mid-Glucose RppH+ TSS-seq rep2


title: MEFs_Exp2_Het_03

source_name: Mouse embryonic fibroblasts

value: Embryo

value: Het


title: Nontumor9

source_name: Non tumor

value: patient 9

value: M

value: Hepatoblastoma

value: Non tumor


title: Rabbit 963 (15) dehydrated

value: New Zealand White


title: Rabbit 239 (13) dehydrated

value: male


title: MEFs_Exp2_Het_02


title: Rabbit 921 (21) control


title: MEFs_Exp2_Het_01


title: Tumor1

value: patient 1

value: F

value: Tumor


title: Rabbit 964 (17) control

value: 6 months


title: MMG Anaer Stationary RppH+ TSS-seq rep2


title: MEFs_Exp2_WT-NTD_03

value: WT-NTD


title: Rabbit 869 (14) control

value: larynx (vocal folds)


title: Tumor10

value: patient 10


title: MMG Anaer Stationary RppH+ TSS-seq rep1

value: stationary

value: RppH-treated

value: rRNA-depleted RNA


title: MEFs_Exp2_WT-NTD_02

value: Embryo


title: Tumor11

value: patient 11


title: Nontumor7

value: patient 7

value: M


title: MMG Anaer mid-Glucose RppH+ TSS-seq rep3

value: mid-glucose


title: Nontumor5

value: patient 5

value: Hepatoblastoma

value: Non tumor


title: MMG Anaer Stationary RppH+ TSS-seq rep3


title: Nontumor30

value: patient 30

value: F


title: Rabbit 240 (12) control

value: New Zealand White

value: male

value: 6 months


title: Nontumor6

value: patient 6


title: MMG Anaer mid-Glucose RppH+ TSS-seq rep2


title: MMG Anaer mid-Glucose RppH- TSS-seq rep2

value: RppH-untreated


title: YR_S3

city: Xining

first: Delin

last: Qi

address: No. 251, Ningda Road

country: China

institute: Qinghai university

data_processing:
Reads obtained from the sequencing machines included raw reads containing adapters or low quality bases which would affect the following assembly and analysis. Thus, to get high quality clean reads, reads were further filtered according to the following rules: 1) Removing reads containing adapters; 2) Removing reads consisting of all A bases; 3) Removing reads containing more than 10% of unknown nucleotides (N); 4) Removing low quality reads containing more than 50% of low quality (Q-value≤20) bases
Short reads alignment tool Bowtie2 (2.2.8) was used for mapping reads to ribosome RNA (rRNA) database. The rRNA mapped reads were then removed. The remaining reads were further used in assembly and analysis of transcriptome.
The rRNA removed reads of each sample were then mapped to reference genome by TopHat2 (version 2.1.1), respectively. The alignment parameters were as follows: 1) Maximum read mismatch is 2 2) Disables the coverage based search for junctions 3) The distance between mate-pair reads is 50bp 4) The standard deviation for the distribution on inner distance between mate-pair reads is 80bp
After aligned with reference genome, unmapped reads (or mapped very poorly) were then re-aligned with Bowtie2, the enriched unmapped reads were split into smaller segments which were then used to find potential splice sites. The section and the section position of these short segments were predicted as well. A set of splice sites was built with initial unmapped reads by TopHat2 without relying on the known genes annotation. Not only be used for identifying expressed genes and their quantitative expression, the sequence alignment will also be helpful to find alternative splicing and new transcripts.
Genome_build: Oncorhynchus mykiss Omyk_1.0
Supplementary_files_format_and_content: tab-delimited text files include RPKM values for each Sample ...

organism: Oncorhynchus mykiss

source_name: dorsal skin

extract_protocol:
The dorsal skin were collected immediately, then flash-frozen in liquid nitrogen,and total RNA was extracted from six simples using Trizol reagent. TruSeq™ RNA Sample Prep Kit with 5 μg of total RNA for RNA-seq library construction
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: phenotype

value: yellow mutant

value: dorsal skin

tag: mean weigth


title: MEFs_Exp2_WT_03

value: Embryo

value: WT


title: MEFs_Exp2_WT-NTD_01

value: WT-NTD


title: MMG Anaer mid-Glucose RppH+ TSS-seq rep1

value: RppH-treated

value: rRNA-depleted RNA


title: YR_S2


title: MEFs_Exp2_WT_02


title: YR_S1


title: Nontumor26

value: patient 26

value: M


title: MEFs_Exp2_WT_01


title: MEFs_Exp2_Het-NTD_03

value: Het-NTD


title: Cardiomyo2

type: RNA

city: Durham

first: Kathleen

last: McCann

state: NC

address: 111 TW Alexander Dr

institute: National Institute of Environmental Health Sciences

description: CMs day 16 replicate 2

hyb_protocol: Reporter and Capture probes were added according to the manufacturer’s directions (nanostring.com) to 50 ng of total RNA in a final volume of 15ul followed by hybridization for at least 14 hours at 65oC

scan_protocol: After sample processing according to manufacturer’s instructions on the nCounter Prep Station Model 5S, sample cartridges were scanned on an nCounter Digital Analyzer Model 5S, using 555 Fields of Vision (FOV) and the .rlf files ‘McCann_SnoRNA_2_C6118’ and ‘McCann_SnoRNA_3_C7138’ for Nano77 and Nano104 respectively.

data_processing: Raw data were normalized to the geometric mean of the positive control probes and to the geometric mean of snoRNAs that remain unchanged as determined by percent coefficient of variation (% CV) < 20 using nSolver Analysis Software 3.0.

source_name: Cardiomyocytes

growth_protocol: All cells were cultured at 37°C in 5% CO2.

extract_protocol: RNA was isolated from cells using Trizol, Dnase treated with Dnase I and further purified using Qiagen Rneasy mini kits. RNA concentration and purity was determined using a Qubit and Nanodrop.

treatment_protocol: Mouse embryonic stem cells were differentiated with retinoic acid for six days. Mouse embryonic stem cells were differentiated into embryoid bodies and then cardiomyocytes, which were selected using puromycin.

value: Cardiomyocytes

value: Differentiated, day16


title: Nontumor4

value: patient 4

value: Hepatoblastoma

value: Non tumor


title: WR_S2

value: wild-type


title: WR_S1


title: Cardiomyo1

description: CMs day 16 replicate 1


title: ESCs, aMHC3

description: CMs day 0 replicate 4

source_name: aMHC-puro ESCs

value: ESCs

value: Differentiated, day0


title: MEFs_Exp2_Het-NTD_02


title: MEFs_Exp2_Het-NTD_01


title: Cardiomyo3

description: CMs day 16 replicate 4


title: ESCs, aMHC2

description: CMs day 0 replicate 2


title: Nontumor16

value: patient 16


title: RMG Aero mid-Glucose RppH+ TSS-seq rep1

value: mid-glucose


title: Nontumor33

value: patient 33

value: F


title: Nontumor15

value: patient 15


title: Nontumor18

value: patient 18


title: Nontumor23

value: patient 23


title: MEFs_Exp1_KO-NTD_02

value: Embryo

value: KO-NTD


title: RMG Anaer Stationary Ribo-seq rep3

data_processing:
Library strategy: Ribo-seq
Ribo-seq: Sequencing adapter was trimmed from reads using fastx_clipper (fastx-0.0.13.2) with the following parameters: -a CTGTAGGCACCATCAATATCTCGTATGCCGTCTTCTGCTTG -l 25 -v -Q33 -c. Trimmed reads were mapped to ZM4 chromosome and plasmid sequences using Bowtie version 1.0.0 with the following parameters: -S --phred33-quals -l 25 -k 1 --best. BEDTools v2.20.1 genomeCoverageBed was used to generate per-nucleotide read coverage genome-wide for each DNA strand using the following parameters: -d -strand. Positions with zero read coverage were removed and plus and minus strand data were concatenated to generate complete.bedgraph files where negative coverage values correspond to minus strand values
Genome_build: Genbank sequences CP023715.1, CP023716.1, CP023717.1, CP023718.1, and CP023719.1
Supplementary_files_format_and_content: 5p.complete.bedgraph files contain plus and minus strand, genome-wide read coverage for the corresponding sample where only the first base in the read is counted towards read coverage; coverage values are not normalized, negative values correspond reads mapped to the minus strand and positive coverage values correspond to reads mapped to plus strand. complete.bedgraph files contain plus and minus strand, genome-wide read coverage for the corresponding sample where every base in the read is counted towards read coverage; coverage values are not normalized, negative values correspond reads mapped to the minus strand and positive coverage values correspond to reads mapped to plus strand. compiledDESeq2.results.txt is a tab-delimited text file that contains the log2 fold change and adjusted p-value (aka q-value or FDR) for pair-wise differential expression analysis of RNA-seq gene counts. RNAseq.RSEM.expectedCounts.txt is a tab-delimited text file that contains the expected reads counts per gene as determined by rsem (used as described in corresponding data processing step description) compiled from all 19 RNA-seq data sets.

extract_protocol:
Ribosome-profiling lysates were prepared as described in PMID:26054770. 30-35 nucleotide footprints were size selected and isolated by polyacrylamide gel electrophoresis.
Libraries were prepared as described in PMID:29606352.

value: stationary

value: ribosome protected RNA footprints


title: Nontumor17

value: patient 17

value: M


title: RMG Anaer Stationary Ribo-seq rep1


title: MEFs_Exp1_KO-NTD_03


title: MEFs_Exp1_KO-NTD_01


title: Nontumor2

value: patient 2

value: Hepatoblastoma

value: Non tumor


title: RMG Anaer Stationary Ribo-seq rep2


title: RMG Anaer mid-Glucose Ribo-seq rep3


title: RMG Aero mid-Glucose RppH+ TSS-seq rep3

value: RppH-treated

value: rRNA-depleted RNA


title: Nontumor28

value: patient 28


title: MEFs_Exp1_KO_03

value: KO


title: ESCs, aMHC1

description: Cardiomyocytes (CMs) day 0 replicate 1

value: ESCs

value: Differentiated, day0


title: MEFs_Exp1_KO_02


title: RMG Anaer mid-Glucose Ribo-seq rep2

value: mid-glucose


title: ESC2

description: mESCs +RA T=6 #4

source_name: ESCs


title: Nontumor14

value: patient 14

value: F


title: RMG Anaer mid-Glucose Ribo-seq rep1


title: Nontumor13

value: patient 13


title: MEFs_Exp1_KO_01

value: Embryo


title: RMG Aero Stationary Ribo-seq rep4

value: stationary

value: ribosome protected RNA footprints


title: ESCs, RA2

description: mESCs untreated T=0 #3

source_name: RA Treated ESCs

value: RA


title: MEFs_Exp1_WT_03

value: WT


title: ESCs, RA3

description: mESCs untreated T=0 #4


title: ipf04

city: los angeles

first: Changfu

last: Yao

state: Ca

address: 8700 Beverly Blvd. AHSP Room A9401

department: Lung and Regenerative Medicine Institutes

institute: cedars-sinai medical center

data_processing:
align with cellranger
Genome_build: hg38/GRCh38
Supplementary_files_format_and_content: h5

source_name: IPF lung explant

extract_protocol:
10x genomics chromium 3' single cell RNAseq kit v2 or v3
follow 10x genomics instruction

value: IPF lung explant

tag: group

value: IPF


title: ipf12


title: ipf1883


title: ipf07


title: RMG Aero Stationary Ribo-seq rep3


title: Nontumor11

value: patient 11

value: M

value: Hepatoblastoma

value: Non tumor


title: ipf03


title: RMG Aero Stationary Ribo-seq rep2


title: MEFs_Exp1_WT_01


title: FetalLiver6

source_name: Fetal liver

value: Fetal liver


title: ESC3

description: mESCS +RAT=6 #3

value: ESCs


title: B_M3

city: Changsha

first: wang

last: zhao

address: No.139 Middle Renmin Road, Changsha, Hunan

department: Department of Cardiovascular Medicine, The Second Xiangya Hospital

institute: Central South University

data_processing:
Illumina Casava1.7 software used for basecalling.
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to hg38(GRCh38.p5) whole genome using Tophat2 v2.1.0 with default parameters.
Fragments Per Kilobase of exon per Megabase of library size (FPKM) were calculated using cufflinks 2.1.1 following the protocol from Trapnell et al.,Nature Protocols, 2012.
Genome_build: Ensembl hg38(GRCh38.p5)
Supplementary_files_format_and_content: FPKM.txt is an text file containing the Fragments Per Kilobase of exon per Megabase of library size for each gene ID/gene
Supplementary_files_format_and_content: count.txt for every sample, which was generated by the HTSeq 0.6.1p2 software after mapping with Tophat2 2.1.0 by default parameter

source_name: HepG2 cell

extract_protocol:
To generate recombinant adenovirus vectors with APOAV expression, the pHBAd-MCMV-APOAV-GFP and adenovirus skeleton plasmid vector of pHBAd-BHG were co-infected into HEK293 cells with lipofectamine 2000 Kit following the manufacturer’s instruction. After 6 h transformation, the recombinant adenoviruses were harvested. Then, the insulin-resistant HepG2 cells were cultured and infected with the recombinant adenovirus vector for 48 h. The successful infection by recombinant adenovirus was determined, when the expression of GFP was observed by fluorescence microscopy.
RNA libraries were prepared for sequencing using standard Illumina protocols

value: APOAV overexpressed

tag: cell line


title: ipf01

tag: tissue


title: RAW 2

description: RAW 2


title: RAW 3

description: RAW 3


title: MEFs_Exp1_WT_02

tag: strain


title: RMG Aero mid-Glucose Ribo-seq rep3

value: mid-glucose


title: B_M2

tag: genotype/variation


title: RMG Aero mid-Glucose Ribo-seq rep2

tag: time point


title: NIH3T3 3

description: NIH3T3 3


title: RMG Aero Stationary Ribo-seq rep1

tag: rna-pretreatment


title: FetalLiver5

value: F


title: RMG Aero mid-Glucose Ribo-seq rep1

tag: molecule subtype


title: NIH3T3 2

description: NIH3T3 2


title: FetalLiver7


title: RAW 1

description: RAW 1


title: A_Con2

value: negative controls


title: B_M1


title: Nontumor10

tag: individual

value: patient 10


title: MMG Anaer Stationary Ribo-seq rep3

value: stationary


title: A_Con1


title: SSC4

description: 72B +G

source_name: Spermatogonial Stem Cells

value: Spermatogonial Stem Cells


title: MMG Anaer Stationary Ribo-seq rep1

value: ribosome protected RNA footprints


title: NIH3T3 1

description: NIH3T3 1


title: Rad B2

city: Shanghai

first: Ling

last: Tian

state: Shanghai

address: No. 650, New Songjiang Road

department: Institute of Translational Medicine

institute: Shanghai General Hospital

description: total RNA

data_processing:
Basecalls performed using CASAVA version 1.8
Sequenced reads were trimmed for adaptor sequence and were quality controlled by Q30.
After 3’ adaptor-trimming and low quality reads removing by cutadapt software (v1.9.3).
The high quality reads were aligned to circBase with STAR software (v2.5.1b) and circRNAs were detected and identified with DCC software (v0.4.4).
Genome_build: UCSC hg19
Supplementary_files_format_and_content: xlsx files include junction reads, logCPM(counts per million) by edgeR, etc.

source_name: pancreatic cancer cell-derived exosomes

growth_protocol: Pancreatic cell lines PANC-1, MIA PaCa-2 and BxPC-3 were generated by DMEM medium (Dulbecco’s Modified Eagle Medium, HyClone) with 2% FBS (Fetal Bovirne Serum with exosome depleting). SW1990 was generated by 1640 medium (Roswell Park Memorial Institute-1640, HyClone) with 2% FBS(Fetal Bovirne Serum with exosome depleting).

extract_protocol:
Total RNA was extracted using the Trizol reagent (Life technology) according to the manufacturer's protocol. And rRNAs were removed using Ribo-Zero rRNA Removal Kits (Illumina, USA).
RNA libraries were prepared for sequencing using standard Illumina protocols and sequencing library was determined by Agilent 2100 Bioanalyzer using the Agilent DNA 1000 chip kit (Agilent, part # 5067-1504) according to the manufacturer's protocol.

treatment_protocol: 10 Gy x-radiation treatment was used for generating dying tumor cells. Exosomes were purified from the conditioned medium using ultracentrifuge. Centrifugation was performed at 300 g, 2,000 g and 10,000 g to remove the live cells, dead cells and cell debris, respectively. The supernant was further purified using 0.22um filters. The crude extract of exosomes was obtained by ultra-high speed centrifugation (> 100,000 g). And the pallet was washed using PBS and repeated twice to remove the contaminated protein.

value: pancreatic cancer cells

value: PANC-1, SW1990, BxPC-3, MIA PaCa-2

tag: passages

value: exosome-derived total RNA


title: FetalLiver4

tag: gender


title: Nontumor12

value: patient 12

tag: disease state


title: MMG Anaer mid-Glucose Ribo-seq rep3


title: Rad B1

description: total RNA

tag: cell type


title: SSC2

description: 72 +G


title: SSC3

description: 72A +G


title: SSC1

description: 52 +G


title: MMG Anaer Stationary Ribo-seq rep2


title: MMG Anaer mid-Glucose Ribo-seq rep1


title: Con A2

description: total RNA


title: ipf02

value: IPF lung explant

value: IPF


title: Con A1

description: total RNA


title: 14_M3

city: Taian

first: yiming

last: Wei

address: Daizong Street, 61

institute: Shandong Agricultural University

data_processing:
We use internal software to filter reads, fllowed as:  1) Remove reads with adaptors;  2) Remove reads in which unknown bases(N) are more than 5%;  3) Remove low quality reads (we define the low quality read as the percentage of base which quality is lesser than 15 is greater than 20% in a read).
We use HISAT to perfrom genome mapping,HISAT:  version: v0.1.6-beta
The gene expression levels were measured in FPKM using StringTie software
Genome_build: The reference genome sequences (http://plants.ensembl.org/Zea_mays/Info/Index)

organism: Zea mays

source_name: endosperm

extract_protocol:
Total RNAs were extracted from the endosperm of WT and mutant at 12 DAP using the Trizol reagent (Ambion; Cat. No. 15596-026)
RNA libraries were prepared for sequencing using standard Illumina protocols

value: 12 days after pollination

value: endosperm

tag: genotype

value: smk8-ref mutant


title: C2C12 cells, Nano104_Myotubes 3

description: Myotubes 3

hyb_protocol: Reporter and Capture probes were added according to the manufacturer’s directions (nanostring.com) to 50 ng (Nano77) or 25 ng (Nano104) of total RNA in a final volume of 15ul followed by hybridization for at least 14 hours at 65oC

source_name: Differentiated C2C12 cells

treatment_protocol: C2C12 myoblasts were differentiated into myotubes for 7 days.

value: myoblasts

tag: treatment

value: Differentiated


title: 14_M2


title: WR_S3

tag: phenotype

value: wild-type

value: dorsal skin


title: 14_M1


title: BM-MCs-2

city: Sapporo

first: Norihisa

last: Ichinohe

state: Hokkaido

address: South-1, West-17, Chuo-ku,

department: Department of Tissue Development and Regeneration

country: Japan

institute: Sapporo Medical University School of Medicine

hyb_protocol: Hybridization was performed using a Gene Expression Hybridization kit (Agilent Technologies) according to manufacturer's instruction. Expression profiles were analyzed using an oligo microarray (SurePrint G3 Rat Gene Expression v2 G4853B).

scan_protocol: Array was scanned with an Agilent G2565BA Microarray Scanner.

data_processing: Agilent Feature Extraction Software (v 10.7) was used for background subtraction

organism: Rattus norvegicus

source_name: SHPCs clusters  were cut in the recipient livers with BM-MCs transplantation under microscopic observation with the use of ultraviolet laser

label_protocol: Total RNA (100 ng) was labeled using a Low Input Quick Amp Labeling Kit One-Color (Agilent Technologies) according to manufacturer's instruction.

extract_protocol: Total RNAs of prepared cells were extracted using the RNeasy Mini Kit (Qiagen).

value: F344 [dipeptidylpeptidase IV (DPPIV)+ strain]

value: Liver

value: small hepatocy-like progenitor cells (SHPCs) clusters


title: BM-MCs-3


title: C2C12 cells, Nano104_Myotubes 2

description: Myotubes 2


title: BM-MCs-1


title: K562 DMSO un-treated endpoint population

city: San Francisco

first: Manuel

middle: D

last: Leonetti

state: CA

address: 499 Illinois St 4th floor

institute: Chan Zuckerberg Biohub

library_source: genomic

data_processing:
detailed info and Python scripts available at github.com/mhorlbeck/ScreenProcessing
1. Base-calling and demultiplexing with bcl2fastq v2.17.1.14; --barcode-mismatches 1 --minimum-trimmed-read-length 5 --mask-short-adapter-reads 5
2. Convert raw sequencing files into library counts using bowtie alignment (i.e. identify the prevalence of each sgRNA sequences from original library in the cell population) github.com/mhorlbeck/ScreenProcessing/fastqgz_to_counts.py
3. Generate sgRNA phenotype scores, gene-level scores, and gene-level p-values: github.com/mhorlbeck/ScreenProcessing/process_experiments.py
Genome_build: hg19
Supplementary_files_format_and_content: alignment count text file;  summed read counts and reference library table

source_name: K562 DMSO

growth_protocol: A pool of lentiviral vectors encoding sgRNA sequences were packaged in HEK293T cells and then transduced into K562 expressing dCas9-KRAB. Infected cells were selected with puromycin (5 days) and passaged in de-lipidated media. Cells were harvested for genomic DNA at T0 (pre-treatment) and at treated/untreated screen endpoints.

extract_protocol:
genomic DNA
PCR Illumina adapter sequences from constant genomic regions flanking the variable sgRNA sequences to be probed

treatment_protocol: 1 µM myriocin

tag: timepoint

value: untreated enpoint

value: untreated


title: K562 T0 pre-treatment population


title: K562 myriocin treated endopint population

source_name: K562 myriocin

value: drug-treated endpoint

value: treated myriocin CAS 35891-70-4


title: C2C12 cells, Nano104_Myotubes 1

description: Myotubes 1


title: C2C12 cells, Nano104_C2C12 3

description: C2C12 3

source_name: C2C12 cells (mouse)

value: control


title: 14_WT2

value: wild type


title: C2C12 cells, Nano104_C2C12 2

description: C2C12 2


title: SHPCs-2

source_name: SHPCs clusters  were cut in the recipient control livers under microscopic observation with the use of ultraviolet laser


title: 14_WT1


title: SHPCs-3


title: C2C12 cells, Nano104_C2C12 1

description: C2C12 1


title: 14_WT3


title: SHPCs-1


title: MHs-2

source_name: MHs  were cut in the recipient control livers under microscopic observation with the use of ultraviolet laser

value: Mature hepatocytes (MHs)


title: Donor 12 tumour

status: Public on Jul 08 2020

city: Southampton

first: Sara

last: Waise

state: Hampshire

address: Somers Building MP284, Southampton General Hospital, Tremona Road

department: Cancer Sciences

country: United Kingdom

institute: University of Southampton

data_processing:
Base calls performed with bcl2fastq 2.18
All read pairs with a quality score of <10 were filtered
Reads were aligned to the human genome using STAR v2.5
Aligned exonic reads were tagged with a gene name
Digital expression matrices were created by counting the number of unique UMIs per gene per cell. Samples from three individual patients were merged together into a single matrix
scRNA-seq data processing and analysis was performed using the Seurat package in R (version 2.3.4). Initial quality control was carried out to remove low quality events. First, we used a random forest classifier to exclude empty droplets as described previously. Outliers for the fraction of reads mapping to mitochondrial genes (> 2 median absolute deviations; MADs) were identified to exclude apoptotic cells.
Initial clustering was performed using a subset of genes selected based on variance and average non-zero expression excluding extreme outliers. Raw counts data were transformed (log((counts+1)/10000)) and scaled (regressing out nUMI) before performing PCA. Clusters were identified with the FindClusters function, using principal components identified as significant with JackStraw analysis (p<1e-5) and a resolution of 0.2. Cluster markers were identified using the FindAllMarkers function  and cell types were assigned based on canonical marker expression or by significant enrichment (adj. p<0.0001) in previously described cell type markers from the Immunological Genome and LungGENS projects, assessed using the ToppFun gene set enrichment tool.
Genome_build: hg19
Supplementary_files_format_and_content: Digital expression matrices in tab-delinated text file

source_name: Lung

extract_protocol:
Fresh tissue was disaggregated with Collagenase P and DNAse for 1 hour
Libraries were prepared for sequencing as per the Drop-seq and standard Illumina protocols

value: Lung

tag: donor number

value: Donor 1

value: tumour


title: MHs-1


title: Donor 10 non-involved lung

value: non-involved lung


title: Donor 10 tumour


title: ESC1

description: mESCs +RA T=6 #1

value: ESCs


title: Donor 7 tumour

value: Donor 7


title: Donor 9 tumour

value: Donor 9


title: Donor 8 tumour

value: Donor 8


title: Donor 9 non-involved lung


title: Donor 6 tumour

value: Donor 6


title: Donor 5 tumour

value: Donor 5


title: Nontumor1

source_name: Non tumor

value: patient 1

value: F

value: Hepatoblastoma

value: Non tumor


title: Donor 7 non-involved lung


title: Donor 11 non-involved lung


title: Donor 3 tumour

value: Donor 3


title: Donor 3 non-involved lung


title: Donor 11 tumour


title: Donor 1 tumour


title: Donor 2 non-involved lung

value: Donor 2


title: Donor 2 tumour


title: Human patients 1-3, hashed and pooled

city: Stanford

first: Michael

last: Januszyk

address: 257 Campus Dr

department: Surgery

institute: Stanford University

data_processing:
Base calls were converted to reads with the software Cell Ranger (10X Genomics; version 3.1)'s implementation mkfastq. These were then aligned against either the GRCh38 v3.0.0 (for human) or mm10 v3.0.0 (for mouse) genomes using Cell Ranger’s count function (an implementation of STAR v2.7.0) with SC3Pv3 chemistry and 5,000 expected cells per sample.
Cell barcodes representative of quality cells were delineated from barcodes of apoptotic cells or background RNA based on a threshold of having at least 1000 transcripts profiled and less than 10% of their transcriptome of mitochondrial origin.
UMIs from each cell barcode were retained for all downstream analysis. Raw UMI counts were normalized with a scale factor of 10,000 UMIs per cell and subsequently natural log transformed with a pseudocount of 1 using the R package Seurat (version 3.1.1).
For human samples, which were hashtagged and pooled, The cell barcodes for each patient are kept in a separate  assay  embedded within the standard three 10X output files, which is the recommended storage format for HTO-indexed 10X data. The three human patients are represented by the following HTO antibodies (near the bottom of features.tsv):   Patient 1: TotalSeq-B-0252 HumanHashTag2--LNH-94_2M2-TSB   Patient 2: TotalSeq-B-0253 HumanHashTag3--LNH-94_2M2-TSB   Patient 3: TotalSeq-B-0254 HumanHashTag4--LNH-94_2M2-TSB   Patient 3 (technical replicate): TotalSeq-B-0255 HumanHashTag5--LNH-94_2M2-TSB  Values for each barcode for each cell can be found with the lookup indices of 33540, 33541, 33542, and 33533, respectively, in the matrix.mtx file.  Please see the associated Seurat vignette for additional details: https://satijalab.org/seurat/v3.1/hashing_vignette.html
Hashtag oligos (HTOs) for human samples were demultiplexed using Seurat’s implementation HTODemux. Briefly, k-medoid clustering is performed on the normalized HTO values, after which a ‘negative’ HTO distribution is calculated. For each HTO,  the cluster with the lowest average value is treated as the negative group and a negative binomial distribution is fit to this cluster. Using the 0.99 quantile of this distribution as a threshold, each cell is classified as positive or negative for each HTO. Cells that are positive for more than one HTOs are annotated as doublets and removed. Cells that are not positive for any HTO are also removed.
As recommended [41], a threshold of P-adjusted < 0.1 was used to define significance for differentially expressed genes
Genome_build: GRCh38 v3.0.0 for human, mm10 v3.0.0 for mouse
Supplementary_files_format_and_content: Filtered 10X matrix counts

source_name: Human

extract_protocol:
For mouse and human adhesion fibroblasts, fibroblasts were isolated from fresh specimens using FACS. RNA extraction was performed using Qiagen miRNeasy kit (cat. 1071023) with on column DAnase treatment per the manufacturer’s recommendations. The Clontech Smarter Ultra Low Input RNA kit (Takara Bio, Cat. 634848) was used to generate cDNA from 150 pg total RNA following the manufacturer’s recommendations.  Amplified cDNA was purified using SPRI Ampure Beads (Beckman Coulter, Cat. A63880) and the quality and quantity was measured using a High Sensitivity DNA chip on the Agilent 2100 Bioanalyzer (Agilent Technologies).
cDNA was sheared to an average length of 300 basepairs using a Covaris S2 ultrasonicator (Covaris) and libraries were generated with the Clontech Low Input Library Prep kit (Takara Bio, Cat. 634947).
The samples were uniquely barcoded, pooled, and sequenced on a single lane of the NextSeq 500 (Illumina). A total of 300 million paired-end, 151 base pair reads were obtained, resulting in 50 million reads per sample.

treatment_protocol: Fresh adhesion or control tissue from mouse or human specimens was minced on ice. The tissue was then digested for 60 minutes in a 37 deg C water bath agitator in 2 mg/mL collagenase (collagenase type IV, ThermoFisher) digest buffer in Medium 199 (HyClone, GE Healthcare) consisting of 5% fetal bovine serum (Gibco FBS, ThermoFisher), DNase I (Worthington), Poloxamer 188 (Cat. P5556-100ML, Sigma), HEPES, and CaCl2. The digest was quenched with quench media (DMEM (Gibco DMEM, ThermoFisher) with 15% FBS), then centrifuged at 300 x G for 5 minutes at 4 deg C, resuspended in quench media, and filtered through 100, 70, and 40m cell strainers (Falcon cell strainer, ThermoFisher). Red blood cell lysis was performed using Hybri-Max (Sigma) per the manufacturers protocol. Histopaque was performed using Histopaque-1119 (Sigma Aldrich), per the manufacturers protocol.   Cells were counted and re-suspended in FACS buffer. Primary antibodies were applied, and cells were stained in the dark with gentle agitation for 30 minutes. Cells were then washed thoroughly in FACS buffer. Staining with secondary antibodies was conducted in the same manner. Propidium iodine (PI, Thermofisher, Cat. P3566, lot: 1755970, 3 g/mL) or DAPI (Thermofisher, Cat. 3571) were used as a viability marker. Fibroblasts were isolated using the FACS Aria II system. For RNA sequencing, cells were sorted into chilled lysing reagent under RNA/DNAse-free conditions (Trizol LS, ThermoFisher).

tag: tag

value: abdominal adhesion


title: H661-Entinostat-rep1

city: BOSTON

first: Li

last: Chai

state: MA

address: 77 AVENUE LOUIS PASTEUR, NRB652-4A

institute: BRIGHAM AND WOMENS HOSPITAL

data_processing:
Illumina Bcl2fastq v2.18
Supplementary_files_format_and_content: raw and normalized miRNA counts

source_name: H661 cells

growth_protocol: H661 cells were culutred by RPMI1640 medium supplied with 10% FBS

extract_protocol:
RNA was harvested using Trizol reagent
NEB small RNA library prep reagents were used with 1ug of total RNA input

treatment_protocol: DMSO or 2.5 μM Entinostat for 8 hours

value: lung cancer cell line

tag: cell line

value: Entinostat


title: H661-Entinostat-rep2


title: H661-DMSO-rep2

value: DMSO


title: H661-DMSO-rep1


title: H929_Fluva_rep1

city: Toronto

first: Petr

last: Smirnov

state: ON

address: 27 King's College Cir

department: Medical Biophysics

country: Canada

institute: University of Toronto

data_processing:
STAR Aligner version 2.5.2b, align to transcriptome BAM using gencode v26
RSEM v1.3.0 to estimate expected counts
Genome_build: hg38
Supplementary_files_format_and_content: Estimated counts for each sample for genes annotated in Gencode v26, estimated using STAR-RSEM

source_name: Multiple myeloma cell line

extract_protocol:
Qiagen RNeasy
Illumina TruSeq Stranded Total RNA Sample Preparation kit with RiboZero Gold. PhiX spike-in at 0.5% per lane.

treatment_protocol: 24 hr treatment with fluvastatin (2 micromolar) or ethanol as a solvent control

value: Fluvastatin


title: H929_Fluva_rep2


title: H929_EtOH_rep1

value: Ethanol


title: KMS11_EtOH_rep2


title: KMS11_Fluva_rep2


title: KMS11_Fluva_rep1


title: Erythroid cells, Input_Don003_Ery_d13_rep1

city: Headington

first: Damien

last: Downes

state: Oxfordshire

address: John Radcliffe Hospital

department: MRC Weatherall Institute of Medicine

institute: The University of Oxford

description: Genome-wide library of Immunoprecipitated fragments

data_processing:
Mapping : bowtie -m 2 --maxIns 350, hg19
For un-mapping reads : trimming adaptors trim_galore -- length 10, combining overlapping R1-R2 reads : flash -m 9 -x 0.125
Combining trimmed+flashed and originally mapped reads, mapping again with  bowtie -m 2 --maxIns 350
Removing read pairs overlapping Blacklisted regions
Removing duplicates : samtools rmdup
Reconstructing sequenced fragments from R1+R2 read pairs ( bedtools bedpe | cut -f 1,2,6) - for visualisation
Pileup of fragments (bedtools genomecov -counts)
Generating bigwig tracks (deeptools bamCoverage --bam ${bamname}.bam -o ${bamname}.bw --binSize 10 --normalizeUsingRPKM --minMappingQuality 1)
Genome_build: hg19
Supplementary_files_format_and_content: bigWig : FPKM normalised coverage of filtered fragments (reconstructed, duplicate-filtered fragments)

source_name: CD34 Culture

growth_protocol: Fresh whole blood collected from three healthy donors (two males, one female) using EDTA Vacuettes (Becton Dickson) or 5 ml leukocyte cones (NHS Blood & Transport). Whole cell counts were performed on a Pentra ES60 (Horiba) for donor blood to ensure clinically healthy red blood cell counts. Blood was diluted with PBS and overlaid onto Histopaque-1077 (Sigma) and centrifuged for 30 min at 630 rcf (no brake). Peripheral Blood Mononuclear Cells (PBMCs) were washed in PBS and MACS buffer (PBS, 2 µM EDTA, 0.5% BSA) and stained with Human CD34 Microbead kit (Miltenyi Biotec) following the manufacturer’s instruction for 30 minutes (4 ºC) before being passed successively through two LS Columns (Miltenyi Biotec) with three MACs buffer washes. Counting of cells was performed on a Luna FL (Logos) after staining with acridine orange (AO) and propidium iodide (PI). CD34+ cells were either stored in freezing buffer (90% FBS, 10% DMSO) or resuspended in growth media for differentiation. Differentiation was performed as per Mettananda et al. 2018 (PMID: 28871148): CD34+ cells were differentiated into erythroid cells over 21 days using a two-phase liquid culture system which used StemSpan SFEM II (Stemcell Technologies). Phase 1 medium was supplemented with stem cell factor, interleukin-3, human recombinant erythropoietin (EPO) (0.5 U/ml) and cholesterol-rich lipids. Phase 2 medium was similar to phase 1 medium except for addition of iron saturated holotransferrin and higher concentration of EPO (3 U/ml).

extract_protocol:
For ChIP-seq, chromatin was crosslinked with 1 % formaldehyde (Sigma) by the addition of 1 ml 10x crosslinking buffer (50 mM HEPES, 1 mM EDTA, 0.5 mM EGTA, 100 mM NaCl, 10 % formaldehyde) to 10E7 cells in 9 ml of media and incubation at room temperature for 10 minutes. Crosslinking was quenched with 130 mM glycine, and cells were washed with cold PBS before snap freezing pelleted cells. Fixed material was stored at -80 ºC for less than 12 months. Chromatin immunoprecipitation was performed using Agarose ChIP Assay Kit (Merck Millipore). Briefly, 10E7 cells were lysed by incubation on ice with 130 µl lysis buffer for 15 minutes. Lysed cells were transferred to Covaris microtubes and sonicated on the Covaris S220 (Duty cycle: 2 %, Intensity: 3, Cycles per burst: 200, Power mode: Frequency sweeping, Duration: 480 sec, Temp.: 6 ºC) to generate 200-400 bp fragments. Insoluble material was removed by centrifugation (15,000 rcf, 15 min, 4 ºC) and soluble material was diluted to 4 ml with dilution buffer. Immunoprecipitation was performed by incubation of 2 ml diluted chromatin (equivalent to 5x10E6 input cells) with antibodies for Gata-1 (7 µg ab11852, lot: GR290167-7; AbCam), H3K4me3 (1 µl 07-473, lot: 2664283; Millipore), H3K27ac (0.3 µg ab4729, lot: GR3205523-1; AbCam), or CTCF (10 µl 07-729, lot: 2836929; Millipore) overnight. Chromatin binding to Protein A/agarose slurry, washes and elution were performed according to the manufacturer’s instructions.
DNA was purified by phenol-chloroform extraction with PhaseLock tubes (5Prime) and ethanol precipitation with NaOAc, and 2 µl GlycoBlue (Invitrogen). ChIP enrichment was determined by RT-qPCR
NEBNext Ultra II DNA Library Prep kit for Illumina (New England Biolabs).

value: Male

value: Erythroid

tag: target

value: Input

tag: chip antibody


title: KMS11_EtOH_rep1


title: Erythroid cells, Input_Don002_Ery_d13_rep1


title: Erythroid cells, Input_Don001_Ery_d13_rep2

value: Female


title: Erythroid cells, H3K4me3_Don003_Ery_d13_rep1


title: Erythroid cells, Input_Don001_Ery_d13_rep1


title: Erythroid cells, Input_Don003_Ery_d13_rep2


title: Erythroid cells, H3K27ac_Don003_Ery_d13_rep2


title: Erythroid cells, H3K4me3_Don002_Ery_d13_rep1


title: Erythroid cells, GATA1_Don003_Ery_d13_rep1


title: Erythroid cells, H3K4me3_Don001_Ery_d13_rep1


title: H929_EtOH_rep2


title: Erythroid cells, GATA1_Don001_Ery_d13_rep1


title: Erythroid cells, GATA1_Don002_Ery_d13_rep1


title: Erythroid cells, CTCF_Don003_Ery_d13_rep1

value: CTCF


title: Erythroid cells, CTCF_Don002_Ery_d13_rep1


title: Erythroid cells, H3K27ac_Don002_Ery_d13_rep2


title: Erythroid cells, CTCF_Don001_Ery_d13_rep1


title: Erythroid cells, Input_Don002_Ery_d13_rep2


title: Donor 4 tumour

tag: tissue

value: Lung

value: Donor 4

value: tumour


title: LCL

city: Oxford

first: Ron

last: Schwessinger

address: MRC WIMM, John Radcliffe Hospital, Headington

department: MRC Weatherall Institute if Molecular Medicine

institute: University of Oxford

description: DpnII digested 3C library, enriched for fragments of interest by oligonucleotide pulldown

data_processing:
Following the data processing described in (Oudelaar and Beagrie et al. BioRxiv 2019)
CCseqBasic pipeline (https://github.com/Hughes-Genome-Group/CCseqBasicF/releases)
Custom scripts (https://github.com/oudelaar/TiledC)
ICE normalization (Imakaev et al. Nature Methods 2012) using HiCPro (Servant et al., Genome Biology, 2015)
Genome_build: hg19
Supplementary_files_format_and_content: Sparse matrix format (bin1  bin2  ICE normalized interaction count) and bed file for bin number annotation.

growth_protocol: Human GM12878 lymphocyte cell line, were obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research and cultured in RPMI 1640 supplemented with 15% FBS, 2mM L-Glutamine and 100U/ml Pen-Strep at 37 °C in a 5% CO2 incubator. K562 cells were supplied by the WIMM transgenics facility. Cells were maintained in RPMI 1640 media supplemented with 10 % FCS at 37 ºC in a 5% CO2 incubator. Both cell types were fixed and processed using the same protocol. Cells were resuspended at 1x106 cells per ml and fixed at room temperature with 2% v/v formaldehyde for 10 minutes. Fixation was quenched with 120 mM glycine. Cells were washed with ice cold PBS. Cells resuspended in cold lysis buffer (10 mM Tris, 10 mM NaCl, 0.2% Igepal CA-630 and complete proteinase inhibitor (Roche)) and snap frozen to −80 °C.

extract_protocol:
3C Libraries were generated according to the NG Capture-C protocol (Davies et al. 2016). Briefly, cells were crosslinked with 2% formaldehyde (10 minutes, room temperature); quenched with cold glycine; washed in phosphate buffered saline; resuspended in cold lysis buffer (tris 10mM, NaCl 10mM, NP40 0.2%, complete proteinase inhibitor (Roche)) and snap frozen to -80. Cells were thawed on ice, washed in milliq dH2O and Dounce homogenised on ice (x 40 strokes). Cells were then resuspended with 0.25% SDS and restriction enzyme buffer and incubated at 37C for 1h at 1400rpm on a Comfort Thermomixer (Eppendorf) followed by a further incubation of 1h following the addition of triton X100 (final concentration 1.67%). An overnight digestion was performed using Dpn II (500U /ml (NEB) at 37C / 1400 rpm). The digested chromatin was ligated overnight (Fermentas HC Ligase final concentration 10U/ml) at 16 degrees at 1400 rpm on the Thermomixer. The samples were then decrosslinked overnight at 65C with Proteinase K (Roche) followed by a 30 min incubation at 37C with RNAse (Roche). Phenol/Chloroform extraction was then performed followed by an Ethanol precipitation and a wash with 70% Ethanol. Digestion efficiencys were assessed by gel electrophoresis (1% agarose) and RT-PCR (Taqman), which showed digestion efficiencies in excess of 70%. DNA content of the Dpn II 3C libraries were quantitated using a Qubit fluorometer (Life technologies)
5-10ug of each library was sheared using a Covaris S2 in milliq dH2O. Covaris settings used were: duty cycle 10%, Intensity 5, Cycles/burst 200, Time 6 cycles of 60seconds, Set Mode Frequency sweeping Temperature 4 to 7 degrees. Following shearing DNA was purified using AMPureXP beads (Agencourt) and DNA quality assessed on a Bioanalyser 2100 using a DNA High Sensitivity Chip (Agilent). DNA end repair and adapter ligation was performed using the NEB Next or NEB Ultra DNA sample preparation reagent kits, depending on the amount of DNA available, using the standard protocol. Biotinylated capture oligonucleotides were designed to the ends of the viewpoint fragments. Where possible 1-2ug of each adapter ligated library were hybridized with the biotinylated capture oligonucleotides, using the Nimblegen SeqCap reagents and an adapted protocol. The quality of the resultant captured library was assessed by Agilent tapestation or bioanalyser (D1000). The resulting libraries were sequenced using Illumina Nextseq 500 (150 bp paired-end reads)

value: B cell derived

tag: day of differentiation

tag: Sex


title: LCL_CTCF

data_processing:
Library Strategy: NG Capture-C
CCseqBasic pipeline (https://github.com/Hughes-Genome-Group/CCseqBasicF/releases)
Adaptor Removal: Trim Galore
Fragment reconstruction into a single read: Flash
In silico restriction enzyme digestion of FASTQ file (dpnIIPE.pl)
Alignment: Bowtie 2
Processing: Removal of PCR duplicates; Parsing of informative reads and mapping to restriction enzyme fragments (CCanalyser2.pl)
Processing: Combining data from multiple replicates (custom scripts)
Processing: Removal of ploidy regions and off target capture (custom scripts)
Genome_build: hg19
Supplementary_files_format_and_content: custom format (chr start stop interactions viewpoint)


title: K562_CTCF


title: K562_intra_domain


title: LCL_intra_domain


title: K562


title: Erythroid cells, H3K27ac_Don001_Ery_d13_rep2

tag: individual


title: ATAC_Don003_Ery_d7_P1_rep2

description: Genome-wide library of transposed fragments

data_processing:
Mapping : bowtie -m 2 --maxIns 350, mm9
For un-mapping reads : trimming adaptors trim_galore -- length 10, combining overlapping R1-R2 reads : flash -m 9 -x 0.125
Combining trimmed+flashed and originally mapped reads, mapping again with  bowtie -m 2 --maxIns 350
Removing read pairs overlapping Blacklisted regions
Removing duplicates : samtools rmdup
Reconstructing sequenced fragments from R1+R2 read pairs ( bedtools bedpe | cut -f 1,2,6) - for visualisation
Pileup of fragments (bedtools genomecov -counts)
Generating bigwig tracks (deeptools bamCoverage --bam ${bamname}.bam -o ${bamname}.bw --binSize 10 --normalizeUsingRPKM --minMappingQuality 1)
Genome_build: hg19
Supplementary_files_format_and_content: bigWig : FPKM normalised coverage of filtered fragments (reconstructed, duplicate-filtered fragments)

growth_protocol: Fresh whole blood collected from three healthy donors (two males, one female) using EDTA Vacuettes (Becton Dickson) or 5 ml leukocyte cones (NHS Blood & Transport). Whole cell counts were performed on a Pentra ES60 (Horiba) for donor blood to ensure clinically healthy red blood cell counts. Blood was diluted with PBS and overlaid onto Histopaque-1077 (Sigma) and centrifuged for 30 min at 630 rcf (no brake). Peripheral Blood Mononuclear Cells (PBMCs) were washed in PBS and MACS buffer (PBS, 2 µM EDTA, 0.5% BSA) and stained with Human CD34 Microbead kit (Miltenyi Biotec) following the manufacturer’s instruction for 30 minutes (4 ºC) before being passed successively through two LS Columns (Miltenyi Biotec) with three MACs buffer washes. Counting of cells was performed on a Luna FL (Logos) after staining with acridine orange (AO) and propidium iodide (PI). CD34+ cells were either stored in freezing buffer (90% FBS, 10% DMSO) or resuspended in growth media for differentiation. Protocol 1 (P1) was performed as per Mettananda et al. 2018 (PMID: 28871148): CD34+ cells were differentiated into erythroid cells over 21 days using a two-phase liquid culture system which used StemSpan SFEM II (Stemcell Technologies). Phase 1 medium was supplemented with stem cell factor, interleukin-3, human recombinant erythropoietin (EPO) (0.5 U/ml) and cholesterol-rich lipids. Phase 2 medium was similar to phase 1 medium except for addition of iron saturated holotransferrin and higher concentration of EPO (3 U/ml). Protocol 2 (P2) was performed as per Palii et al. 2011 (PMID: 21785407) and Palii et al 2019 (PMID: 30880026). The first step (Day0 to Day11) consists of cultivating CD34+ cells in serum-free IMDM medium supplemented with 1% penicillin/streptomycin, 4x10-3 ML glutamine, 40 ug/ml inositol, 10 ug/ml folic acid, 1.6x10-4 M monothioglycerol, 90 ng/ml ferrous nitrate, 900 ng/ml ferrous sulfate, 20% albumin-insulin-transferrin (BIT), also containing the following cytokines: 10-6 M hydrocortisone (HC), 100 ng/ml stem cell factor (SCF), 5 ng/ml interleukin 3 (IL-3) and 3 IU/ml erythropoietin (EPO) for 8 days followed by 3 days in supplemented IMDM medium containing only SCF and EPO. For the second step (Day12 to Day14), cells were co-cultured on a layer of stromal MS-5 cells in the supplemented IMDM medium containing only EPO. For the third step (Day15 to Day18), cells were co-cultured on a layer of MS-5 cells in the supplemented IMDM medium with no cytokines. For the fourth step (Day19 to Day24), cells were co-cultured on a layer of MS-5 cells in the supplemented IMDM medium in the presence of 10% fetal bovine serum.

extract_protocol:
Assay for transposition of active chromatin sequencing (ATAC-Seq) was performed as previously published (Buenrostro, 2013) on single cell suspensions. 60000-80000 cells were used per biological replicate. Cells were lysed and nuclei were isolated prior to transposition with Tn5 transposase (Nextera, Illumina) for 30 minutes at 37°C. DNA was purified using a MinElute kit (Qiagen).
Libraries were amplified and barcoded using the NEBNext 2xMastermix (NEB) and the custom primers as published in Buenrostro et al., 2013.ATAC-Seq libraries profiles were visualized using D1000 tape on the Tapestation (Agilent). The libraries were quantified using the universal library quantification kit (KAPA Biosystems).

value: Day 7

tag: differentiation protocol


title: ATAC_Don003_Ery_d7_P1_rep1

tag: gender


title: ATAC_Don003_Ery_d16_P1_rep1

value: Day 16


title: ATAC_Don003_Ery_d16_P1_rep2


title: ATAC_Don003_Ery_d13_P1_rep4

value: Day 13


title: ATAC_Don003_Ery_d13_P1_rep3


title: ATAC_Don003_Ery_d13_P1_rep2


title: ATAC_Don003_Ery_d13_P1_rep1


title: ATAC_Don003_Ery_d10_P1_rep4

value: Day 10


title: ATAC_Don002_Ery_d16_P1_rep4


title: ATAC_Don002_Ery_d7_P1_rep1


title: ATAC_Don003_Ery_d10_P1_rep2


title: ATAC_Don002_Ery_d7_P1_rep2


title: ATAC_Don002_Ery_d16_P2_rep1


title: ATAC_Don003_Ery_d10_P1_rep3


title: ATAC_Don002_Ery_d16_P1_rep3


title: ATAC_Don003_Ery_d10_P1_rep1


title: ATAC_Don003_Ery_d16_P1_rep4


title: ATAC_Don002_Ery_d16_P1_rep2


title: ATAC_Don002_Ery_d13_P1_rep1


title: ATAC_Don002_Ery_d13_P1_rep4


title: ATAC_Don002_Ery_d13_P1_rep2


title: ATAC_Don002_Ery_d13_P1_rep3


title: ATAC_Don003_Ery_d16_P1_rep3


title: ATAC_Don002_Ery_d12_P2_rep1

value: Day 12


title: ATAC_Don002_Ery_d12_P2_rep2


title: ATAC_Don002_Ery_d10_P2_rep2


title: ATAC_Don002_Ery_d10_P1_rep4


title: ATAC_Don002_Ery_d10_P2_rep1


title: ATAC_Don002_Ery_d10_P1_rep1


title: ATAC_Don002_Ery_d10_P1_rep3


title: ATAC_Don002_Ery_d16_P1_rep1


title: ATAC_Don002_Ery_d0_rep1

value: Day 0


title: ATAC_Don001_Ery_d8_P2_rep1

value: Day 8


title: ATAC_Don001_Ery_d7_P1_rep2


title: ATAC_Don002_Ery_d10_P1_rep2


title: ATAC_Don001_Ery_d16_P2_rep1


title: ATAC_Don001_Ery_d7_P1_rep1


title: ATAC_Don001_Ery_d16_P1_rep2


title: ATAC_Don001_Ery_d16_P2_rep2


title: ATAC_Don001_Ery_d16_P1_rep3


title: ATAC_Don001_Ery_d13_P1_rep3


title: ATAC_Don001_Ery_d16_P1_rep4


title: ATAC_Don001_Ery_d16_P1_rep1


title: ATAC_Don001_Ery_d13_P1_rep1


title: ATAC_Don001_Ery_d10_P1_rep4


title: ATAC_Don001_Ery_d13_P1_rep2


title: ATAC_Don001_Ery_d10_P2_rep2


title: ATAC_Don001_Ery_d10_P1_rep1


title: ATAC_Don001_Ery_d10_P1_rep3


title: ATAC_Don001_Ery_d10_P2_rep1


title: ATAC_Don001_Ery_d12_P2_rep1


title: ATAC_Don001_Ery_d10_P1_rep2


title: REH Spleen rep2

city: Bearsden

first: Pawel

last: Herzyk

address: Wolfson Wohl Cancer Research Centre, Garscube Estate

department: College of Medical, Veterinary and Life Sciences

institute: University of Glasgow

description: Xenotransplants

data_processing:
Fastq files were generated with bcl2fastq v.1.8.4 Illumina software
The raw fastq files containing paired-end 2 x 75bp reads were pre-processed to trim the 3’ end adapter with Cutadapt (version 1.5) and to trim the very low quality reads using Sickle (version 0.940) software using generous quality threshold -q 10. Only read pairs containing ≥54 bases were kept.
Transcript expression quantification was performed using Kallisto (version 0.42.4) software against combined human and mouse transcriptomes, Ensembl GRCh38.79 and GRCm38.78, respectively, in order to remove the possible mouse RNA contamination.
Read counts related to human transcripts were collected, rounded, and summarized into gene specific read counts. These were then used in downstream gene-based differential expression analysis using DESeq2 R-package.
The normalised gene-expression estimates were calculated with regularised logarithm transformation using rlog function within DESeq2 R-package. These were used in downstream analysis of metabolic pathways enrichment using single sample gene set enrichment analysis (ssGSEA).
Genome_build: Ensembl GRCh38.79 and GRCm38.78
Supplementary_files_format_and_content: Tab delimited (.tsv) sample specific kallisto output files generated with kallisto v.0.42.4 used against combined human and mouse transcriptomes, Ensembl GRCh38.79 and GRCm38.78, respectively. The files present transcript-specific length, effectove length, estimated counts and tpm.
Supplementary_files_format_and_content: Coma delimited (.csv) matrix representing human gene read counts. The Kallisto-generated estimated read counts related to human transcripts were extracted from the kallisto output, rounded, and summarized into gene-specific read counts. These were generated for the subsequent use in downstream gene-based differential expression analysis with DESeq2 R-package
Supplementary_files_format_and_content: Coma delimited (.csv) matrices representing normalised human gene expression estimates calculated with rlog function within DESeq2 software. These were generated for the subsequent use in downstream analysis of metabolic pathways enrichment with single sample gene set enrichment analysis (ssGSEA).

source_name: acute lymphoblastic leukaemia blast cells

growth_protocol: REH [t(12;21) ETV6-RUNX1 (TEL-AML1)]  cell line was bought from ATCC. REH cells were maintained in Glutamax 25mM glucose Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% (vol/vol) FBS (Life Technologies), 1% penicillin/streptomycin solution. Cells were cultured at 37°C at 21 % oxygen in a 5% CO2 incubator and were regularly monitored for mycoplasma contamination. All cell culture reagents were purchased from Thermo Fisher Scientific (Life Technologies).

extract_protocol:
RNA was extracted from cells resuspended and lysed in TRIzol according to manufacturer’s instructions, and underwent DNase treatment using an RNase-free DNase kit (Qiagen). RNA quality was assessed with the RNA Nano Chip kit (Agilent) on an Agilent Bioanalyser 2100.
RNA libraries were prepared from totalRNA using TruSeq Stranded mRNA Library Prep kit and standard Illumina protocols

treatment_protocol: JAX NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG; Charles River Laboratories, Harlow, United Kingdom) mice were kept in sterile isolators with autoclaved food, bedding, and water. Xenotransplants were performed in five 6-10 week old mice. At the end of experiment, mice were sacrificed by overdose of pentobarbital (IP) and cells were collected from bone marrow, spleen and leptomeninges. For RNA sequencing leukaemic cells were purified using a Ficoll gradient (Lymphoprep, Stemcell) following the supplier instructions. Purity was determined using flow cytometry. Cells were dry pelleted and snap frozen for further use. RNA was combined from all 5 mice for RNA sequencing. The experiment was repeated on 3 independent occasions (rep 1-3). Spleen rep 3 failed quality control and is not shown here.

value: ALL blasts retrieved from spleen

value: REH (TEL-AML1) leukaemic cells

tag: origin site

value: cells retrieved from spleen


title: REH Brain rep3

description: Xenotransplants

value: ALL blasts retrieved from brain

value: cells retrieved from brain


title: REH Spleen rep1

description: Xenotransplants


title: REH Brain rep2

description: Xenotransplants


title: REH Brain rep1

description: Xenotransplants


title: SEM Spleen rep2

description: Xenotransplants

data_processing:
Fastq files were generated with bcl2fastq v.1.8.4 Illumina software
The raw fastq files containing paired-end 2 x 75bp reads were pre-processed to trim the 3’ end adapter with Cutadapt (version 1.5) and to trim the very low quality reads using Sickle (version 0.940) software using generous quality threshold -q 10. Only read pairs containing ≥54 bases were kept.
Transcript expression quantification was performed using Kallisto (version 0.42.4) software against combined human and mouse transcriptomes, Ensembl GRCh38.79 and GRCm38.78, respectively, in order to remove the possible mouse RNA contamination.
Read counts related to human transcripts were collected, rounded, and summarized into gene specific read counts. These were then used in downstream gene-based differential expression analysis using DESeq2 R-package.
The normalised gene-expression estimates were calculated with regularised logarithm transformation using rlog function within DESeq2 R-package. These were used in downstream analysis of metabolic pathways enrichment using single sample gene set enrichment analysis (ssGSEA).
Genome_build: Ensembl GRCh38.79 and GRCm38.78
Supplementary_files_format_and_content: Tab delimited (.tsv) sample specific abundance files generated with kallisto v.0.42.4 used against combined human and mouse transcriptomes, Ensembl GRCh38.79 and GRCm38.78, respectively. The files present transcript-specific length, effectove length, estimated counts and tpm.
Supplementary_files_format_and_content: Coma delimited (.csv) matrix representing human gene read counts. The Kallisto-generated estimated read counts related to human transcripts were extracted from the kallisto output, rounded, and summarized into gene-specific read counts. These were generated for the subsequent use in downstream gene-based differential expression analysis with DESeq2 R-package.
Supplementary_files_format_and_content: Coma delimited (.csv) matrix representing normalised human gene expression estimates calculated with rlog function within DESeq2 software. These were generated for the subsequent use in downstream analysis of metabolic pathways enrichment with single sample gene set enrichment analysis (ssGSEA).

growth_protocol: SEM [t(4;11) KMT2A-AFF1 (MLL-AF4)] cell lines were bought from ATCC. SEM cells were maintained in Glutamax 25mM glucose Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% (vol/vol) FBS (Life Technologies), 1% penicillin/streptomycin solution. Cells were cultured at 37°C at 21 % oxygen in a 5% CO2 incubator and were regularly monitored for mycoplasma contamination. All cell culture reagents were purchased from Thermo Fisher Scientific (Life Technologies).

treatment_protocol: Xenotransplants were performed in five 6-10 week old mice. At the end of experiment, mice were sacrificed by overdose of pentobarbital (IP) and cells were collected from bone marrow, spleen and leptomeninges. For RNA sequencing leukaemic cells were purified using a Ficoll gradient (Lymphoprep, Stemcell) following the supplier instructions. Purity was determined using flow cytometry. Cells were dry pelleted and snap frozen for further use. RNA was combined from all 5 mice for RNA sequencing. The experiment was repeated on 2 independent occasions (rep 1-2).

value: SEM (MLL-AF4) leukaemic cells


title: ATAC_Don001_Ery_d13_P1_rep4

tag: cell type

value: Erythroid

value: Female


title: ATAC_Don001_Ery_d12_P2_rep2


title: SEM Spleen rep1

description: Xenotransplants


title: SEM Brain rep2

description: Xenotransplants


title: SEM Brain rep1

description: Xenotransplants


title: BaF3_JAK2VF_Input _1 (Input rep 1)

city: Planegg

first: Sung-Huan

last: Yu

address: Am Klopferspitz 18

country: Germany

institute: Max Planck Institute

data_processing:
Sequencing reads were trimmed by fastq_quality_trimmer (Quality threshold = 20, Minimum length = 1) and adaptors are removed by Trimgalore (default)
Reads are mapped to the Ensembl gene annotation and the mouse genome assembly GRCm38 using segemehl (default setting)
MACS2 was used for peaks calling (narrow peak calling, cutoff of q-value is 0.01)
IGV-viewer was utilized to visualize the peaks
Genome_build: GRCm38
Supplementary_files_format_and_content: BigWig files were generated by using MACS2. They can be loaded into genome browser and the values represent the normalized expression values.
Supplementary_files_format_and_content: XLS files are the peak files generated by using MACS2. They contain positions, fold changes, -log10p-values and -log10q-values at peak summit
Supplementary_files_format_and_content: BED files are peak files generated by using MACS2. They can be loaded to genome browser and the scores represent -log10q-value at peak summit

source_name: BaF3 Jak2V617F

growth_protocol: Cells were grown in RPMI1640 containing 10% FBS and 1mM Sodium pyruvate

extract_protocol:
DNAextraction kit according to the Manufacturer’s protocol (Macherey Nagel)
Magnetic Isolation Module

treatment_protocol: Untreated

value: proBcells derived BaF3 cells

tag: antibody


title: BaF3_JAK2VF_Input _3 (Input rep 3)


title: BaF3_JAK2VF_Input _2 (Input rep 2)


title: BaF3_JAK2VF_YBX1 _3 (ChIP rep 3)


title: BaF3_JAK2VF_YBX1 _2 (ChIP rep 2)


title: BaF3_JAK2VF_YBX1 _1 (ChIP rep 1)


title: Mouse Adh 1

source_name: POD2 mice

value: abdominal adhesion


title: Mouse Adh 2

source_name: POD7 mice


title: KO_Iso_CD8_Spleen [1041287]

city: Tarrytown

first: Asiel

middle: Arturo

last: Benitez

state: New York

address: 777 Old Saw Mill River Rd, 92-516A

department: Immunology & Inflammation

institute: Regeneron Pharmaceuticals, Inc

data_processing:
The cell suspensions were loaded on a Chromium Single Cell Instrument (10X Genomics) and RNA libraries were prepared using Chromium Single Cell 3’ Library, Gel Beads & Multiplex Kit (10X Genomics).
Genome_build: GRCm38
Supplementary_files_format_and_content: tab-delimited text file include umi counts for each sample

extract_protocol:
Single cell suspensions of MC38 tumors were sorted for CD45+ or CD8+ and collected into tubes containing PBS with 0.04% BSA.
The cell suspensions were loaded on a Chromium Single Cell Instrument (10X Genomics) and RNA libraries were prepared using Chromium Single Cell 3’ Library, Gel Beads & Multiplex Kit (10X Genomics).

tag: strain background

tag: genotype/variation

value: Aire-/-

tag: treatment

value: Isotype Control

value: spleen

tag: celltype


title: WT_PD1_CD8_Spleen [1041286]

value: Aire+/+


title: KO_PD1_CD45_Spleen [1041284]


title: KO_Iso_CD45_Spleen [1041283]


title: WT_Iso_CD8_Spleen [1041285]


title: WT_003

city: Los Angeles

first: Georges Doumet

last: HELOU

state: California

address: 1450 Biggy St, NRT5505, Keck School of Medicine

department: Molecular Microbiology and Immunology

institute: University of Southern California

data_processing:
Illumina Casava1.7 software used for basecalling, algorithm: bcl2fastq-v2.17.1.14
RNAseq data were analyzed using Partek® Flow® software, version 7.0 Copyright ©; 2018
Raw reads were first trimmed based on Quality Score (min quality level 20, trim from both ends, min read length 25)
Trimmed reads were aligned to mm10 with Gencode M19 as guidance using STAR 2.5.3a
Aligned reads were quantified to Gencode M16 genes using Partek E/M. Normalized reads counts were tested for differential expression using Partek's GSA algorithm.
Genome_build: mm10

source_name: Lungs

extract_protocol:
Total RNA was isolated using MicroRNAeasy (Qiagen). 10ng of input RNA was used to produce cDNA for downstream library preparation.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: Freshly sorted ILC2s after three intranasal administrations of rm-IL-33 (0.5 µg per mouse), were incubated (5 x 104 per mL) with rm-IL-2 (10 ng.mL-1) and rm-IL-7 (10 ng.mL-1) for 24 h.

tag: strain

value: BALB/cByJ

tag: genotype

value: WT

tag: age

value: 8 weeks

value: Type-2 innate lymphoid cells (ILC2s)


title: WT_001


title: PD-1 KO_002

value: PD-1 KO


title: WT_002


title: PD-1 KO_003


title: PD-1 KO_001


title: WT_Iso_CD45_Spleen [1041281]


title: KO_PD1_CD8_Tum [1041198]

value: tumor


title: KO_Iso_CD8_Tum [1041197]


title: ESCs, RA1

city: Durham

first: Kathleen

last: McCann

address: 111 TW Alexander Dr

institute: National Institute of Environmental Health Sciences

description: mESCs untreated T=0 #1

data_processing: Raw data were normalized to the geometric mean of the positive control probes and to the geometric mean of snoRNAs that remain unchanged as determined by percent coefficient of variation (% CV) < 20 using nSolver Analysis Software 3.0.

source_name: RA Treated ESCs

extract_protocol: RNA was isolated from cells using Trizol, Dnase treated with Dnase I and further purified using Qiagen Rneasy mini kits. RNA concentration and purity was determined using a Qubit and Nanodrop.

value: ESCs

value: RA


title: WT_Iso_CD8_Tum [1041195]


title: KO_PD1_CD8_Spleen [1041288]


title: KO_Iso_CD45_Tum [1041189]


title: WT_Iso_CD45_Tum [1041187]


title: LLC+Th9 Coculture rep3

city: bad nauheim

first: Stefan

last: Günther

address: ludwigtr. 43

institute: MPI for heart and lung research

description:
LCC_Th9_3
th09_counts.matrix.norm_anno

data_processing:
Reaper version 13-100 was employed to trim reads after a quality drop below a mean of Q20 in a window of 10 nucleotides. Reads between 30 and 150 nucleotides only were cleared for further analysis.
Trimmed and filtered reads were aligned versus the Ensembl mouse genome version mm10 (GRCm38) using STAR 2.4.0a with the parameter “--outFilterMismatchNoverLmax 0.1” to increase the maximum ratio of mismatches to mapped length to 10%.
The number of reads aligning to genes was counted with featureCounts 1.4.5-p1 tool from the Subread package. Only reads mapping at least partially inside exons were admitted and aggregated per gene. Reads that are overlapping multiple genes or aligning to multiple regions were excluded.
Differentially expressed genes were identified using DESeq2 version 1.62. Only genes with a minimum fold change of +- 1.5 (log2 +-0.59), a maximum Benjamini-Hochberg corrected p-value of 0.05, and a minimum combined mean of 5 reads were deemed to be significantly differentially expressed.
The Ensemble annotation was enriched with UniProt data (release 06.06.2014) based on Ensembl gene identifiers.
Genome_build: mm10
Supplementary_files_format_and_content: library-size normalized counts

source_name: Lewis lung carcinoma cells

growth_protocol: Artificially generated T cell subsets were co-cultured for 24h in direct contact with LLC1 cells at 1:1 ratio. Afterwards, CD4+ cells were sorted from the co-culture and RNA was isolated from remaining mouse cancer cells

extract_protocol:
RNA was isolated from LLC1 cells after sorting using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion.
1µg of total RNA was used as input for SMARTer Stranded Total RNA Sample Prep Kit - HI Mammalian (Clontech).

value: LLC+Th9 Coculture


title: LLC+Th9 Coculture rep1

description:
LCC_Th9_1
th09_counts.matrix.norm_anno


title: LLC+Th9 Coculture rep2

description:
LCC_Th9_2
th09_counts.matrix.norm_anno


title: LLC+Th17 Coculture rep3

description:
LCC_Th17_3
th17_counts.matrix.norm_anno

value: LLC+Th17 Coculture


title: LLC+Th17 Coculture rep1

description:
LCC_Th17_1
th17_counts.matrix.norm_anno


title: LLC+Th17 Coculture rep2

description:
LCC_Th17_2
th17_counts.matrix.norm_anno


title: LLC+Th0 Coculture rep3

description:
LCC_Th0_3
th09_counts.matrix.norm_anno, th17_counts.matrix.norm_anno

value: LLC+Th0 Coculture


title: LLC+Th0 Coculture rep1

description:
LCC_Th0_1
th09_counts.matrix.norm_anno, th17_counts.matrix.norm_anno


title: WT_PD1_CD45_Spleen [1041282]


title: Input

city: Philadelphia

first: Jessica

last: Pfleger

state: PA

address: 3500 North Broad Street

institute: Temple University

description: Includes Drosophila chromatin spike-in

data_processing:
sequence analysis: The 75-nt sequence reads generated by Illumina sequencing (using NextSeq  500) are mapped to the genome using the BWA algorithm with default settings. Alignment information for each read is stored in the BAM format. Only reads that pass Illumina’s purity filter, align with no more than 2 mismatches, and map uniquely to the genome are used in the subsequent analysis. In addition, unless stated otherwise, duplicate reads (“PCR duplicates”) are removed.
determination of fragment density: Since the 5´-ends of the aligned reads (= “tags”) represent the end of ChIP/IP-fragments, the tags are extended in silico (using Active Motif software) at their 3´- ends to a length of 150-250 bp, depending on the average fragment length in the size selected library (normally 200 bp). To identify the density of fragments (extended tags) along the genome, the genome is divided into 32-nt bins and the number of fragments in each bin is determined. This information (“signal map”; histogram of fragment densities) is stored in a bigWig file, which can be visualized in genome browsers (see Section V.). bigWig files also provide the peak metrics in the Active Motif analysis program described below.
peak finding: The generic term “Interval” is used to describe genomic regions with local  enrichments in tag numbers. Intervals are defined by the chromosome number and a start and end coordinate. The two main peak callers used at Active Motif are MACS (Zhang et al., Genome Biology 2008, 9:R137) and SICER (Zang et al., Bioinformatics 25, 1952-1958, 2009). MACS is suitable to identify the binding sites of transcription factors that bind to discrete sites (often containing a consensus DNA sequence) as well as many active histone marks and methyl-C enriched regions, while SICER is used to study proteins that bind to extended regions in the genome (such as repressive histone marks or RNA polymerase II). Both methods look for significant enrichments in the ChIP/IP data file when compared to the Input data file (~ random background).
Spike-in Adjustment: The number of test tags are adjusted (again by down-sampling) by a factor that would result in the same number of spikein Drosophila tags for each sample. Spike-in adjustment can be useful for rare assays where standard normalization does not result in the expected global differences in enrichments between test samples.
merged region analysis: To compare peak metrics between 2 or more samples, overlapping Intervals are grouped into “Merged Regions”, which are defined by the start coordinate of the most upstream Interval and the end coordinate of the most downstream Interval (= union of overlapping Intervals; “merged peaks”). In locations where only one sample has an Interval, this Interval defines the Merged Region. The use of Merged Regions is necessary because the locations and lengths of Intervals are rarely exactly the same when comparing different samples.
annotation: After defining the Intervals and Merged Regions, their genomic locations along with their proximities to gene annotations and other genomic features are determined and presented in Excel spreadsheets. In addition, average and peak (i.e. at “summit”) fragment densities within Intervals and Merged Regions are compiled.
Genome_build: mm10
Supplementary_files_format_and_content: bigWig files show peak shapes in the form of a signal histogram and can be visualized in the UCSC browser
Supplementary_files_format_and_content: Excel files show Merged Regions, which are genomic regions containing 1 or multiple overlapping intervals

source_name: Heart Tissue

extract_protocol:
After 7 days, hearts were removed, snap frozen, and shipped to Active Motif (a pool of 3 hearts per condition).
Libraries were constructed by Active Motif (https://www.activemotif.com/).

treatment_protocol: 12 wk old, wild type C57BL/6 male mice were subjected to vehicle injection/sham operation, isoproterenol injection (subcutaneous, 3 mg/kg/day), or transverse aortic constriction (TAC) surgery for 7 days.

value: heart

value: Wild Type

tag: surgical procedure

value: DNA pooled from all samples

tag: days post surgery

value: none (input)

value: male


title: LLC+Th0 Coculture rep2

description:
LCC_Th0_2
th09_counts.matrix.norm_anno, th17_counts.matrix.norm_anno


title: WT_PD1_CD8_Tum [1041196]

value: Aire+/+

tag: tissue


title: FoxO1 ChIP-Seq Veh/Sham

description: Includes Drosophila chromatin spike-in

data_processing:
sequence analysis: The 75-nt sequence reads generated by Illumina sequencing (using NextSeq  500) are mapped to the genome using the BWA algorithm with default settings. Alignment information for each read is stored in the BAM format. Only reads that pass Illumina’s purity filter, align with no more than 2 mismatches, and map uniquely to the genome are used in the subsequent analysis. In addition, unless stated otherwise, duplicate reads (“PCR duplicates”) are removed.
determination of fragment density: Since the 5´-ends of the aligned reads (= “tags”) represent the end of ChIP/IP-fragments, the tags are extended in silico (using Active Motif software) at their 3´- ends to a length of 150-250 bp, depending on the average fragment length in the size selected library (normally 200 bp). To identify the density of fragments (extended tags) along the genome, the genome is divided into 32-nt bins and the number of fragments in each bin is determined. This information (“signal map”; histogram of fragment densities) is stored in a bigWig file, which can be visualized in genome browsers (see Section V.). bigWig files also provide the peak metrics in the Active Motif analysis program described below.
peak finding: The generic term “Interval” is used to describe genomic regions with local  enrichments in tag numbers. Intervals are defined by the chromosome number and a start and end coordinate. The two main peak callers used at Active Motif are MACS (Zhang et al., Genome Biology 2008, 9:R137) and SICER (Zang et al., Bioinformatics 25, 1952-1958, 2009). MACS is suitable to identify the binding sites of transcription factors that bind to discrete sites (often containing a consensus DNA sequence) as well as many active histone marks and methyl-C enriched regions, while SICER is used to study proteins that bind to extended regions in the genome (such as repressive histone marks or RNA polymerase II). Both methods look for significant enrichments in the ChIP/IP data file when compared to the Input data file (~ random background).
Spike-in Adjustment: The number of test tags were adjusted (again by down-sampling) by a factor that would result in the same number of spikein Drosophila tags for each sample. Spike-in adjustment can be useful for rare assays where standard normalization does not result in the expected global differences in enrichments between test samples.
merged region analysis: To compare peak metrics between 2 or more samples, overlapping Intervals are grouped into “Merged Regions”, which are defined by the start coordinate of the most upstream Interval and the end coordinate of the most downstream Interval (= union of overlapping Intervals; “merged peaks”). In locations where only one sample has an Interval, this Interval defines the Merged Region. The use of Merged Regions is necessary because the locations and lengths of Intervals are rarely exactly the same when comparing different samples.
annotation: After defining the Intervals and Merged Regions, their genomic locations along with their proximities to gene annotations and other genomic features are determined and presented in Excel spreadsheets. In addition, average and peak (i.e. at “summit”) fragment densities within Intervals and Merged Regions are compiled.
Genome_build: mm10
Supplementary_files_format_and_content: bigWig files show peak shapes in the form of a signal histogram and can be visualized in the UCSC browser
Supplementary_files_format_and_content: Excel files show Merged Regions, which are genomic regions containing 1 or multiple overlapping intervals

value: Normal Heart:12 wk old, male mice were subjected to subcutaneous vehicle injection (daily) and sham operation for 7 days

value: Anti-FoxO1 (Santa Cruz Biotechnology- sc-11350)

tag: Sex


title: FN1

city: Newark

first: Melinda

middle: K.

last: Duncan

state: DE

address: 327 Wolf Hall

department: Biological Sciences

institute: University of Delaware

description: FPKM-all.csv.gz

data_processing:
Analysis was performed by DNA Link USA, Inc
Sequence quality was assessed using FASTQC
Sequences were  trimmed 5'  8bp and 3' 2bp and filtered 35bp minimum length after trimming using Cutadapt v 1.12
Trimmed reads were aligned to the reference genome using Tophat v2.1.0
Pairwise differential expression analysis was performed using Cuffdiff v2.2.1
Genome_build: Mus musculus mm10 (UCSC downlad GRCm38 and gff from NCBI/RefSeq GRCm38.p5 vertion)
Supplementary_files_format_and_content: comma-delimited w/ the following columns:gene_short_name, locus, WT1, WT2, WT3, FN1, FN2, FN3

source_name: FN, lens

extract_protocol:
By using microdissection, lenses of two month old of WT and FNcKO mice were collected, flash frozen on dry ice, and RNA was harvested using the SV Total RNA Isolation System (Invitrogen).
RNA libraries were prepared for sequencing using standard Clonthech protocols for  SMARTer® Stranded Total RNA-Seq Kit-Pico Input Mammalian
Total RNA-Seq for pico input

value: Mixed (C57BL/6, 129, FVB/N)

value: Lens

value: Adult 2 month old

value: Fibronectin conditional knockout


title: FoxO1 ChIP-Seq Iso

description: Includes Drosophila chromatin spike-in

value: Hypertrophied Heart:12 wk old, male mice were subjected to subcutaneous isoproterenol injections (3 mg/kg/day) for 7 days


title: WT3

description: FPKM-all.csv.gz

source_name: WT, lens

value: Wldtype


title: FN3

description: FPKM-all.csv.gz


title: FN2

description: FPKM-all.csv.gz


title: KO_PD1_CD45_Tum [1041190]

value: Aire-/-

value: tumor


title: WT2

description: FPKM-all.csv.gz


title: FoxO1 ChIP-Seq TAC

description: Includes Drosophila chromatin spike-in

value: Hypertrophied Heart:12 wk old, male mice were subjected to transverse aortic constriction (TAC) surgery for 7 days


title: WT1

description: FPKM-all.csv.gz


title: WT_PD1_CD45_Tum [1041188]


title: JHU083 TAM3

city: Baltimore

first: Jonathan

middle: D.

last: Powell

state: MD

address: 1650 Orleans Street

department: Oncology

institute: Johns Hopkins University

data_processing:
NextSeq 500/550 V2 Systems suite version 2.1.2, bcl2fastq2 version 2.17.1.14. Data processing Illumina NextSeq 500/550 V2 reads were trimmed and clipped for quality control based on sliding windows considering quality and length thresholds to determine the quality at which it is sufficiently low to trim the 3′-end of reads and also determines the quality at which it is sufficiently high enough to trim the 5′-end of reads. This approach finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. Quality Threshold < 30
the pre-processing operations included a quality check (FastQC), removal of adapter content (used during sequencing), quality thresholding (remove any bad quality reads)
Read quality was checked for each sample using FastQC v0.11.2.
High-quality reads were then imported into a fast splice junction mapper for RNA-Seq reads and this aligns RNA-Seq reads to genomes using the ultra high-throughput short read aligner. The mapping results were then analyzed to identify splice junctions between exons, for alignment into BAM files.
BAM files were imported into the RNA-Seq pipeline by the Transcriptomic Analysis Pipeline (proprietary pipeline designed in-house).
Reads were mapped to the reference genome. This aligns RNA-Seq reads to the genome using a short read aligner and discovers the splice sites.The resulting alignment files were used to generate a transcriptome assembly. TopHat (v 2.1.1) used
The major stages of analysis included read mapping to the latest reference genome (GRCM38), assembly of the mapped reads to identify expressed transcripts and genes, followed by quantification and comparison of the assembled transcriptomes between cells.
Gene and transcript expression between the comparing RNASeq samples were quantified and reported as FPKM (Fragments Per Kilobase of transcript per Million mapped reads) units
Genome_build: GRCM38
Supplementary_files_format_and_content: Raw counts, normalized counts

source_name: sorted tumor-associated macrophages (CD45+7AAD-CD11b+F4/80+CD8-Ly6C-Ly6G-)

growth_protocol: 1X10^5 cells 4T1 (murine breast tumor) s.c. into mammary fat pad of BALB/cJ mice

extract_protocol:
Sorted into TRIZOL (LS)
RNeasy Mini Kit (QIAGEN)
Extracted RNA were sent to Admera Health to process library construction and data analysis. Paramagnetic beads coupled with oligo d(T) are combined with total RNA to isolate poly(A)+ transcripts based on NEBNext® Poly(A) mRNA Magnetic Isolation Module manual. Prior to first strand synthesis, samples are randomly primed (5´ d(N6) 3´ [N=A,C,G,T]) and fragmented based on manufacturer’s recommendation (NEBNext® Ultra™ RNA Library Prep Kit for Illumina®). The first strand is synthesized with the Protoscript II Reverse Transcriptase with a longer extension period (40 minutes for 42◦C). All remaining steps for library construction were used according to the NEBNext® Ultra™ RNA Library Prep Kit for Illumina®. Illumina 8-nt dual-indices were used.

treatment_protocol: Sorting with FACSAria Fusion

value: Balb/cJ

tag: tumor model

value: JHU083, pro-drug of 6-Diazo-5-oxo-L-norleucine (glutamine antagonist) on day 7-13 (1mg/kg) then harvested and sorted on day 14

tag: grouping

value: B


title: JHU083 TAM5

value: 1X10^5 cells 4T1 (murine breast tumor) s.c. into mammary fat pad of BALB/cJ mice


title: JHU083 TAM4


title: JHU083 TAM2


title: Vehicle TAM5

value: vehicle (PBS) treatment then harvested and sorted on day 14

value: A


title: JHU083 TAM1


title: Vehicle TAM3


title: A_Con3

city: Changsha

first: wang

last: zhao

address: No.139 Middle Renmin Road, Changsha, Hunan

institute: Central South University

data_processing:
Illumina Casava1.7 software used for basecalling.
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to hg38(GRCh38.p5) whole genome using Tophat2 v2.1.0 with default parameters.
Fragments Per Kilobase of exon per Megabase of library size (FPKM) were calculated using cufflinks 2.1.1 following the protocol from Trapnell et al.,Nature Protocols, 2012.
Genome_build: Ensembl hg38(GRCh38.p5)
Supplementary_files_format_and_content: FPKM.txt is an text file containing the Fragments Per Kilobase of exon per Megabase of library size for each gene ID/gene
Supplementary_files_format_and_content: count.txt for every sample, which was generated by the HTSeq 0.6.1p2 software after mapping with Tophat2 2.1.0 by default parameter

source_name: HepG2 cell

extract_protocol:
To generate recombinant adenovirus vectors with APOAV expression, the pHBAd-MCMV-APOAV-GFP and adenovirus skeleton plasmid vector of pHBAd-BHG were co-infected into HEK293 cells with lipofectamine 2000 Kit following the manufacturer’s instruction. After 6 h transformation, the recombinant adenoviruses were harvested. Then, the insulin-resistant HepG2 cells were cultured and infected with the recombinant adenovirus vector for 48 h. The successful infection by recombinant adenovirus was determined, when the expression of GFP was observed by fluorescence microscopy.
RNA libraries were prepared for sequencing using standard Illumina protocols

value: negative controls

tag: cell line


title: FetalLiver2

city: Badalona

first: Carolina

last: Armengol

address: Crta Can Ruti; cami de les escoles, S/N

institute: Germans Trias i Pujol Health Research Institute

data_processing: There was preprocessing using the normalization method Funnorm, recommended for tumor samples as implemented in the minfi Bioconductor Package (v 1.24). CpGs were annotated with the closer gene. Probes containing single nucleotide polymorphisms were discarded from analyses to avoid confounding.

source_name: Fetal liver

extract_protocol: MagMAX™ DNA Multi-Sample kit was used using following manufacturer’s instructions (Thermo Fisher Scientific)

tag: gender

value: M

value: Fetal liver


title: 8D0Z_3

city: Santa Barbara

first: Lindsay

middle: J

last: Bailey-Steinitz

address: 6131 Biological Sci Bldg II

department: MCDB, NRI

institute: University of California, Santa Barbara

description: Unwounded control for 8D samples

data_processing:
Base-calling was carried out using Torrent Suite and default parameters.
Prior to alighments the shared 10bp 5' bases were trimmed and reads less than 40 bp were discarded. Reads are first mapped using STAR to the human genome hg38. Unmapped reads were then alligned using TMAP (map1,2,&3). The results are then combined into one file using samtools and picard-tools.
Gene-level RNA quantification was determined using Partek Genomics Suite 6.6 and the hg38 RefSeq Transcript annotation. Only reads aligned to exons were considered in the determination of the number of reads per gene.
Protein coding RNA gene level results were normalized using the trimmed mean of the M-values (TMM) method of Robinson and Oshlack [Genome Biology 2010, 11:R25] as implemented by “edgeR”. Using the raw integer read counts for protein coding genes (HUGO Gene Nomenclature Database) as input, the normalization factor (norm.factor) and  total number of mRNAs reads for each sample (lib.size) were determined.  The final processed normalized data for each gene is expressed as reads per million aligned reads (RPM) where RPM = (raw read count * 1 x 106) /(norm.factor * lib.size) .
Genome_build: hg38
Supplementary_files_format_and_content: Tab-delimited text; Annotations, mRNA  gene-level raw read counts (Reads) and TMM-normalized read counts per million mRNA alignments (RPM) for all protein coding genes

source_name: Fetal RPE- Donor "E"

growth_protocol: RPE cells were isolated from fetal donor eyes (Advanced Biosciences Resources, Alameda, CA USA) according to the methods of Hu and Bok [Mol. Vis. 2001, 7:14-19; Methods Mol. Biol. 2010, 652:55-73]. Beyond the initial isolation, all cell culture was carried out using a base medium described by Maminiskis [Invest. Ophthalmol. Vis. Sci.2006, 47:3612-3624]. For 2-3 days post-plating the medium included 15% heat inactivated fetal calf serum. Thereafter, it was reduced to 5%. To generate a working cell bank, primary fetal RPE stocks were expanded approximately 10-fold and these working stocks were designated Passage 0. ECIS 96W1E+ plates were coated with 10mM cysteine per manufacturer recomendations before coating with 20 ug/m laminin. Fetal cells were plated at 100,000/cm2 and allowed to differentiate for 32-40 days

extract_protocol:
RNA was harvested using NucleoSpin RNA XS kit (Clontech Laboratories)
RNA was converted into cDNA using SMART-Seq v4 Ultra Low Input RNA Kit (Clontech Laboratories). DNA libraries were prepared with Ion Xpress™ Plus gDNA Fragment Library Preparation kit and sequenced by an Ion Proton next-generation sequencer (Thermo Fisher Scientific Inc.).

treatment_protocol: Acute samples were wounded one time (1Z). Chronic samples were wounded once every 24-hours for 10 consecutive days (10Z). Wounds were applied using ECIS Zθ with a wound current of 3000 µA, frequency of 60000Hz, and a wound time of 15 sec. Samples were let to recover for 5-hours, 24-hours, or 8-days after final wound treatment before harvesting with a 1.5mm biopsy punch. Unwounded samples were used as controls (0Z)

tag: cell type

value: retinal pigmented epithelial (RPE) cells

tag: donor id

tag: plating density

tag: wounding condition

value: Unwounded

tag: time point

value: 8 days

tag: substrate

value: ECIS 96W1E+


title: 8D0Z_1

description: Unwounded control for 8D samples


title: 24H0Z_3

description: Unwounded control for 5H and 24H samples


title: 24H0Z_2


title: 24H0Z_1


title: 8D10Z_3

description: Chronic Wound 8D time point

value: Chronic


title: Vehicle TAM4

tag: strain

tag: treatment


title: 5H1Z_3

description: Acute Wound 5H time point

value: Acute


title: 5H1Z_2

description: Acute Wound 5H time point


title: 5H1Z_1

description: Acute Wound 5H time point


title: Vehicle TAM2


title: Vehicle TAM1


title: 8D0Z_2

description: Unwounded control for 8D samples


title: CTLA4.WT.M34 [1047513]

description:
1047513_1_1_180924_D00377_0359_BHF5W5BCX2
processed data file: b16_counts.txt

data_processing:
Array Studio software (OmicSoft) used for reads mapping.
Genome_build: GRCm38
Supplementary_files_format_and_content: tab-delimited text file include read count for each sample

extract_protocol:
Total RNA was purified from all samples using MagMAX™-96 for Microarrays Total RNA Isolation Kit (Ambion by Life Technologies) according to manufacturer’s specifications. Genomic DNA was removed using MagMAX™Turbo™DNase Buffer and TURBO DNase from the MagMAX kit listed above (Ambion by Life Technologies).
Strand-specific mRNAseq libraries were prepared from total RNA using the KAPA Stranded mRNA-Seq Kits (Kapa Biosystems).

tag: strain background

tag: genotype

value: Aire+/+

value: tumor


title: CTLA4.WT.M33 [1047512]

description:
1047512_1_1_180924_D00377_0359_BHF5W5BCX2
processed data file: b16_counts.txt


title: CTLA4.WT.M32 [1047511]

description:
1047511_1_1_180924_D00377_0359_BHF5W5BCX2
processed data file: b16_counts.txt


title: 24H1Z_2

description: Acute Wound 24H time point


title: 8D1Z_3

description: Acute Wound 8D time point


title: 24H10Z_1

description: Chronic Wound 24H time point


title: 24H1Z_3

description: Acute Wound 24H time point


title: 24H10Z_3

description: Chronic Wound 24H time point


title: 5H10Z_3

description: Chronic Wound 5H time point


title: 8D10Z_2

description: Chronic Wound 8D time point


title: 8D1Z_2

description: Acute Wound 8D time point


title: CTLA4.WT.M30 [1047510]

description:
1047510_1_1_180924_D00377_0359_BHF5W5BCX2
processed data file: b16_counts.txt


title: 8D10Z_1

description: Chronic Wound 8D time point


title: 5H10Z_1

description: Chronic Wound 5H time point


title: 24H10Z_2

description: Chronic Wound 24H time point


title: 8D1Z_1

description: Acute Wound 8D time point


title: CTLA4.WT.M27 [1047507]

description:
1047507_1_1_180924_D00377_0359_BHF5W5BCX2
processed data file: b16_counts.txt


title: 24H1Z_1

description: Acute Wound 24H time point


title: 5H10Z_2

description: Chronic Wound 5H time point