Sequencing data · What you can do here
Call peaks in ATAC-seq and ChIP-seq data
Call peaks from ATAC-seq and ChIP-seq alignments using MACS3, annotate genomic features with HOMER and bedtools, and query transcription-factor motifs against JASPAR.
What this involves
Peak calling identifies genomic regions enriched for histone modifications, transcription-factor binding, or open chromatin. For ChIP-seq and ATAC-seq experiments, this involves processing aligned BAM files, distinguishing true enrichment signals from non-specific background, and identifying summits and enrichment intervals. Doing this properly requires strict attention to the reference genome build, chromosome naming styles, and interval coordinate systems across every file format.
Once candidate intervals are identified, downstream characterisation requires annotating peaks relative to genomic landmarks and identifying over-represented sequence motifs. The research agent runs peak-calling tools like MACS3 directly on its dedicated environment, links peak coordinates against known cis-regulatory elements from databases such as ENCODE and ReMap, and performs motif discovery using HOMER and curated profiles from JASPAR.
For complex or multi-sample datasets requiring standardised end-to-end processing, QC, or differential analysis, automated workflows such as nf-core/atacseq and nf-core/chipseq can also be executed directly by the agent without local setup.
How it goes
- 1Alignment inspection and index verificationUse samtools to inspect alignment headers, confirm chromosome naming conventions, and verify coordinate sorting on BAM files stored in /work/uploads/.
- 2Peak callingExecute MACS3 via run_command to model fragment distributions and identify significant enriched regions for narrow or broad marks, outputting standard BED and peak intervals to /work/.
- 3Peak manipulation and overlap analysisRun bedtools to intersect, filter, merge, or compare peak intervals across experimental conditions or against control tracks while maintaining 0-based half-open interval conventions.
- 4Peak annotation and motif discoveryUse HOMER to annotate peak summits relative to gene models and discover enriched sequence motifs de novo or against curated binding databases.
- 5Regulatory database integrationQuery JASPAR for known transcription-factor binding profiles, and cross-reference peak coordinates against ENCODE candidate cis-regulatory elements, ReMap regulatory regions, and RegulomeDB via query_database.
Start it here
Ask in plain language. The agent works on a Linux machine of its own — it installs and runs what the job needs, keeps every file, and reads the results back with the numbers explained. Nothing to set up, and a long run continues after you close the page.
What to watch for
- A coordinate without a build is not a coordinate; unlabelled coordinates between GRCh37, GRCh38, or T2T-CHM13v2.0 can sit megabases apart and are unusable.
- Mismatched contig naming styles, such as chr1 versus 1 or chrM versus MT, produce zero overlaps and emit no error during joins.
- Mixing 0-based half-open formats (BED, bedGraph, bigWig, BAM) with 1-based fully closed formats (GFF3, GTF, VCF) causes silent off-by-one errors.
- Converting coordinates between genome builds by eye or simple arithmetic rather than lifting over with a chain file produces corrupted intervals.
- Failing to treat cells as separate biological replicates or treating a failed lift-over row as something to quietly drop rather than a biological finding in an unstable region.
What it runs
Programs
- MACS3Preinstalled on the research machineA peak caller identifying enriched genomic regions from bulk and single-cell ChIP-seq, ATAC-seq, and DNA assays.
- HOMERPreinstalled on the research machineDiscovers sequence motifs and analyses functional genomics sequencing data such as ChIP-seq and RNA-seq.
- bedtoolsPreinstalled on the research machineA command-line suite for intersecting, merging, and analysing genomic intervals across standard bioinformatics formats.
- samtoolsPreinstalled on the research machineA command-line toolsuite for reading, writing, sorting, indexing, and viewing SAM, BAM, and CRAM alignment files.
Databases it can query
nf-core pipelines
Questions
Do I need to install anything to call peaks in atac-seq and chip-seq data?
No. The research agent does this work on a Linux machine of its own — it runs MACS3, HOMER, bedtools, samtools there, keeps the files, and reads the results back to you. Long runs continue if you close the page.
Which peak callers and interval tools are available on the machine?
MACS3 3.0.4, HOMER 5.1, bedtools 2.31.1, and samtools 1.20 are preinstalled on PATH on the research machine, ready to be run without manual environment setup.
Can complete community pipelines be run instead of individual tools?
Yes. The platform can run standard pipelines such as nf-core/atacseq, nf-core/chipseq, and nf-core/cutandrun to handle quality control, peak calling, and downstream analysis across multi-sample projects.
What motif databases can be queried during analysis?
The agent can query JASPAR directly for curated transcription-factor binding profiles, as well as ReMap and ENCODE for comparative public ChIP-seq and regulatory datasets.
How are coordinate discrepancies between BED and GTF handled?
BED files are 0-based and half-open [start, end), whereas GTF/GFF files are 1-based and fully closed. When converting or joining, the agent uses bed_start = pos - 1 and labels coordinate conventions explicitly to avoid off-by-one shifts.
Written from the method the research agent follows for this work and the documentation of the tools listed above. Statements citing a figure that does not appear there are removed before publication. Corollary is a non-commercial research demonstration; results are not for clinical use.