title: Input-HOXD13-wt

source_name: sonified chromatin from Hoxd13(wt) expressing chMM


title: R9308-12 rep1

status: Public on Aug 19 2013

type: SRA

city: hangzhou

first: Rongrong

last: Zhai

address: No. 359, Tiyuchang Rd

country: China

institute: China National Rice Research Institute

library_source: transcriptomic

data_processing:
Basecalls performed using CASAVA version 1.8
The raw reads were filtered to obtain high-quality reads by removing low-quality reads containing more than 30% Q<20 bases. Then  the low-quality bases (Q<20) at the 5’ and 3’ ends of the remaining reads were discarded. Passed filter reads were mapped onto the Nipponbare reference genome (IRGSP build 5.0) by RSEM (v1.1.11)
Reads Per Kilobase of exon per Megabase of library size (RPKM) were calculated to detect gene expression levels.
Supplementary_files_format_and_content: tab-delimited text files include RPKM values for each Sample ...

molecule: total RNA

organism: Oryza sativa

source_name: Root

growth_protocol: Rice seeds were surface-sterilized with 3% H2O2 for 10 min and then rinsed with distilled water several times. After soaking in distilled water at 37℃ for 2d, germinated seeds were sowed in the field of the China National Rice Research Institute, Fuyang, China, for approximately 30 d. Then 40 seedlings of each genotype were transplanted in plots on a floating foamed plastic in a pool full of nutrient solution. Roots were sampled with ten replicates at the tillering stage and heading stage to measure root traits and estimate heterosis. Meantime, for RNA-Seq analysis, two roots of every genotype at either stage were collected and stored at -80℃ before use.

extract_protocol:
Total RNA was extracted from roots using TRIzol regent (Invitrogen) and purified with Oligotex mRNA Midi Kit (QIAGEN). RNA quality was checked by the Bioanalyzer 2100 (Aligent) and all samples had RNA Integrity Number (RIN) value more than 8.5. The sequencing library was prepared according to manufacturer′s instructions (Illumina). The poly-A containing mRNA was isolated from total RNA using two rounds of purification with poly-T oligo-attached magnetic beads and subsequently fragmented by the RNA fragmentation kit. The first strand cDNA was generated using reverse transcriptase and random primers. After the second strand cDNA synthesis and adaptor ligation, cDNA fragments of 200 bp were isolated by gel electrophoresis and enriched by 18 cycles of PCR. The products were loaded on Illumina Hiseq2000 instrument for pair-end 100 bp×2 sequencing for 100 cycles.
RNA libraries were prepared for sequencing using standard Illumina protocols.

tag: strain

tag: tissue

value: root

tag: developmental stage

value: Tillering stage


title: Xieyou 9308-12 rep2

value: cv. Xieyou9308


title: HOXD13-Q317K

city: Berlin

first: Peter

last: Hansen

address: Augustenburger Platz 1

department: Institute for Medical Genetics and Human Genetics

country: Germany

institute: Charité-Universitätsmedizin Berlin

library_source: genomic

data_processing: Peaks were called using MACS2 with appropriate input controls and the following settings: ( -g 1. 0e9 -q None -p 1e-1 --too-large --bw (as determined by spp-get binding characteristics))

molecule: genomic DNA

organism: Gallus gallus

source_name: Hoxd13(Q317K) expressing chMM

growth_protocol: Chicken micromass cultures were routinely prepared by generating a single cell suspension of embryonic mesenchymal chicken limb bud cells (HH24) (2 × 10^7 cells/ml) and the appropriate virus was added before plating. Cultures were plated as 10µl droplets and cells were cultured for 9 days in chMM medium (DMEM/HAM’S F12 (Gibco) with 10% FBS (PAA), 0.2% chicken serum (Sigma), 1% L-glutamin (Gibco), 1% penicillin/streptomycin (Gibco) before harvest.

extract_protocol: Lysates were clarified from sonicated nuclei and protein-DNA complexes were enriched with antibody. For ChIP-seq library preparation ethanol precipitated DNA from ChIP was redissolved in 46 µl of water and subjected to library preparation using the NEBnext ChIP-Seq Library Prep Master Mix for Illumina (New England Biolabs) selecting for a fragment size range of 300-450 bp according to manufacturer's instructions. Sequencing was performed on an Illumina GAIIx sequencer with 36 bp single reads using TruSeq v5 sequencing chemistry and TruSeq v5 Cluster Generation Kits. For RNA-seq, total RNA from chicken micromass cultures was isolated using peqGOLD TriFast Reagent (peqLAB) and subsequent purification with RNeasy Mini Kit (Qiagen) according to manufacturer's instructions. mRNA for RNA-seq libraries was purified using the Oligotex mRNA Mini Kit (Qiagen) from 6 µg of total RNA. RNA-seq libraries were constructed using the NEBNext mRNA Library Prep Master Mix Set for Illumina according to manufacturer's instructions selecting for a fragment size range of 300-500 bp. Sequencing was performed on an Illumina GAIIx sequencer with 115 bp single reads using TruSeq v5 sequencing chemistry and TruSeq v5 Cluster Generation Kits.

tag: cell type

value: chicken micromass

tag: days of incubation

tag: virus used for infection

tag: chip antibody

value: FLAG M2

tag: chip vendor/catalog/lot


title: Xieqingzao B-34 rep2

value: cv.Xieqingzao B

value: Heading stage


title: HOXD13-Q317R-RNAseq

description: cDNA from polyA selected RNA

data_processing: The  Reads Per Kilobase of transcript per Million mapped reads (RPKM) values were then calculated for all transcripts (i)  in dependence on the formula introduced by Mortazavi et. al. Nat Methods 2008  : RPKM(i)= (reads(i) * 10^9)/(length(i) * no.of.reads), with reads(i) = number of reads mapped to the transcript; length(i) =  length of this specific transcript ; no.of.reads = the number of mapped reads. The RPKM values were calculated for each isoform separately, taking into account the compensatory effect between isoforms of the same gene.

source_name: Hoxd13(Q317R) expressing chMM


title: Xieyou 9308-12 rep1


title: PITX1-RNAseq

description: cDNA from polyA selected RNA

source_name: Pitx1(wt) expressing chMM


title: HOXD13-Q317K-RNAseq

description: cDNA from polyA selected RNA


title: HOXD13-wt

source_name: Hoxd13(wt) expressing chMM


title: Lib11

status: Public on Aug 18 2013

city: Helsinki

first: Kui

last: Qian

address: Viikinkaari 4

country: Finland

institute: University of Helsinki

description: small RNA

data_processing:
The reads in SOLiD colorspace format were mapped to papillomavirus genomes using SOLiD small RNA pipeline (RNA2MAP) with default parameters.
The mapped results were converted to GFF files using MaToGff (Applied Biosystems).
We predicted novel virus-encoded miRNA candidates from the small RNA sequencing data using our recently developed miRSeqNovel software
Genome_build: The reference genome was constructed by concatenating 393 complete papillomavirus genomes retrieved from NCBI, including known subtypes and isolates of HPV and papillomaviruses in other species.
Supplementary_files_format_and_content: wig files were generated using RNA2MAP

organism: Homo sapiens

extract_protocol:
Total RNA from altogether four 20-micrometer sections from FFPE tissue samples were harvested using the RecoverAll total RNA isolation kit (Ambion)
Small RNA fragments of ~18–25nt were enriched from total RNA preparations (ca. 6 mg) from HPK IA cells, HPK II cells and ten tissue samples by flashPAGE system (Ambion). All of the enriched small RNA fractions (30-60 ng)  was used for preparing the libraries and subsequently ligated to adaptors in the SOLiDTM Total RNA-Seq kit (Ambion). Next, small RNAs were reverse transcribed into cDNA libraries, size selected using PAGE gel, and amplified with PCR primers introducing barcode sequences. The libraries were prepared for emulsion PCR (emPCR) according to SOLiD sequencing instructions followed by sequencing using the SOLiD 4 instrument (Life Technologies, Carlsbad, CA).

value: FFPE Tissue


title: Lib10

description: small RNA


title: Lib5

description: small RNA

source_name: squamous cell carcinoma


title: Lib6

description: small RNA

source_name: adenocarcinoma in situ


title: Lib7

description: small RNA

source_name: CIN1/ condyloma


title: Lib9

description: small RNA


title: Lib8

description: small RNA


title: Lib1

description: small RNA

source_name: HPK IA

growth_protocol: HPK IA and HPK II cells established by transfection of primary human foreskin keratinocytes with HPV 16, together with CaSki epidermoid cervical carcinoma cells and SiHa human cervical tumor cells were cultured in DMEM (Sigma-Aldrich Inc., Saint Louis, MO) supplemented with 10% fetal bovine serum and penicillin/streptomycin at 37°C and 5% CO2 in a humidified incubator.

extract_protocol:
Total RNA from cultured cells was isolated using the mirVana RNA isolation kit (Ambion, Austin, TX).
Small RNA fragments of ~18–25nt were enriched from total RNA preparations (ca. 6 mg) from HPK IA cells, HPK II cells and ten tissue samples by flashPAGE system (Ambion). All of the enriched small RNA fractions (30-60 ng)  was used for preparing the libraries and subsequently ligated to adaptors in the SOLiDTM Total RNA-Seq kit (Ambion). Next, small RNAs were reverse transcribed into cDNA libraries, size selected using PAGE gel, and amplified with PCR primers introducing barcode sequences. The libraries were prepared for emulsion PCR (emPCR) according to SOLiD sequencing instructions followed by sequencing using the SOLiD 4 instrument (Life Technologies, Carlsbad, CA).

value: Cell line


title: PITX


title: CD8 D8 Effector

city: Atlanta

first: Chris

last: Scharer

state: GA

address: 1510 Clifton Rd, Suite 3086A

department: Microbiology and Immunology

country: USA

institute: Emory University

data_processing:
Raw sequencing reads were mapped to the mm9 version of the mouse genome with Bowtie using the following options to ensure each read mapped to a unique location -m 1 -n 1
To determine differentially methylated regions (DMRs) between Naïve and D8 Effectors we applied a sliding window approach to identify methylation changes greater than 1.5 fold with an FDR less than 0.05 that were enriched above background using the MEDIPS package available through Bioconductor (Chavez et al. Genome Research, 20:1441-1550).  We used a window size of 200 bp and a step size of 100 bp to identify all 1.5 fold significantly enriched regions.  Overlapping regions were stitched together using Bedtools.
Genome_build: mm9
Supplementary_files_format_and_content: Wig files are normalized to reads per million.  A bed file of all differentially methylated regions (DMRs) identified that changed greater than 1.5 fold between Naïve and D8 Effectors.  If the DMR was methylated in Naïve it is annotated with D0 and if the DMR was methylated in D8 Effectors it is annotated with D8.  A red and blue color scheme is provided indicating D0 vs D8 methylated regions respectively.

organism: Mus musculus

source_name: CD8 T cells

extract_protocol:
LCMV-specific CD8 T cells were obtained from naïve transgenic P14 mice that have a transgenic TCR recognizing the DbGP33-41 epitope of LCMV (Pircher et al. Nature, 342:559-561).  Chimeric mice were generated by intravenous adoptive transfer of 1x10^5 congenically labeled Thy1.1+ naïve LCMV-specific CD8 T cells into Thy1.2+ C57BL/6 recipients.  24 hours after adoptive transfer, chimeric mice were infected with 2x10^5 pfu of LCMV Armstrong.  LCMV-specific effector CD8 T cells (D8 Effectors) were obtained from the spleen 8 days post infection.  CD8 T cells were purified by FACS using fluorescently labeled CD90.1 (Thy1.1) and CD8 antibodies as previously described (Kersh, E.N. Journal of Immunology, 177:3821-3826).  Naïve P14 cells (Naive) were FACS purified and used as antigen-specific naïve CD8 T cells.
Libraries were constructed using the Illumina Genomic DNA Library preparation kit with minor modifications.  Briefly, 2 ug DNA was End Repaired, A-tailed, adaptors ligated, and 200-400 bp product size selected on an agarose gel.  Adaptor-ligated size-selected DNA was used as input for the MeDIP reaction.  MeDIP DNA was PCR amplified for 15 cycles into a sequencing library and each library sequenced on a single lane of an Illumina HiSeq 200 instrument.

value: CD8 D8 Effector

tag: genetic background

value: mixed C57BL/6


title: Lib2

description: small RNA

source_name: HPK II


title: CD8 Naive

value: CD8 Naive


title: HOXD13-Q317R


title: CD8 Input

value: CD8 Input


title: hippocampus_fear-conditioned_IgG

city: Chicago

first: C. Sehwan

last: Park

state: IL

address: 375 East Chicago Ave

department: Pritzker School of Law

institute: Northwestern University

description: IgG ChIP genomic DNA from FC group

data_processing: The color space reads were mapped to the mouse genome (mm9 obtained from USCS; http://genome.ucsc.edu/cgi-bin/hgGateway?org=mouse) using the mapping tool of the Bioscope v1.2.1 software suite (Applied Biosystems). For the mapping, only reads with maximal 4 failed color calls and quality values larger than 8 were considered. The reads were mapped allowing maximal 6 color mismatches and only uniquely mapping reads were reported in a SAM file. This file was used for subsequent identification of enriched regions.

source_name: hippocampus, fear-conditioned, IgG

extract_protocol: Hippocampus from fear-conditioned and non-conditioned mice were collected, homogenized, and chromatin-immunoprecipitated with an antibody to histone H4K5 acetylation (Millipore, cat. 07-327). 200 ng of DNA from both immunoprecipitated and input control samples are sonicated at 4C to a mean fragment size of between 100 to 150 bp using the Covaris S2 System. The DNA is then end-repaired using end polishing enzymes 1 and 2 such that damaged DNA with protruding 5' or 3' ends are blunt-ended and phosphorylated. Following repair, the samples are purified using a column purification kit and the blunt ends are ligated with 1ul of multiplex adaptors P1 and P2. The ligated samples are then nick translated and amplified according to the SOLiD Fragment Library Barcoding protocol and column purified separately. The libraries are then quantitated using a Qubit Fluorometer (Invitogen). 20ul of each library is size-selected for ligation products of 170-230 bp using 2% E-gels and pooled after gel purification. Finally, equimolar amounts of each barcoded library are mixed together before ePCR followed by sequencing (ABI SOLiD System 3+).

treatment_protocol: contextual fear-conditioning

tag: age

value: 6 months

value: hippocampus


title: hippocampus_fear-conditioned_H4K5ac

description: H4K5ac ChIP genomic DNA from FC group

source_name: hippocampus, fear-conditioned, H4K5ac

value: antibody to histone H4K5 acetylation (Millipore, cat. 07-327)


title: hippocampus_fear-conditioned_input

description: Total genomic DNA input control from FC group

source_name: hippocampus, fear-conditioned, IC


title: hippocampus_context-only-control_IgG

description: IgG ChIP genomic DNA from CON group

source_name: hippocampus, context-only control, IgG


title: hippocampus_context-only-control_input

description: Total genomic DNA input control from CON group

source_name: hippocampus, context-only control, IC


title: Lib12

description: small RNA

source_name: normal cervical columnar epithelium


title: Kasumi_RUNX1_N_TERMINUS_1

status: Public on Aug 17 2013

city: Rehovot

first: Yoram

last: Groner

address: 234 Herzl St.

department: Molecular Genetics

country: Israel

institute: Weizmann institute

description: Chromain IP against RUNX1 (n-terminus), replicate 1

data_processing:
ChIP-seq short read tags were mapped to the genome using bowtie. Mapped reads were then extended to 120 bp fragments in the appropriate strand and all fragments were piled up to generate a coverage track in 50 bp resolution. We computed the genome-wide distribution of coverage on 50 bp bins for each track, and used it to normalize piled-up chip-seq coverage by transforming coverage values v to log(1-quantile(v), defining the ChIP-seq binding intensity or binding enrichment. We largely preferred using binding intensities directly, and minimized using arbitrarily defined threshold on binding intensity to define binding sites. In cases where a threshold was needed (e.g. to report indicative statistics on binding, or to facilitate motif finding), we searched for genomic bins with normalized coverage > log(1-0.9985) (merging all sites that were within 250 bp of each other). We used a control non-immune serum (NIS) ChIP-seq experiment to filter spurious binding sites (defined as bins with NIS normalized intensity > log(1-0.9985) ).
Genome_build: hg18
Supplementary_files_format_and_content: 50bp-binned profiles were converted to BigWig format.

source_name: Kasumi-1 cell culture

growth_protocol: Kasumi-1 cells were purchased from the ATCC (Manassas, VA) and maintained in RPMI-1640 supplemented with 20% fetal bovine serum (FBS), 2 mM L-glutamine and 1% penicillin–streptomycin at 37°C and 5% CO2.

extract_protocol: Cross-linked chromatin from approximately 5-10x107 Kasumi-1 cells was prepared and fragmented to an average size of approximately 200 bp by 30-40 cycles of sonication (30 seconds each) in 15 ml tubes using the Bioruprtor UCD-200 sonicator (Diagenode). For immunoprecipitation, the following antibodies were added to 12 mL of diluted, fragmented chromatin: 32 uL of anti-RUNX1 (Aziz-Aloya, 1998; Levanon, 2011) raised against the protein C-terminal fragment; 320 ul of anti-ETO (PC283; Calbiochem). Non-immunized rabbit serum served as control. DNA was purified using QIAquick spin columns (QIAGEN) and sequencing performed using Illumina genome analyzer IIx, according to the manufacturer’s instructions. For ChIP-seq analysis, Illumina sequencing of short reads (40 bp) was conducted using the GAII system.

tag: cell line

value: AML-patient-derived cell lines t(8;21) Kasumi-1

value: anti-RUNX1 (n-terminus) [Yoram Groner lab, Weizmann Institute]


title: Kasumi_RUNX1_N_TERMINUS_2

description: Chromain IP against RUNX1 (n-terminus), replicate 2


title: Kasumi_AP4_2

description: Chromain IP against AP4 replicate 2

value: anti-AP4 [Takeshi Egawa]


title: Kasumi_AP4_NIS1

description: Non-immune Serum, for comparison of the AP4 ChIP-seqs, replicate 1

value: Non-immune Serum (control for the AP4 ChIP-Seqs)


title: Lib4

description: small RNA


title: Kasumi_AP4_NIS2

description: Non-immune Serum, for comparison of the AP4 ChIP-seqs, replicate 2


title: Kasumi_RUNX1_NIS_2

description: Non-immune Serum, for comparison of the RUNX1 and AML1-ETO ChIP-seqs, replicate 2

value: Non-immune Serum (control for the RUNX1 and AML1-ETO ChIP-Seqs)


title: Kasumi_AP4_1

description: Chromain IP against AP4, replicate 1


title: hippocampus_context-only-control_H4K5ac

description: H4K5ac ChIP genomic DNA from CON group

source_name: hippocampus, context-only control, H4K5ac_ChIP


title: Lib3

description: small RNA

source_name: normal cervical squamous epithelium


title: Kasumi_RUNX1_NIS_1

description: Non-immune Serum, for comparison of the RUNX1 and AML1-ETO ChIP-seqs, replicate 1


title: Kasumi_AML1_ETO_2

description: Chromain IP against AML1-ETO replicate 2

value: anti-AML1-ETO [Calbiochem, catalog# PC283]


title: Kasumi_RUNX1_2

description: Chromain IP against RUNX1 (c-terminus), replicate 2

value: anti-RUNX1 (c-terminus) [Yoram Groner lab, Weizmann Institute]


title: Kasumi_AML1_ETO_1

description: Chromain IP against AML1-ETO, replicate 1


title: Kasumi_RUNX1_1

description: Chromain IP against RUNX1 (c-terminus), replicate 1


title: Input DNA

city: Clayton

first: Wei

last: Shi

state: Victoria

address: Wellington Rd

country: Australia

institute: Monash University

description: Sample 2

data_processing:
Single-end sequenced reads of 49 bp were obtained with the Illumina Analysis Pipeline and mapped to the mouse genome (mm9) using the Subread aligner. Ten subreads were extracted from each read and at least three consensus subreads were required to report a hit. Mapping quality scores were used to break the tie when more than one best locations were found for a read. Only uniquely mapped reads were retained.
IRF4 binding peaks were identified using MACS v1.4.1 program with a p-value cutoff of 10-5, with total sonicated chromatin (input) used as a control. Genes with binding peaks falling within between 20 kilobases upstream and 5 kilobases downstream of the gene body were considered to be IRF4 binding targets. NCBI RefSeq mouse annotation build 37.2 was used to obtain chromosomal coordinates of genes.
Entrez gene identifiers were used to match genes in ChIP-seq data with those in RNA-seq data.
MEME v4.8.1 program was used to carry out a de novo motif discovery to find the binding co-factors of IRF4. 100 bp genomic sequences centered on IRF4 binding summit positions were used for motif search.
Genome_build: mm9
Supplementary_files_format_and_content: bedGraph files including binding regions and their sequencing coverages.

source_name: Input DNA

extract_protocol:
Live cells were isolated by Histopaque gradient centrifugation.
Cross-linking was done by addition of 1% paraformaldehyde at room temperature for 10 min, followed by sonication and immunoprecipitation with 10 μg of anti-IRF4 (clone sc-6059) and a corresponding goat polyclonal-IgG control (clone sc-2028) (Santa Cruz Technologies). The DNA fragments were blunt-end ligated to the Illumina adaptors, amplified, and sequenced with an Illumina HiSeq 2000.

treatment_protocol: Naïve mouse CD8+ T cells isolated from spleens and lymph nodes were stimulated in vitro with anti-CD3 (5 mg/ml), anti-CD28 (1.8 mg/ml) and rhIL-2 (100 U/ml) for 72 h.

value: Spleens and lymph nodes

value: CD8+ T cells

tag: stimulated with

value: anti-CD3, anti-CD28 and recombinant hIL-2

tag: time

value: 72 hours


title: D. pseudoobscura RNA-seq

first: Kevin

last: White

department: Institute for Genomics and Systems Biology

institute: University of Chicago

data_processing:
Illumina Casava1.7 software used for basecalling.
Sequenced reads were trimmed for adaptor sequence (using fastx_clipper -a GATCGGAAGAGC -M 12 -Q 33), then mapped to the appropriate whole genome using tophat (tophat -o dmel_WPP --solexa1.3-quals -p 8 --bowtie1 -n 2 -g 1 -M -G dmel.gtf).
Duplicated reads were removed with SAMtools rmdup command (with -s flag for single-end data).
FPKMs for each gene were calculated using the cufflinks software (cufflinks -b -u).
Genome_build: dm3 (D. melanogaster), droSim1 (D. simulans), droYak2 (D. yakuba), dp4 (D. pseudoobscura)
Supplementary_files_format_and_content: Tab-delimited text files include FPKM values for each sample.  Format is cufflinks standard.

organism: Drosophila pseudoobscura

source_name: Whole animal

extract_protocol:
RNA was isolated with Trizol.
RNA libraries were prepared for sequencing using standard Illumina protocols

value: White prepupa

tag: organism

value: Drosophila pseudoobscura


title: IRF4 wildtype V4 rep2

description: Sample 4

data_processing:
Reads were mapped to the mouse genome using the Subread aligner. Ten subreads were extracted from each read and at least three consensus subreads were required to report a hit. The distance between paired reads was constrained to be 50−600 bp. Mapping quality scores were used to break the tie when more than one best locations were found.
The featureCounts function of the Bioconductor Rsubread package was used to count the number of fragments mapped to the exome of each gene. Fragments overlapping exons in the NCBI RefSeq mouse annotation build 37.2 were included.
Genes were filtered from downstream analysis if they failed to achieve at least 8 FPKM (Fragments Per Kilobases per Million mapped reads) in at least one library.
Counts were converted to log2 counts per million, quantile normalized and precision weighted using the voom function of the Bioconductor limma package. A linear model was fitted to each gene and empirical Bayes moderated t-statistics were used to assess differential expression. P-values were adjusted to control the global false discovery rate (FDR) across all comparisons using the global option of the limma package.
Genome_build: mm9
Supplementary_files_format_and_content: tab-delimited text files including FPKM values for each sample. Each row in the file represent a gene. Entrez gene identifier and official gene symbol are provided for each gene.
The 'Raw_counts.txt' (available on Series record) includes raw read count data for all eleven samples.

source_name: IRF4 wildtype V4

extract_protocol:
Live cells were isolated by Histopaque gradient centrifugation. RNA purification was performed following the manufacturer’s protocol using the RNAeasy Plus Mini Kit (Qiagen).
The cDNA fragments were blunt-end ligated to the Illumina adaptors, amplified, and sequenced with an Illumina HiSeq 2000 sequencer.

treatment_protocol: Naïve CD8+ T cells were isolated from spleens and lymph nodes of OT-I transgenic mice and activated in vitro with OVA peptides N4 and V4 (1 mg/ml), respectively, and rhIL-2 (100 U/ml) for 72 h.

tag: strain background

tag: genotype/variation

value: IRF4 wild type

tag: celltype

tag: treatment

value: OVA peptides V4 (SIIVFEKL) and rhIL-2

value: 48 hours


title: IRF4 wildtype naïve

description: Sample 10

source_name: IRF4 wildtype naïve

tag: tissue

value: untreated

value: 0 hours


title: IRF4 knockout V4 rep2

description: Sample 9

source_name: IRF4 knockout V4

value: IRF4 knockout


title: IRF4 knockout V4 rep1

description: Sample 8


title: IRF4 knockout N4 rep2

description: Sample 6

source_name: IRF4 knockout N4

value: OVA peptides N4 (SIINFEKL) and rhIL-2


title: IRF4 knockout N4 rep1

description: Sample 5


title: IRF4 knockout naïve

description: Sample 11

source_name: IRF4 knockout naïve


title: IRF4 ChIPSeq

description: Sample 1

source_name: IRF4 ChIPSeq

tag: strain

tag: chip antibody vendor

value: Santa Cruz Technologies

tag: chip antibody cat. #


title: IRF4 knockout N4 rep3

description: Sample 7


title: IRF4 wildtype V4 rep1

description: Sample 3


title: IRF4 wildtype N4 rep2

description: Sample 2

source_name: IRF4 wildtype N4


title: D. melanogaster RNA-seq

organism: Drosophila yakuba

tag: developmental stage

value: Drosophila yakuba


title: IRF4 wildtype N4 rep1

description: Sample 1


title: D. simulans RNA-seq

organism: Drosophila simulans

value: Drosophila simulans


title: D. yakuba RNA-seq

organism: Drosophila melanogaster

value: Drosophila melanogaster


title: Kc167_Input, replicate1

status: Public on Aug 16 2013

middle: P.

address: 900 E. 57th STR. 10th FL.

description:
NA
NA

data_processing:
The Raw images were first processed with the Casava 1.7.0.
Base-called sequences with confidence metrics were obtained using OLB-1.9.0.  All multiplexed samples were demultiplexed using Casava 1.7.0
The BWA program was used to align the sequence reads to the Drosophila melanogaster (v5.32) genome, allowing up to 2 edit distance in the seed region and 3 in the full read length. Tags that aligned to more than one  location were excluded from our analysis for both ChIP sample and the corresponding control sample (input chromatin). Only properly aligned reads with mapping quality more than 30 were kept.
Peaks were called using SPP and IDR
Wig files were generated using MACS2
Genome_build: dm3
Supplementary_files_format_and_content: bed (columns are: chrom; chromStart; chromEnd; name; score; strand; signalValue; pValue; qValue; peak; Ref to: http://code.google.com/p/phantompeakqualtools/) and wig

extract_protocol:
Chromatin lysates were clarified from homogenized and sonicated tissues; protein-DNA complexes were isolated with antibody.  DNA fragments recovered following chromatin IP prepared for Illumina sequencing using the Epicentre Nextera DNA Sample Prep Kit (Cat. # GA0911).  Briefly, up to 12.5 ng DNA was included in the high molecular weight (HMW) tagmentation reaction (5 minutes at 55 degrees Celsius). Tagmented DNA was purified using a Qiagen MinElute column. Addition of barcoded PCR-compatible sites and library enrichment were performed using 12 cycles of PCR. Amplified DNA was purified using the Qiagen MinElute PCR Purification Kit. Library fragments of approximately 225 bp were gel purified and captured on an Illumina flow cell for cluster generation. Libraries were sequenced on a HiSeq2000 according to the manufacturer’s protocol.
Libraries were prepared according to ChIP-seq library kit instruction Nextera DNA prep kit is FC-121-103

tag: fraction

value: input DNA

tag: replicate

tag: transcription factor

tag: antibody name

tag: antibody manufacturer

tag: antibody catalog number


title: S2_Input, replicate1

description:
NA
NA


title: AbdB_ChIP-seq, replicate2

description:
4962.bw
4962.bed

source_name: AbdB-GFP

value: ChIP

value: AbdB

value: Anti-GFP

value: Abcam


title: AbdB_Input, replicate1

description:
NA
NA


title: AbdB_ChIP-seq, replicate1

description:
4962.bw
4962.bed


title: Cmi_Input, replicate1

description:
NA
NA

source_name: Exd-GFP


title: CG8478_ChIP-seq, replicate2

description:
4966.bw
4966.bed

value: Aviva


title: CG8478_ChIP-seq, replicate1

description:
4966.bw
4966.bed


title: Cmi_ChIP-seq, replicate1

description:
4967.bw
4967.bed

value: Cmi

value: Gift from Dingwall Lab


title: h_ChIP-seq, replicate2

description:
4983.bw
4983.bed

value: h


title: h_ChIP-seq, replicate3

description:
4983.bw
4983.bed


title: h_ChIP-seq, replicate1

description:
4983.bw
4983.bed


title: Hr78_E8-16_Input, replicate1

description:
NA
NA


title: Hr78_E8-16_ChIP-seq, replicate2

description:
4998.bw
4998.bed


title: Hr78_E8-16_ChIP-seq, replicate1

description:
4998.bw
4998.bed


title: insv_ChIP-seq, replicate1

description:
5001.bw
5001.bed

value: insv

value: Gift from Eric Lai lab


title: insv_ChIP-seq, replicate2

description:
5001.bw
5001.bed


title: Hr78_W3L_ChIP-seq, replicate2

description:
5000.bw
5000.bed


title: Lola_Input, replicate1

description:
NA
NA

source_name: LolaI-GFP


title: Hr78_W3L_ChIP-seq, replicate1

description:
5000.bw
5000.bed


title: Lola_ChIP-seq, replicate2

description:
5003.bw
5003.bed

value: Lola


title: Hr78_W3L_Input, replicate1

description:
NA
NA


title: Lola_ChIP-seq, replicate1

description:
5003.bw
5003.bed


title: Notch_Input, replicate1

description:
NA
NA

source_name: Notch-GFP


title: dm_ChIP-seq, replicate1

description:
5006.bw
5006.bed

value: dm


title: dm_ChIP-seq, replicate2

description:
5006.bw
5006.bed


title: Notch_ChIP-seq, replicate2

description:
5011.bw
5011.bed

value: Notch


title: Notch_ChIP-seq, replicate1

description:
5011.bw
5011.bed


title: Stat92E_Input, replicate1

description:
NA
NA


title: Stat92E_ChIP-seq, replicate2

description:
5013.bw
5013.bed


title: Cmi_ChIP-seq, replicate2

description:
4967.bw
4967.bed


title: Stat92E_ChIP-seq, replicate1

description:
5013.bw
5013.bed


title: Su(H)_ChIP-seq, replicate3

description:
5018.bw
5018.bed

value: Su(H)

value: Santa Cruz Biotechonology


title: Su(H)_ChIP-seq, replicate2

description:
5018.bw
5018.bed


title: Su(H)_ChIP-seq, replicate1

description:
5018.bw
5018.bed


title: EStTA-PB-B-26, mapping restr enz 2

city: Amsterdam

first: Bas

last: van Steensel

address: Plesmanlaan 121

department: division of Molecular Biology

country: Netherlands

institute: Netherlands Cancer Institute

data_processing:
Library strategy: TRIP
Basecalling and filtering was performed using standard software of  the illumina hiSeq 2000
For Expression: Sequences of indices (10 bp) and barcodes (15-17 bp) were determined in each read using Bioconductor package ShortRead. For each replicate of the normalization reads (norm counts), only the barcodes with at least 100 counts were taken for the subsequent analysis. To eliminate aberrant barcodes arising from mutations during PCR and sequencing, the following algorithm was used. First, we sorted barcodes according to their counts. Then, for each barcode (starting from the most frequent one), we identified and removed all its mutant versions, defined as barcodes within a Hamming distance of 3. The remaining sequences were regarded as ‘genuine’ barcodes.   The set of genuine barcodes was used as a reference to identify and count the barcodes in the expression (expr counts) and normalization reads (norm counts). The expr counts were normalized by dividing by corresponding norm counts to obtain the expression for each barcode.
For mapping: Sequences of indices (10 bp), barcodes (15-17 bp) and associated genomic DNA were determined in each read using Bioconductor package ShortRead. The reads containing the ‘genuine barcodes’ from the corresponding cell line were retained. The genomic DNA sequences in the reads retained were aligned against mouse genome mm9 using Bowtie 2.0 with the following settings.  -p 6 -f  --sensitive -x mm9 –U    To find the location of integration of a barcode  i) At first the DpnII data was analyzed. If there are reads associated then the most frequent read should represent at least 60% of total reads whereas the representation of the second most frequent read should be less than 20%.   ii). After getting the associated genomic region from DpnII data, the Sau3AI data was used to find if location found by DpnII data analysis could be confirmed. For this, there should be reads mapping within 1000 bp from the reads associated with this barcode in DpnII data. In addition, if found, a site was selected that was nearer to the actual site of integration (because Sau3AI also cuts other similar sites than GATC, so multiple closely spaced ligation points are possible for one barcode). It is important to note that because the sequencing was performed only from one side (the barcode side) so it is mostly not possible to detect the exact site of integration. In the end the length of the aligned read was either added (if the integration is on ‘-’ strand) or subtracted (if the integration is on ‘+’ strand) from the position of alignment to get a position, which is nearest to the actual site of integration.
For further details see the supplementary methods document 'Inventory of TRIP libraries_v04_LP130529.docx'.
Genome_build: MGSCv37 (mm9)
Supplementary_files_format_and_content: Tabular text: It contains genomic locations of mapped barcodes and raw normalization_counts and expression_counts for each cell line

source_name: ES cells

growth_protocol: Mouse embryonic stem cells EBRTcH3 expressing the tetracycline-controlled transactivator from the endogenous ROSA26 promoter (Masui et. al., Nucleic Acids Res., 2005; PMID: 15741176) and harboring reporter integrations with mouse PGK promoter were cultured in 60% BRL cell-conditioned medium in the presence of leukemia inhibitory factor, MEK inhibitor PD0325901 and GSK-3 inhibitor CHIR99021.

extract_protocol:
Total RNA was isolated from each of the clones using Qiagen RNeasy kit.  Genomic DNA was isolated using Qiagen DNeasy kit.
Mapping of the barcoded PB insertion sites was done by inverse PCR coupled with high throughput sequencing. Briefly, 2 μg of gDNA was digested with 20 units of DpnII (New England Biolabs) overnight at 37°C in a volume of 100 μl. Subsequently, 600 ng of purified digested DNA was self-ligated with 40 units of high concentration T4 DNA ligase (Promega) overnight at 4°C in a volume of 400 μl. The ligation reactions were phenol/chloroform/isoamylalcohol extracted and ethanol precipitated. DNA pellets were dissolved in 30 μl of water. 5 μl of each sample was used as a template for amplification of fragments containing both the barcodes and flanking genomic DNA regions. PCR was performed in three rounds and purified products were directly used for high throughput Illumina paired-end sequencing. To measure the barcode expression levels (expression_counts), 2 μg of total RNA was reverse transcribed in a 50 μl reaction containing 50 ng of oligo(dT) primer and 1 μl of Superscript II (Invitrogen). 1 μl of cDNA was used as a template for amplification of barcode sequences . PCR was performed in two rounds and purified products were directly used for high throughput Illumina single-read sequencing. To quantify the barcode abundances for normalization (normalization_counts), 100 ng of gDNA instead of cDNA was used as a template.

treatment_protocol: To establish the cell lines harboring multiple reporter constructs with the mPGK promoter, EBRTcH3 cells were transfected with 22.5 μg of barcoded piggyBac mPGK plasmid library and 2.5 μg of mPB transposase (Cadinanos and Bradley, Nucleic Acids Res., 2007; PMID: 17576687) plasmid using Lipofectamine 2000 (Invitrogen). After 36-48 hr, the cells were FACS sorted into three populations with respect to eGFP signal. The cells with high levels of eGFP expression were grown sparsely on 10-cm dishes and single clones were picked and further propagated.

tag: cell line

tag: cell type

value: mouse embryonic stem cell line

tag: promoter construct

value: mPGK

tag: restriction enzyme

value: DpnII

tag: index sequence

value: TCGTCGCTCG


title: EStTA-PB-B-25, mapping restr enz 2

value: TAGAGACGAG


title: EStTA-PB-B-23, mapping restr enz 2

value: TACGAGTATG


title: EStTA-PB-B-22, mapping restr enz 2

value: CGTAGACTAG


title: insv_ChIP-seq, replicate3

description:
5001.bw
5001.bed

value: ChIP


title: EStTA-PB-B-20, mapping restr enz 2

value: TGTACTACTC


title: EStTA-PB-B-21, mapping restr enz 2

value: ACGACTACAG


title: EStTA-PB-B-18, mapping restr enz 2

value: CGTCTAGTAC


title: EStTA-PB-B-16, mapping restr enz 2

value: ATACGACGTA


title: EStTA-PB-B-25, mapping restr enz 1

value: TCTCTATGCG


title: EStTA-PB-B-17, mapping restr enz 2

value: TCACGTACTA


title: EStTA-PB-B-22, mapping restr enz 1

value: CGTGTCTCTA


title: EStTA-PB-B-20, mapping restr enz 1

value: ATCAGACACG


title: EStTA-PB-B-23, mapping restr enz 1

value: CTCGCGTGTC


title: EStTA-PB-B-26, mapping restr enz 1

value: mouse embryonic stem cell line

value: TGATACGTCT


title: EStTA-PB-B-18, mapping restr enz 1

value: mPGK

value: AGACGCACTC


title: EStTA-PB-B-17, mapping restr enz 1

value: ACGCTCGACA


title: EStTA-PB-B-21, mapping restr enz 1

value: ATATCGCGAG


title: EStTA-PB-B-19, mapping restr enz 1

value: AGCACTGTAG


title: EStTA-PB-B-16, mapping restr enz 1

value: ACGAGTGCGT


title: EStTA-PB-B-25 normalization_counts

value: CAGTAGACGT


title: EStTA-PB-B-24, mapping restr enz 2

value: DpnII

value: TACTCTCGTG


title: EStTA-PB-B-26 normalization_counts

value: CGACGTGACT


title: EStTA-PB-B-24 normalization_counts

value: CACGCTACGT


title: EStTA-PB-B-23 normalization_counts

value: ATAGAGTACT


title: EStTA-PB-B-22 normalization_counts

value: AGTACGCTAT


title: EStTA-PB-B-21 normalization_counts

value: AGCGTCGTCT


title: EStTA-PB-B-20 normalization_counts

value: AGACTATACT


title: EStTA-PB-B-16 normalization_counts

value: mouse embryonic stem cell line

value: ACATACGCGT


title: EStTA-PB-B-19, mapping restr enz 2

value: mPGK

value: TCTACGTAGC


title: EStTA-PB-B-19 normalization_counts

value: ACTGTACAGT


title: EStTA-PB-B-18 normalization_counts

value: ACTACTATGT


title: EStTA-PB-B-26 expression_counts

molecule: polyA RNA

value: TACTGAGCTA


title: EStTA-PB-B-25 expression_counts

value: TGATACGTCT


title: EStTA-PB-B-24 expression_counts

value: TCTCTATGCG


title: EStTA-PB-B-24, mapping restr enz 1

value: TAGTATCAGC


title: EStTA-PB-B-23 expression_counts


title: EStTA-PB-B-22 expression_counts

value: CTCGCGTGTC


title: EStTA-PB-B-20 expression_counts

value: ATATCGCGAG


title: EStTA-PB-B-19 expression_counts

value: ATCAGACACG


title: EStTA-PB-B-21 expression_counts

value: CGTGTCTCTA


title: EStTA-PB-B-16 expression_counts

value: ACGCTCGACA


title: EStTA-PB-B-17 expression_counts

value: AGACGCACTC


title: tet-Off-D, mapping, repl 2, PCR1

data_processing:
Library strategy: TRIP
Basecalling and filtering was performed using standard software of  the illumina hiSeq 2000
Basecalling and filtering was performed using standard software of  the illumina HiSeq 2000
For Expression: Sequences of indices (10 bp) and barcodes (15-17) were determined in each read using Bioconductor package ShortRead. For each replicate of the normalization reads (normalization_counts), only the barcodes with at least 5 counts were taken for the subsequent analysis. To eliminate aberrant barcodes arising from mutations during PCR and sequencing, the following algorithm was used. First, we sorted barcodes according to their counts. Then, for each barcode (starting from the most frequent one), we identified and removed all its mutant versions, defined as barcodes within a Hamming distance of 2. The remaining sequences were regarded as ‘genuine’ barcodes and typically show a large overlap between the replicates. The set of genuine barcodes found in both replicates of all the induction levels was used as a reference to identify and count the barcodes in the expression (expression_counts) and normalization reads (normalization_counts) independently for each replicate.
For mapping: Starting with the forward reads, sequences of indices (10 bp), barcodes (15-17) and associated genomic DNA were determined in each read using Bioconductor package ShortRead. The reads containing the ‘genuine barcodes’ from the corresponding TRIP pool were retained. The genomic DNA sequences in the reads retained as well as in their reverse counterpart were aligned against mouse genome mm9 using Bowtie 2.0 with the following settings.  -p 6 -f  --sensitive -x mm9 –U    Only those barcodes were retained for which  i) there were at least 3 reads aligned to the genome  ii) one associated location with this barcode on the reverse read was representing more than 90% of reads   iii) no other location associated with this barcode on the reverse read was representing 2.5% or more reads  iv) one location associated with this barcode on the forward read was representing more than 70% of reads  v) no other location associated with this barcode on the forward read was representing 5% or more reads   vi) the forward and the reverse reads align to the same chromosome within a distance of 5 Kb    These retained barcodes were considered the mapped barcodes and sites of integration of IRs with those barcodes are the most frequent positions (>90%) to which the reverse reads align.
For further details see the supplementary methods document 'Inventory of TRIP libraries_v04_LP130529.docx'.
Genome_build: MGSCv37 (mm9)
Supplementary_files_format_and_content: Tabular text: It contains genomic locations of mapped barcodes and raw normalization_counts and expression_counts for each replicate and each concentration of Doxycycline

extract_protocol:
Total RNA was isolated from each of these clones using Qiagen RNeasy kit.  Genomic DNA was isolated using Qiagen DNeasy kit.
Mapping of the barcoded PB insertion sites was done by inverse PCR coupled with high throughput sequencing. Briefly, 2 μg of gDNA was digested with 20 units of DpnII (New England Biolabs) overnight at 37°C in a volume of 100 μl. Subsequently, 600 ng of purified digested DNA was self-ligated with 40 units of high concentration T4 DNA ligase (Promega) overnight at 4°C in a volume of 400 μl (2 times for each technical replicate of the TRIP pool). The ligation reactions were phenol/chloroform/isoamylalcohol extracted and ethanol precipitated. DNA pellets were dissolved in 30 μl of water. 5 μl of each sample was used as a template for amplification of fragments containing both the barcodes and flanking genomic DNA regions (two PCR replicates were performed each with a different index). PCR was performed in three rounds and purified products were directly used for high throughput Illumina paired-end sequencing. To measure the barcode expression levels (expression_counts), 2 μg of total RNA was reverse transcribed in a 50 μl reaction containing 50 ng of oligo(dT) primer and 1 μl of Superscript II (Invitrogen). 1 μl of cDNA was used as a template for amplification of barcode sequences. PCR was performed in two rounds and purified products were directly used for high throughput Illumina single-read sequencing. To quantify the barcode abundances for normalization (normalization_counts, 100 ng of gDNA instead of cDNA was used as a template.

treatment_protocol: To establish the pools of cells harboring reporter constructs with the mPGK promoter, ~ 6 million EBRTcH3 cells were transfected with 22.5 μg of barcoded piggyBac tet-Off plasmid library and 2.5 μg of mPB transposase (Cadinanos and Bradley, Nucleic Acids Res., 2007; PMID: 17576687) plasmid using Lipofectamine 2000 (Invitrogen). After 36-48 hr, the cells were FACS sorted into three populations with respect to eGFP signal. The cells with low levels of eGFP expression were sorted and grown for 5 days. Then small pools of cells (TRIP pools) were isolated and propagated further for 7 days. Then each TRIP pool was split into two halves (serving as technical replicates) and each half was grown independantly for additional 7 days. Then each technical replicate pool was split into four pools which were treated with different concentrations of Doxycycline (0, 0.01, 0.1 and 100 ng/ml) for 72 hr  before RNA and DNA were isolated for further analysis.

value: tet-Off

tag: dox concentration


title: tet-Off-D, Dox  conc 100, normalization_counts, repl 2

value: mouse embryonic stem cell line

value: CATAGTAGTG


title: tet-Off-D, mapping, repl 2, PCR2

value: TCACGTACTA


title: tet-Off-D, mapping, repl 1, PCR1


title: tet-Off-D, mapping, repl 1, PCR2

value: ATACGACGTA


title: EStTA-PB-B-18 expression_counts

value: mPGK

value: AGCACTGTAG


title: tet-Off-D, Dox  conc 0.1, normalization_counts, repl 2

value: CGAGAGATAC


title: tet-Off-D, Dox  conc 0.01, normalization_counts, repl 2


title: tet-Off-D, Dox  conc 100, normalization_counts, repl 1


title: tet-Off-D, Dox  conc 0, normalization_counts, repl 2


title: tet-Off-D, Dox  conc 0, normalization_counts, repl 1

value: TACTGAGCTA


title: tet-Off-D, Dox  conc 100, expression_counts, repl 2

value: ACTGTACAGT


title: EStTA-PB-B-17 normalization_counts

value: ACGCGAGTAT


title: tet-Off-D, Dox  conc 0.1, normalization_counts, repl 1

value: TCTCTATGCG


title: tet-Off-D, Dox  conc 0.01, normalization_counts, repl 1

value: TGATACGTCT


title: tet-Off-D, Dox  conc 100, expression_counts, repl 1

value: TCGTCGCTCG


title: tet-Off-D, Dox  conc 0.1, expression_counts, repl 1

value: ACATACGCGT


title: tet-Off-D, Dox  conc 0.01, expression_counts, repl 2

value: AGCGTCGTCT


title: tet-Off-D, Dox  conc 0.1, expression_counts, repl 2

value: AGACTATACT


title: tet-Off-D, Dox  conc 0, expression_counts, repl 2

value: tet-Off

value: AGTACGCTAT


title: tet-Off-D, Dox  conc 0, expression_counts, repl 1

value: mouse embryonic stem cell line

value: ACTACTATGT


title: tet-Off-D, Dox  conc 0.01, expression_counts, repl 1


title: tet-Off-C, mapping, repl 2, PCR2


title: tet-Off-C, mapping, repl 1, PCR2

value: CATAGTAGTG


title: tet-Off-C, mapping, repl 2, PCR1

value: ATATCGCGAG


title: tet-Off-C, mapping, repl 1, PCR1

value: ATCAGACACG


title: tet-Off-C, Dox  conc 100, normalization_counts, repl 2


title: tet-Off-C, Dox  conc 0.1, normalization_counts, repl 1

value: ACGCTCGACA


title: tet-Off-C, Dox  conc 0.1, normalization_counts, repl 2


title: tet-Off-C, Dox  conc 100, normalization_counts, repl 1

value: ACGAGTGCGT


title: tet-Off-C, Dox  conc 0.01, normalization_counts, repl 1

value: AGACGCACTC


title: tet-Off-C, Dox  conc 0.01, normalization_counts, repl 2

value: CGTGTCTCTA


title: tet-Off-C, Dox  conc 100, expression_counts, repl 2

value: CGTAGACTAG


title: tet-Off-C, Dox  conc 0, normalization_counts, repl 2

value: CTCGCGTGTC


title: tet-Off-C, Dox  conc 0, normalization_counts, repl 1

value: AGCACTGTAG


title: tet-Off-C, Dox  conc 0.1, expression_counts, repl 2

value: TACGAGTATG


title: tet-Off-C, Dox  conc 0.1, expression_counts, repl 1

value: TCTACGTAGC


title: tet-Off-C, Dox  conc 0, expression_counts, repl 2

value: TAGAGACGAG


title: tet-Off-C, Dox  conc 0, expression_counts, repl 1

value: tet-Off

value: ACGACTACAG


title: tet-Off-C, Dox  conc 0.01, expression_counts, repl 1

value: mouse embryonic stem cell line

value: TGTACTACTC


title: tet-Off-C, Dox  conc 0.01, expression_counts, repl 2

value: TACTCTCGTG


title: tet-Off-B, mapping, repl 2, PCR1


title: tet-Off-B, mapping, repl 2, PCR2

value: TACTGAGCTA


title: tet-Off-B, Dox  conc 100, normalization_counts, repl 2

value: CATAGTAGTG


title: tet-Off-B, mapping, repl 1, PCR1


title: tet-Off-B, Dox  conc 0.1, normalization_counts, repl 2

value: CGAGAGATAC


title: tet-Off-B, Dox  conc 0.1, normalization_counts, repl 1

value: TCTCTATGCG


title: tet-Off-B, mapping, repl 1, PCR2

value: TGATACGTCT


title: tet-Off-B, Dox  conc 0.01, normalization_counts, repl 2

value: ATACGACGTA


title: tet-Off-B, Dox  conc 100, normalization_counts, repl 1

value: TAGTATCAGC


title: tet-Off-B, Dox  conc 0.01, normalization_counts, repl 1


title: tet-Off-B, Dox  conc 0, normalization_counts, repl 2

value: TCACGTACTA


title: tet-Off-B, Dox  conc 0, normalization_counts, repl 1


title: tet-Off-C, Dox  conc 100, expression_counts, repl 1

value: CGTCTAGTAC


title: tet-Off-B, Dox  conc 100, expression_counts, repl 1

value: TCGTCGCTCG


title: tet-Off-B, Dox  conc 0.1, expression_counts, repl 1

value: ACATACGCGT


title: tet-Off-B, Dox  conc 100, expression_counts, repl 2

value: ACTGTACAGT


title: tet-Off-B, Dox  conc 0.1, expression_counts, repl 2

value: tet-Off

value: AGACTATACT


title: tet-Off-B, Dox  conc 0.01, expression_counts, repl 2

value: mouse embryonic stem cell line

value: AGCGTCGTCT


title: tet-Off-A, mapping, repl 2, PCR1

value: ACGCTCGACA


title: tet-Off-A, mapping, repl 1, PCR2


title: tet-Off-A, mapping, repl 2, PCR2


title: tet-Off-B, Dox  conc 0, expression_counts, repl 1

value: ACTACTATGT


title: tet-Off-A, mapping, repl 1, PCR1

value: ACGAGTGCGT


title: tet-Off-A, Dox  conc 0, normalization_counts, repl 2

value: CTCGCGTGTC


title: tet-Off-A, Dox  conc 100, normalization_counts, repl 1


title: tet-Off-A, Dox  conc 0.01, normalization_counts, repl 2

value: CGTGTCTCTA


title: tet-Off-A, Dox  conc 0.1, normalization_counts, repl 2

value: ATATCGCGAG


title: tet-Off-A, Dox  conc 0.1, normalization_counts, repl 1


title: tet-Off-A, Dox  conc 0.01, normalization_counts, repl 1

value: AGACGCACTC


title: tet-Off-A, Dox  conc 100, normalization_counts, repl 2

value: ATCAGACACG


title: tet-Off-A, Dox  conc 100, expression_counts, repl 2

value: CGTAGACTAG


title: tet-Off-A, Dox  conc 0.1, expression_counts, repl 2

value: TACGAGTATG


title: tet-Off-A, Dox  conc 100, expression_counts, repl 1

value: CGTCTAGTAC


title: tet-Off-A, Dox  conc 0, normalization_counts, repl 1

value: AGCACTGTAG


title: tet-Off-A, Dox  conc 0.1, expression_counts, repl 1

value: TCTACGTAGC


title: tet-Off-A, Dox  conc 0.01, expression_counts, repl 2

value: tet-Off

value: TACTCTCGTG


title: tet-Off-A, Dox  conc 0, expression_counts, repl 2

value: mouse embryonic stem cell line

value: TAGAGACGAG


title: tet-Off-A, Dox  conc 0, expression_counts, repl 1

value: ACGACTACAG


title: mPGK-F mapping, repl 2, PCR1

data_processing:
Library strategy: TRIP
Basecalling and filtering were performed using standard software of the Illumina HiSeq 2000.
For expression: Sequences of indices (10 bp) and barcodes (15-17 bp) were determined in each read using Bioconductor package ShortRead. For each PCR replicate of the normalization reads (normalization_counts), only the barcodes with at least 5 counts were taken and the barcodes present in both PCR replicates were used for the subsequent analysis. To eliminate aberrant barcodes arising from mutations during PCR and sequencing, the following algorithm was used. First, we sorted barcodes according to their counts. Then, for each barcode (starting from the most frequent one), we identified and removed all its mutant versions, defined as barcodes within a Hamming distance of 2. The remaining sequences were regarded as 'genuine' barcodes and typically show a large overlap between the replicates. The barcodes identified only in one technical replicate are mostly with low counts and are frequently lost in the other replicate due to the threshold of 5 counts . The set of genuine barcodes found in both replicates was used as a reference to identify and count the barcodes in the expression (expression_counts) and normalization reads (normalization_counts) independently for each replicate.
For mapping: Starting with the forward reads, sequences of indices (10 bp), barcodes (15-17 bp) and associated genomic DNA were determined in each read using Bioconductor package ShortRead. The reads containing the 'genuine barcodes' from the corresponding TRIP pool were retained. The genomic DNA sequences in the reads retained as well as in their reverse counterpart were aligned against mouse genome mm9 using Bowtie 2.0 with the following settings: -p 6 -f --sensitive -x mm9 –U
Only those barcodes were retained for which
i) there were at least 3 reads aligned to the genome
ii) one associated location with this barcode on the reverse read was representing more than 90% of reads
iii) no other location associated with this barcode on the reverse read was representing 2.5% or more reads
iv) one location associated with this barcode on the forward read was representing more than 70% of reads
v) no other location associated with this barcode on the forward read was representing 5% or more reads
vi) the forward and the reverse reads align to the same chromosome within a distance of 5 Kb
These retained barcodes were considered the mapped barcodes and sites of integration of IRs with those barcodes are the most frequent positions (>90%) to which the reverse reads align.
For further details, see the supplementary methods document 'Inventory of TRIP libraries_v04_LP130529.docx'.
Genome_build: MGSCv37 (mm9)
Supplementary_files_format_and_content: Tabular text: It contains genomic locations of mapped barcodes and raw normalization_counts and expression_counts for each replicate.

source_name: ES cells, IRs with mPGK promoter sequences

extract_protocol:
Total RNA was isolated using Qiagen RNeasy kit. Genomic DNA was isolated using Qiagen DNeasy kit.
Mapping of the barcoded PB insertion sites was done by inverse PCR coupled with high throughput sequencing. Briefly, 2 μg of gDNA was digested with 20 units of DpnII (New England Biolabs) overnight at 37°C in a volume of 100 μl. Subsequently, 600 ng of purified digested DNA was self-ligated with 40 units of high concentration T4 DNA ligase (Promega) overnight at 4°C in a volume of 400 μl (2 times for each technical replicate of the TRIP pool). The ligation reactions were phenol/chloroform/isoamylalcohol extracted and ethanol precipitated. DNA pellets were dissolved in 30 μl of water. 5 μl of each sample was used as a template for amplification of fragments containing both the barcodes and flanking genomic DNA regions (two PCR replicates were performed each with a different index). PCR was performed in three rounds and purified products were directly used for high throughput Illumina paired-end sequencing. To measure the barcode expression levels (expression_counts), 2 μg of total RNA was reverse transcribed in a 50 μl reaction containing 50 ng of oligo(dT) primer and 1 μl of Superscript II (Invitrogen). 1 μl of cDNA was used as a template for amplification of barcode sequences (two PCR replicates were performed each with a different index). PCR was performed in two rounds and purified products were directly used for high throughput Illumina single-read sequencing. To quantify the barcode abundances for normalization (normalization_counts), 100 ng of gDNA instead of cDNA was used as a template (two PCR replicates were performed each with a different index).

treatment_protocol: To establish the pools of cells harboring reporter constructs with the mPGK promoter, ~6 million EBRTcH3 cells were transfected with 22.5 μg of barcoded piggyBac mPGK plasmid library and 2.5 μg of mPB transposase (Cadinanos and Bradley, Nucleic Acids Res., 2007; PMID: 17576687) plasmid using Lipofectamine 2000 (Invitrogen). After 36-48 hr, the cells were FACS sorted into three populations with respect to eGFP signal. The cells with low levels of eGFP expression were sorted and grown for 5 days. Then small pools of cells (TRIP pools) were isolated and propagated further for 7 days. Then each TRIP pool was split into two halves (serving as technical replicates) and each half was grown independently for an additional 7 days before RNA and DNA were isolated for further analysis.

tag: promoter contruct

value: mPGK

value: CGACGTGACT


title: tet-Off-B, Dox  conc 0.01, expression_counts, repl 1

value: ACGCGAGTAT


title: mPGK-F mapping, repl 1, PCR2

value: TGTGAGTAGT


title: mPGK-F mapping, repl 2, PCR 2

value: ACAGTATATA


title: mPGK-F normalization_counts, repl 2, PCR 2


title: mPGK-F mapping, repl 1, PCR 1

value: CAGTAGACGT


title: mPGK-F normalization_counts, repl 2, PCR 1

value: TACTGAGCTA


title: mPGK-F expression_counts, repl 2, PCR 2


title: mPGK-F expression_counts, repl_1, PCR 2


title: mPGK-F expression_counts, repl_1, PCR 1


title: mPGK-F normalization_counts, repl 1, PCR 1

value: TGATACGTCT


title: mPGK-E mapping, repl 2, PCR 2

value: TGACGTATGT


title: mPGK-E mapping, repl 2, PCR1

value: CACGCTACGT


title: mPGK-E normalization_counts, repl 2, PCR 2

value: TACGAGTATG


title: mPGK-E mapping, repl 1, PCR2

value: TCTATACTAT


title: mPGK-E normalization_counts, repl 1, PCR 2

value: CGTAGACTAG


title: mPGK-E normalization_counts, repl 1, PCR 1

value: TAGTATCAGC


title: tet-Off-A, Dox  conc 0.01, expression_counts, repl 1

value: mouse embryonic stem cell line

value: tet-Off

value: TGTACTACTC


title: mPGK-E normalization_counts, repl 2, PCR 1

value: mPGK

value: TCTCTATGCG


title: mPGK-E expression_counts, repl 2, PCR 1


title: mPGK-E mapping, repl 1, PCR 1

value: ATAGAGTACT


title: mPGK-E expression_counts, repl_1, PCR 2


title: mPGK-E expression_counts, repl 2, PCR 2


title: mPGK-D mapping, repl 2, PCR1

value: AGTACGCTAT


title: mPGK-E expression_counts, repl_1, PCR 1


title: mPGK-D mapping, repl 1, PCR 1

value: AGCGTCGTCT


title: mPGK-F normalization_counts, repl 1, PCR 2

value: TACTCTCGTG


title: mPGK-D normalization_counts, repl 2, PCR 2

value: ACGACTACAG


title: mPGK-D mapping, repl 1, PCR2

value: TCGCACTAGT


title: mPGK-D normalization_counts, repl 2, PCR 1

value: CTCGCGTGTC


title: mPGK-D expression_counts, repl 2, PCR 1


title: mPGK-D normalization_counts, repl 1, PCR 2


title: mPGK-D normalization_counts, repl 1, PCR 1

value: CGTGTCTCTA


title: mPGK-F expression_counts, repl 2, PCR 1

value: CGACGTGACT


title: mPGK-D expression_counts, repl 2, PCR 2

value: TCTAGCGACT


title: tet-Off-B, Dox  conc 0, expression_counts, repl 2


title: mPGK-D expression_counts, repl_1, PCR 2


title: mPGK-D expression_counts, repl_1, PCR 1


title: mPGK-C mapping, repl 2, PCR 2

value: TCGATCACGT


title: mPGK-C mapping, repl 1, PCR2

value: TAGTGTAGAT


title: mPGK-C normalization_counts, repl 2, PCR 2

value: mouse embryonic stem cell line

value: TCTACGTAGC


title: mPGK-C mapping, repl 1, PCR 1

value: ACTGTACAGT


title: mPGK-C normalization_counts, repl 1, PCR 2

value: mPGK

value: CGTCTAGTAC


title: mPGK-C normalization_counts, repl 1, PCR 1

value: ATCAGACACG


title: mPGK-C expression_counts, repl 2, PCR 1

value: AGACTATACT


title: mPGK-C expression_counts, repl 2, PCR 2


title: mPGK-D mapping, repl 2, PCR 2


title: mPGK-C expression_counts, repl_1, PCR 2


title: mPGK-B mapping, repl 2, PCR 2

value: TACGCTGTCT


title: mPGK-C expression_counts, repl_1, PCR 1


title: mPGK-B mapping, repl 2, PCR1

value: ACTACTATGT


title: mPGK-B mapping, repl 1, PCR 1

value: ACGCGAGTAT


title: mPGK-B normalization_counts, repl 1, PCR 2

value: ATACGACGTA


title: mPGK-B normalization_counts, repl 2, PCR 2

value: TCACGTACTA


title: mPGK-B normalization_counts, repl 2, PCR 1

value: AGCACTGTAG


title: mPGK-B mapping, repl 1, PCR2

value: TACAGATCGT


title: mPGK-B normalization_counts, repl 1, PCR 1

value: AGACGCACTC


title: mPGK-B expression_counts, repl 2, PCR 2


title: mPGK-A mapping, repl 2, PCR1

value: ACATACGCGT


title: mPGK-C mapping, repl 2, PCR1


title: mPGK-A normalization_counts, repl 2, PCR 2

value: CGAGAGATAC


title: mPGK-A mapping, repl 1, PCR 1

value: mouse embryonic stem cell line

value: TCGTCGCTCG


title: mPGK-A mapping, repl 1, PCR2

value: TACACACACT


title: mPGK-A mapping, repl 2, PCR 2

value: mPGK

value: TACACGTGAT


title: mPGK-A normalization_counts, repl 2, PCR 1

value: ACGCTCGACA


title: mPGK-C normalization_counts, repl 2, PCR 1

value: ATATCGCGAG


title: H3ac H3K4me3 input control (Rag1 -/- DN thymocytes)

city: La Jolla

first: Salvatore

last: Loguercio

state: California

address: 10550 North Torrey Pines Rd

department: MB

institute: TSRI

description: H3ac_H3K4me3 input control

data_processing:
Duplicated reads were removed before mapping.
Experimental and input control fastaq tags were aligned to the mouse reference genome (mm9) using Bowtie 0.12.9. Alignment parameters used: -a -v 2 -m 3 --best --strata
All reads mapping with their best alignment score at more than 3 sites in the genome were discarded.
Tags were extended 300 bp upstream or downstream from the alignment start site, depending on the strand orientation of the mapping.
Final UCSC wig tracks had the input subtracted from the ChIP signal.
Genome_build: mm9
Supplementary_files_format_and_content: file format: UCSC wig; content: tag density (ChIP signal, input subtracted)

source_name: Rag1 -/- DN thymocytes

growth_protocol: Thymocytes were isolated from 5- to 8-wk-old Rag1−/− mice

extract_protocol:
DN cells were crosslinked with 1% formaldehyde for 10 minutes at room temperature. Subsequently, the lysates were sonicated using a Diagenode Biorupter. The chromatin solution was precleared with salmon sperm DNA-protein A agarose beads. The lysate was immunoprecipitated using the following antibodies: H3ac was purchased from EMD Millipore (Billerica, MA), H3K4me3 from Active Motif (Carlsbad, CA). Immune complexes were isolated with protein A agarose beads.  Following elution, chromatin-antibody complexes and input DNA were reverse crosslinked by heating at 65°C overnight.  The DNA was purified using the Qiagen DNA purification kit.
The sequencing libraries were prepared using 10 ng of DNA. ChIP DNA sample ends were repaired using the recommended Illumina protocol, including T4 DNA polymerase, Klenow Large Fragment, and T4 polynucleotide kinase. DNA products were purified using the DNA Clean&Concentrator- 5 Kit (Zymo Research). The DNA ends were A-tailed with Klenow Large Fragment (3′→5′ exo-) at 37 °C for 30 min. DNA products were again purified using the DNA Clean&Concentrator- 5 Kit. Next, Illumina Paired End-adapter oligonucleotides (2), at a concentration of 0.33 μM, were ligated to the A-tailed cDNA ends with T4 DNA ligase. DNA products were purified using the DNA Clean&Concentrator-5 Kit. The DNA library products were separated on a 2% (wt/vol) agarose gel, and products corresponding to a size of ∼200–250 bases were removed from the gel and cleaned using the Agencourt SPRI system (Beckman). The DNA material was PCR-amplified with Phusion Polymerase (Finnzymes) with 0.6 μM PCR primers PE 1.0 and PE 2.0 (Illumina) for 15 cycles. The amplified DNA products were further purified on 2% (wt/vol) agarose gel, excised, and isolated again using the ZymocleanGel DNA recovery kit (Zymo Research). The purified DNA library was quantitated using the Qubit quantitation platform (Invitrogen) and sized using the 2100 Bioanalyzer (Agilent). DNA products were then denatured in 0.1 N of NaOH and diluted to a final concentration of 10 pM before being loaded onto the Illumina single read flow cell for 100 base sequencing by synthesis on the Illumina HiSeq2000.

tag: antibody

value: input control

tag: strain

tag: tissue

value: DN (CD4-CD8-) thymocytes

tag: genotype

value: Rag -/-


title: mPGK-A normalization_counts, repl 1, PCR 2

value: CATAGTAGTG


title: mPGK-A normalization_counts, repl 1, PCR 1

value: ACGAGTGCGT


title: H3K4me3 ChIP-seq (Rag1 -/- DN thymocytes)

description: H3K4me3 ChIP-seq

value: H3K4me3 from Active Motif (Carlsbad, CA)


title: H3ac ChIP-seq (Rag1 -/- DN thymocytes)

description: H3ac ChIP-seq

value: H3ac from EMD Millipore (Billerica, MA)


title: EStTA-PB-B-25

data_processing:
Basecalling and filtering were performed using standard software of the Illumina HiSeq 2000.
Reads were aligned to the mouse genome mm9, using TopHat (version 1.4.0) and bowtie (version 0.12.7), using default settings and a model annotation file (GTF version 66).
Reads were assigned to genes (Ens V66) using HTSseq-count, using default settings.
Genome_build: MGSCv37
Supplementary_files_format_and_content: RNAseq_protCoding_readcounts_EnsV66_hg19_LP130219.txt: absolute read counts, generated by HTSseq-count.

source_name: total RNA from mouse embryonic stem cells harboring multiple reporter integrations with mPGK promoter

extract_protocol:
Total RNA was isolated from each of these clones using Qiagen RNeasy kit.
Illumina TruSeq RNA PART# 15008136 REVISION A.

tag: construct

value: multiple reporter constructs with the mPGK promoter


title: mPGK-A expression_counts, repl_1, PCR 1


title: mPGK-B expression_counts, repl_1, PCR 1

value: ACGCGAGTAT


title: EStTA-PB-B-26


title: EStTA-PB-B-23


title: EStTA-PB-B-19


title: EStTA-PB-B-22


title: mPGK-B expression_counts, repl 2, PCR 1

value: ACTACTATGT


title: EStTA-PB-B-20

value: mouse embryonic stem cell line


title: EStTA-PB-B-21


title: mPGK-B expression_counts, repl_1, PCR 2

value: TACAGATCGT


title: EStTA-PB-B-18


title: Pol II ChIP-seq W303 25º

city: Aurora

first: David

middle: L.

last: Bentley

state: CO

department: Biochemistry and Mol. Genetics

institute: U. Colorado School of Medicine

description:
Chromatin IP against pol II
cells were grown in YPD to O.D. ~ 0.8 at 25º

data_processing:
Single-end 50 bp?? reads were mapped to the SacCer3  with Bowtie version 0.12.5
Genome_build: scer3

organism: Saccharomyces cerevisiae

source_name: Pol II ChIP DNA

growth_protocol: cells were grown in YPD

extract_protocol: IPs from 2 mg of cross-linked extract were immunoprecipitated, and prepared for illumina library construction by repair with Klenow, T4 DNA polymerase and T4 polynucleotide kinase, A-tailing with Klenow exo-, ligation to branched adaptors, gel purification of ~200bp fragments, and amplification (18cycles) with Illumina PE primers using Phusion DNA polymerase.

tag: chip antibody

value: rabbit anti pan CTD (Schroeder eta l Genes Dev. 14:2435, 2000)

tag: growth protocol


title: EStTA-PB-B-16


title: EStTA-PB-B-17


title: H3 ChiP-seq WT 37º

description:
Chromatin IP against histone H3
cells were grown in YPD to O.D. ~ 0.8 at 25º, then shifted to YPD at 37º+ doxycycline (2ug/ml) 1hr.

source_name: H3 ChIP DNA

value: rabbit anti-H3 C-terminus (Zhang et al EMBO J. 24:2379, 2005)


title: mPGK-A expression_counts, repl_1, PCR 2

value: mPGK

value: TACACACACT


title: mPGK-A expression_counts, repl 2, PCR 2

value: TACACGTGAT


title: batch1_chrom1_LoVo_IgG_Rabbit

status: Public on Aug 15 2013

city: Stockholm

first: Martin

last: Enge

address: CCK, Z4

department: Dep of Oncology-Pathology

country: Sweden

institute: Karolinska Institute

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4

source_name: LoVo

growth_protocol: LoVo (ATCC CCL-229) and GP5d (ECACC cat no. 95090715) colon adenocarcinoma cells were cultured in DMEM supplemented with penicillin/streptomycin and 10% FBS under standard culture conditions.

extract_protocol:
Cells were cross-linked by 1% formaldehyde, and DNA was sonicated to 200- 400 bp fragments. Antibodies (5 µg) were added and collected using protein G Sepharose (GE). Cross-links were reversed and proteins digested by incubation with proteinase K at 65 °C overnight. DNA was then purified using Qiagen PCR purification kit.
Libraries were constructed according to Illuminas standard protocol. The concentration of the library was determined by Nanodrop spectrophotometer (Thermo Fisher Scientific Inc.) and 10 pmol of the DNA was applied for one flow-cell lane. Sequencing was performed using one lane of Illumina GAIIx, or alternatively, samples were indexed with DNA barcodes and four to six different samples were multiplexed in one library and sequenced using Illumina HiSeq 2000 (single 36 bp reads).

value: LoVo

value: colon adenocarcinoma

tag: enriched motif (p<0.001) with dbd sequence similarity > 65%.

tag: qc successful


title: batch1_chrom1_LoVo_IgG_Mouse


title: batch1_chrom1_LoVo_IgG_Goat


title: batch1_chrom1_LoVo_H3K4me3_Rabbit_PassedQC

description: control sample: batch1_chrom1_LoVo_IgG_Rabbit

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_H3K4me3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_H3K4me1_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_H3K4me1_PassedQC_peaks.txt: hg18

value: PassedQC


title: batch1_chrom1_LoVo_H3_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_H3_PassedQC_peaks.txt: hg18


title: EStTA-PB-B-24


title: mPGK-A expression_counts, repl 2, PCR 1

value: ACATACGCGT


title: batch2_chrom1_LoVo_ETS2_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch2_chrom1_LoVo_ETS2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZZZ3_Goat_FailedQC

description: control sample: batch1_chrom1_LoVo_IgG_Goat

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZZZ3_FailedQC_peaks.txt: hg18

value: FailedQC


title: batch1_chrom1_LoVo_ZNF706_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZNF706_PassedQC_peaks.txt: hg18


title: batch2_chrom1_LoVo_ADNP_Rabbit_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch2_chrom1_LoVo_ADNP_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZNF250_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZNF250_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZBED4_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZBED4_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZBTB17_Mouse_FailedQC

description: control sample: batch1_chrom1_LoVo_IgG_Mouse

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZBTB17_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_UBTF_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_UBTF_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_YY1_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_YY1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_XBP1_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_XBP1_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TP53_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TP53_FailedQC_peaks.txt: hg18


title: H3 ChiP-seq spt6 37º

value: cells were grown in YPD to O.D. ~ 0.8 at 25º, then shifted to YPD at 37º+ doxycycline (2ug/ml) 1hr.


title: batch1_chrom1_LoVo_TGIF1_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TGIF1_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TFEB_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TFEB_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TCF7L2_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TCF7L2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TFAP2A_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TFAP2A_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TCF12_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TCF12_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SREBF2_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SREBF2_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TBX3_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TBX3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZNF407_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZNF407_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SP1_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SP1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SOX9_Rabbit_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SOX9_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SP3_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SP3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SOX4_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SOX4_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZBTB7B_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZBTB7B_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SMC3_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SMC3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_ZNF236_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_ZNF236_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SMAD3_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SMAD3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SMAD4_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SMAD4_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TFE3_Rabbit_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TFE3_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TFDP2_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TFDP2_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_RFX2_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_RFX2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SMAD2_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SMAD2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_RFX1_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_RFX1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_RFX5_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_RFX5_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NR3C1_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NR3C1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_PITX1_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_PITX1_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_RAD21_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_RAD21_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_RAX2_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_RAX2_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_TFDP1_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_TFDP1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_RXRA_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_RXRA_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SRF_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SRF_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NR2F2_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NR2F2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NR2F1_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NR2F1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NR1H3_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NR1H3_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NPAT_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NPAT_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NFIL3_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NFIL3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NIPBL_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NIPBL_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SNAI1_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SNAI1_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_SMC1A_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_SMC1A_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NFE2L2_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NFE2L2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NFAT5_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NFAT5_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NFATC3_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NFATC3_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_NEUROG3_Mouse_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_NEUROG3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MZF1_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MZF1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MYC_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MYC_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MYBL2_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MYBL2_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MYB_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MYB_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MSX2_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MSX2_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MEIS2_Rabbit_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MEIS2_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MEF2C_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MEF2C_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MED12_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MED12_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MED1_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MED1_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MEF2A_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MEF2A_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_KLF3_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_KLF3_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_LEF1_Rabbit_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_LEF1_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_KLF5_Rabbit_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_KLF5_PassedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_KLF10_Goat_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_KLF10_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_MAX_Mouse_FailedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_MAX_FailedQC_peaks.txt: hg18


title: batch1_chrom1_LoVo_LHX2_Goat_PassedQC

data_processing:
Basecalls performed using Casava 1.4
fastq files were split by barcode
reads were aligned to the human genome (hg18) using BWA
peaks were called with MACS 1.4, using the following settings:
Genome_build: hg18
Supplementary_files_format_and_content: Peak files generated using MACS 1.4
Genome Build:
batch1_chrom1_LoVo_LHX2_PassedQC_peaks.txt: hg18