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by EpiNexus Team announcementrelease

What's new in EpiNexus since February

In February we wrote about why we built EpiNexus. Since then it has become an invite-only pilot, and almost every step of an analysis has changed. The biggest changes follow the same idea: do each step the way published standards and pipelines do it, and show the researcher where each number comes from. Here are the changes you would notice most, as of EpiNexus 1.5.

Bring in public data without downloading it

You can import data from GEO, SRA or ENA by accession: a series (GSE), a sample (GSM), SRA projects, experiments or runs, or a BioProject or BioSample. EpiNexus lists the samples and fills in each one's target, condition, replicate and controls from the archive's records, for you to confirm. It then copies the reads straight from the archive into your project and checks each file against the archive's MD5 checksum. Runs that ENA holds no FASTQ files for are fetched from SRA and converted. The samples stay editable afterwards.

Quality control graded by published standards

Since EpiNexus 1.2.7, each library is graded against the lines for what it profiled. A narrow histone mark, a broad histone mark, a transcription factor, an ATAC-seq library and a CUT&Tag library each have their own lines, taken from ENCODE and the methods' own papers. Depth is counted in usable fragments, as the standards count it.

There are four grades: Good, Marginal, Below minimum and Fail. Only Fail fails a sample, and only at ENCODE's error level or after a technical failure. Our post Is my ChIP-seq or CUT&Tag data good enough? explains the lines.

Differential analysis as the field does it

  • DESeq2 in R is the default test, with csaw for broad marks such as H3K27me3.
  • Sharp histone marks such as H3K27ac are counted over regions from one peak call on all the libraries pooled, as Lun and Smyth recommend. A narrow window around each summit would miss much of a histone mark's signal.
  • Every pair of conditions is compared, unless you choose which ones. A paired design is available when replicates were processed together.
  • The whole table of tested regions can be downloaded, not only the significant ones.

From regions to biology

  • Gene Ontology enrichment follows GREAT's rules: each gene gets a regulatory domain around its start, and regions are tested against the genome, not against a list of nearest genes.
  • Motifs in changed regions: EpiNexus tests which transcription factor motifs are enriched in gained or lost regions, compared with the other tested regions. Before, it only tested which motifs are common in all peaks, which is a different question.
  • Enhancer–gene links follow the rules of the activity-by-contact (ABC) model. When the only activity data is H3K27ac, without an accessibility assay, EpiNexus calls the result an ABC-style approximation.
  • H3K27ac and H3K27me3 read together: when a run holds both marks, each gene is grouped by what both marks did at its promoter.
  • A genome browser is built in, and each track can also be opened in the UCSC Genome Browser.

The Regulatory Atlas

The largest addition compares your results with public chromatin data of many tissues. It shows what kinds of regulatory element your gained and lost regions fall on, and in which tissues these elements are normally active. The data are:

  • ENCODE's registry of candidate regulatory elements;
  • chromatin states of 833 human reference samples (EpiMap) and of mouse fetal tissues;
  • ENCODE's DNase accessibility of 298 mouse samples.

It works for ChIP-seq, ATAC-seq, CUT&RUN and CUT&Tag runs on human (hg38) and mouse (mm10, mm39) genomes, and starts by itself when a new run finishes.

The Atlas also checks each sample's identity. If you give a sample's tissue on the Samples page, EpiNexus says whether the sample's peaks look like that tissue: Consistent, May not match, Unclear or Not checked. A mismatch can reveal a swapped or mislabelled sample. It is a warning, never a QC failure, and it is done for ATAC-seq and active histone marks such as H3K27ac.

DNA methylation

  • The library type is detected from the reads. RRBS reads start at the cut site of the enzyme MspI, so EpiNexus can tell RRBS from WGBS before the run starts. RRBS reads are not deduplicated, as the Bismark authors advise.
  • Differentially methylated regions (DMRs) are called with dmrseq. When none reaches significance, the strongest candidates are shown, labelled as not significant, with the reason.
  • Context: each DMR is placed on a CpG island, shore, shelf or the open sea, and compared with the CpGs that were tested.
  • Bisulfite QC sits on the Quality Control page. It grades conversion against ENCODE's 98 %.

Results you can publish and repeat

  • Methods text is written from what the run actually did, with every tool's version and the references. It comes with a report and a GEO submission package.
  • Each run records its environment: the software image it ran in, the reference genome and the settings. Run again starts a new run with the same samples and settings on the current software.
  • Large files, such as signal tracks and aligned reads, download through links, and deleted runs can be restored for 7 days.

Also new

  • Spike-in normalisation works with any installed genome of another species, and each read is given to one species only.
  • Genome lists show only the genomes that are installed. Each genome is built from downloads checked against the provider's checksums where the provider publishes them, and human analyses use the no-alt analysis set.

The free book explains each of these steps in depth: Epigenomics Data Analysis with EpiNexus. EpiNexus is in an invite-only pilot: ask for access.

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