ChIP-Atlas is the database and its web interface to provide the result of analysis processed from the entire ChIP-Seq data archived in Sequence Read Archive. We have curated metadata described by original data submitter to enable further data analysis. See details here: https://github.com/inutano/chip-atlas/wiki

Table of HN-scores and ChIP-seq scores (MACS2 score) for each gene. The genes listed in this data are the only human and mouse gene symbols that can be converted.The ChIP-seq score is retrieved from the ChIP-Atlas database (http://chip-atlas.org) (accessed on February 2023). Using the "Target Genes" feature, data were obtained for HSF1, HSF2, and PPARGC1A.

All ChIP-Seq data analyzed on ChIP-Atlas. BigWig, Bed, BigBed format files are provided for each individual Experiment. Bed files are provided for data assembled by antigens and cell types. Analysis data from target genes analysis and colocalization analysis are provided in tab separated values (tsv). See details here: https://github.com/inutano/chip-atlas/wiki#peak_browser_doc * The dataset of past version can not be downloaded.

Sheet1 ToolsComparison: ChIP-seq pipeline software comparison. Sheet2 Examples of ChiLin report. A summary of example data annotation of transcription factor, chromatin regulatory factor and histone modification ChIP-seq data. Sheet3 Protein classification standard for the 8 categories. Sheet4 Protein classification results. Sheet5 BWA QC Database. ChiLin samples and datasets quality metrics across three layers. A clean up table of cistrome samples and datasets quality metrics for ChiLin users’ reference. The QC results is based on the reference of hg38 and mm10 assembly. (XLSX 10363 kb)

Publicly available ChIP-seq experiments were processed by MACS2 program and the average values of those scores were calculated for all genes.Original calculated data were from ChIP-Atlas database.Top300 genes for EPAS1(HIF2A) ChIP-seq experiments are listed for the comparison.

Publicly available ChIP-seq experiments were processed by MACS2 program and the average values of those scores were calculated for all genes.Original calculated data were from ChIP-Atlas database.Top300 genes for HIF1A ChIP-seq experiments are listed for the comparison.

H3K27me3 data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S2. Second H3K27me3 data QC report from ChiLin. The sequencing reads had been mapped to the hg38 genome build for BWA and Bowtie. File S3. H3K4me3 data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S4. Second H3K4me3 data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S5. H2A.Z data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S6. TRRAP data QC report from ChiLin. The sequencing reads had been mapped to the hg38 genome build for BWA and Bowtie. File S7. FOXA1 data QC report from ChiLin. The sequencing reads had been mapped to the hg38 genome build for BWA and Bowtie. File S8. STAT6 data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S9. AR data QC report from ChiLin. This report includes two immunoprecipitated and two input samples. The sequencing reads had been mapped to the hg38 genome build for BWA and Bowtie. File S10. RAD21 paired end data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S11. RAG2 data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S12. CHD7 data QC report from ChiLin. The sequencing reads had been mapped to the mm10 genome build for BWA and Bowtie. File S13. DNase-seq QC report from ChiLin. The sequencing reads had been mapped to the hg38 genome build for BWA and Bowtie. (GZ 9019Â kb)

Aging is a universal biological phenomenon linked to many diseases, such as cancer or neurodegeneration. However, the molecular mechanisms underlying aging, or how lifestyle interventions such as cognitive stimulation can ameliorate this process, are yet to be clarified. Here, we performed a multi-omic profiling, including RNA-seq, ATAC-seq, ChIP-seq, EM-seq, SWATH-MS and single cell Multiome scRNA and scATAC-seq, in the dorsal hippocampus of young and old mouse subjects which were subject to cognitive stimulation using the paradigm of environmental enrichment. In this study we were able to describe the epigenomic landscape of aging and cognitive stimulation.

This dataset contains information related to preprocessed datasets and additional files mentioned in the original manuscript.

ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate.

shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity >7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by managed care participation (comprehensive managed care, primary care case management, MLTSS, including PACE, behavioral health organizations, nonmedical prepaid health plans, medical-only prepaid health plans, and other). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each managed care plan type over the year (duplicated count); (2) the number of beneficiaries enrolled in each managed care plan type as of an individual’s last month of enrollment (duplicated count); and (3) average monthly enrollment in each managed care plan type. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some cells have a value of “DS”. Some states have serious data quality issues, making the data unusable for calculating these measures. To assess data quality, analysts used measures featured in the DQ Atlas. Data for a state and year are considered unusable or of high concern based on DQ Atlas thresholds for the topics Enrollment in CMC, Enrollment in PCCM Programs, and Enrollment in BHO Plans. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

ReMap is a large scale integrative analysis of DNA-binding experiments for Homo sapiens, Mus musculus, Drosophila melanogaster and Arabidopsis thaliana transcriptional regulators. The catalogues are the results of the manual curation of ChIP-seq, ChIP-exo, DAP-seq from public sources (GEO, ENCODE, ENA).

ReMap (https://remap.univ-amu.fr) aims to provide manually curated, high-quality catalogs of regulatory regions resulting from a large-scale integrative anlysis of DNA-binding experiments in Human, Mouse, Fly and Arabidopsis thaliana for hundreds of transcription factors and regulators. In this 2022 update, we have uniformly processed >11 000 DNA-binding sequencing datasets from public sources across four species. The updated Human regulatory atlas includes 8103 datasets covering a total of 1210 transcriptional regulators (TRs) with a catalog of 182 million (M) peaks, while the updated Arabidopsis atlas reaches 4.8M peaks, 423 TRs across 694 datasets. Also, this ReMap release is enriched by two new regulatory catalogs for Mus musculus and Drosophila melanogaster. First, the Mouse regulatory catalog consists of 123M peaks across 648 TRs as a result of the integration and validation of 5503 ChIP-seq datasets. Second, the Drosophila melanogaster catalog contains 16.6M peaks across 550 TRs from the integration of 1205 datasets. The four regulatory catalogs are browsable through track hubs at UCSC, Ensembl and NCBI genome browsers. Finally, ReMap 2022 comes with a new Cis Regulatory Module identification method, improved quality controls, faster search results, and better user experience with an interactive tour and video tutorials on browsing and filtering ReMap catalogs.

We thank our users for past and future feedback to make ReMap useful for the community. The ReMap team welcomes your feedback on the catalogs, use of the website and use of the downloadable files. Please contact benoit.ballester@inserm.fr for development requests.

Reference:

ReMap 2022: a database of Human, Mouse, Drosophila and Arabidopsis regulatory regions from an integrative analysis of DNA-binding sequencing experiments Fayrouz Hammal, Pierre de Langen, Aurélie Bergon, Fabrice Lopez, Benoit BallesterNucleic Acids Research, Volume 50, Issue D1, 7 January 2022, Pages D316–D325, https://doi.org/10.1093/nar/gkab996

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by program type (Medicaid or CHIP). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each program type over the year (duplicated count); (2) the number of beneficiaries enrolled in each program type as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly enrollment in each program type.

These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues, making the data unusable for calculating these measures. To assess data quality, analysts used measures featured in the DQ Atlas. Data for a state and year are considered unusable or of high concern based on DQ Atlas thresholds for the topics Medicaid-only enrollment and M-CHIP and S-CHIP Enrollment. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods.

Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by benefit package (full-scope, comprehensive, limited, or unknown). There are three metrics presented: (1) the number of beneficiaries ever enrolled with each benefit package over the year (duplicated count); (2) the number of beneficiaries enrolled with each benefit package as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly enrollment with each benefit package. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topic Restricted Benefits Code. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

The number of experiments in which gene was up/down regulated in RNA-seq data and the average of ChIP-seq MACS2 values of HIF1A and EPAS1(HIF2A) in ChIP-Atlas database.Both were calculated from public NGS database (SRA).For up/donw regulated gene selection, 2 fold threshold was adopted.

This data set includes monthly enrollment counts of Medicaid and CHIP beneficiaries by program type (Medicaid or CHIP). These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topics Medicaid-only Enrollment and M-CHIP and S-CHIP Enrollment. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

This data set includes monthly enrollment counts of Medicaid and CHIP beneficiaries by benefit package (full-scope, comprehensive, limited, or unknown). These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topic Restricted Benefits Code. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

This data set includes monthly counts and rates (per 1,000 beneficiaries) of pregnancy outcomes, including (1) live births and (2) miscarriages, stillbirths, and terminations, for female Medicaid and CHIP beneficiaries ages 15 to 44 (as of the first day of the month), by state. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating pregnancy measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Procedure Codes - OT Professional, Claims Volume - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

This data set includes monthly counts and rates (per 1,000 beneficiaries) of COVID-19 testing services provided to Medicaid and CHIP beneficiaries, by state.

These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating COVID-19 testing services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Procedure Codes - OT Professional, Claims Volume - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data.

Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

Chromatin State Profilining using multiple histone modifications in human craniofacial tissue spanning 4.5 post conception weeks to 10 pcwThe raw FASTQ sequence files are being deposited in dbGAP Parallel profiling of six distinct histone modifications via ChIP-Seq in craniofacial tissue samples from individual human embryos