Everything you need to go from raw sequencing data to publication-ready figures — all from your browser.
Automatically find enriched regions in your data: MACS3 for ChIP-seq and ATAC-seq, SEACR (or GoPeaks) for CUT&Tag and CUT&RUN. Sharp marks and transcription factors get narrow peaks, broad marks such as H3K27me3 get broad domains. Blacklisted regions are removed and replicate reproducibility is checked (IDR or overlap).
See exactly where each peak lands — at a promoter (within 1, 2 or 3 kb of a TSS), in a UTR, exon or intron, downstream of a gene, or in a distal intergenic region. Every peak is linked to its nearest gene automatically.
Compare conditions (e.g. treated vs. control) to find regions that gain or lose signal. Uses DESeq2 (in R, with shrunken fold changes), or csaw for broad marks, with spike-in calibration when your libraries carry a spike-in. Sharp histone marks such as H3K27ac are tested on regions from one peak call on the pooled libraries. Volcano, MA, PCA and heatmap views, plus result tables.
Discover the large, highly active regulatory regions that drive cell identity. For H3K27ac, MED1 or BRD4 data, EpiNexus stitches nearby peaks, ranks them by signal, and separates super-enhancers from typical enhancers.
Analyse H3K27ac and H3K27me3 together in one run and read their changes at each gene's promoter (3 kb either side of the start site). Genes are grouped by what both marks did — for example H3K27ac gained and H3K27me3 lost — with changes within 100 kb shown beside, a flow chart and a gene table you can download.
Find out which genes each enhancer or regulatory region likely controls, with the Activity-by-Contact (ABC) model's rules: element activity from your ATAC-seq, DNase-seq or H3K27ac reads, contact estimated from genomic distance, within 5 Mb. With H3K27ac alone, the links are labelled an ABC-style approximation.
Which biological processes do your gained and lost regions point to? GREAT-style enrichment links regions to nearby genes and tests Gene Ontology terms, for each comparison and each sample.
Find the transcription-factor motifs enriched in your peaks (MEME AME), and those enriched in the regions that gained or lost signal compared with unchanged regions of the same GC content (MEME SEA, and monaLisa along the fold change). Motifs come from JASPAR 2024 for your organism and are grouped by TF family.
See the signal around your peaks in every sample, input included: tornado heatmaps and average profiles on a shared scale, plus a sample-correlation matrix (deepTools).
Chromatin accessibility with ATAC-specific processing (Tn5 shift, mitochondrial reads removed) and QC: fragment-size distribution, TSS enrichment, FRiP. Find regions that become more open or more closed between conditions.
Bisulfite sequencing (WGBS or RRBS — detected from the reads) aligned with Bismark; differentially methylated regions with dmrseq, placed in their CpG-island context; bisulfite QC with coverage, conversion and M-bias plots. When nothing is significant, the strongest candidate regions are shown and labelled.
Look at your signal tracks, peaks and reads in an IGV browser inside the app, jump there from any differential peak, or open the same tracks in IGV desktop or the UCSC Genome Browser.
After each run, EpiNexus places your changed regions and peaks in public chromatin data: which ENCODE regulatory elements they overlap, and in which tissues these elements are active enhancers, promoters or Polycomb regions. For human (hg38) and mouse (mm10, mm39).
Give each sample its tissue, and for accessibility and active histone marks EpiNexus checks after the run whether the sample's peaks look like that tissue. A mismatch can reveal a swapped or mislabelled sample. It is a warning, never a failure.
The atlas is built from public data whose licences allow its use, in versioned releases. The Data sources page lists every source with its version, licence and what to cite, and the methods text describes the comparison.
Every run reports usable fragments, how well reads mapped, duplication, library complexity, signal-to-noise (FRiP), fragment sizes and TSS enrichment — graded against published standards for each kind of sample (Good, Marginal, Below minimum or Fail), explained in plain language, and collected in a MultiQC report.
Drag and drop your FASTQ or BAM files in the browser — uploads resume after a dropped connection and every transfer is verified. Or type a GEO, SRA or ENA accession and the reads go straight from the archive into your project.
Before a run starts, EpiNexus checks your design — controls, replicates, genome, library type — and tells you what to fix. During the run you see each step's progress; afterwards, clear messages for anything that went wrong. Re-run with corrected settings — your uploads are preserved.
Every run records the software image, the tool versions, the exact commands, the settings and the reference genome it used. EpiNexus writes a methods section for your paper, prepares a GEO submission package, and runs an analysis again with one click.
Download the main figures as PNG or SVG, any table as a tab-separated file, a full report (HTML or Markdown, or PDF from your browser), or a zip of the run's peaks and tables. Large files — signal tracks, alignments and methylation calls — come as direct download links, valid for 24 hours.
Each project belongs to its owner. Runs execute on their own temporary cloud machine, and deleting a project removes its files and results.