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 peaks that gain or lose signal. Uses DESeq2 statistics (PyDESeq2), or csaw for broad marks, with spike-in calibration when your libraries carry a spike-in. 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.
When a project has differential results for both H3K27ac and H3K27me3, compare them gene by gene: activated, repressed, both gained, poised, or stable — with a diagram of how each mark changed and a gene table.
Find out which genes each enhancer or regulatory region likely controls, with the Activity-by-Contact (ABC) model: element activity from your reads, contact estimated from genomic distance, up to 1 Mb.
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, tested with MEME AME against the JASPAR 2024 collection for your organism, with sequence logos to compare motifs.
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; bisulfite QC with coverage, conversion and M-bias plots.
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.
Every run reports how well reads mapped, duplication, library complexity, signal-to-noise (FRiP), fragment sizes and TSS enrichment — graded against ENCODE standards, 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 tool versions, the exact commands and the reference genome it used. EpiNexus writes a methods section for your paper and prepares a GEO submission package.
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, signal tracks, alignments and tables.
Each project belongs to its owner. Runs execute on their own temporary cloud machine, and deleting a project removes its files and results.