bioconductor-extrachips

name	bioconductor-extrachips
description	This package builds on existing tools and adds some simple but extremely useful capabilities for working wth ChIP-Seq data. The focus is on detecting differential binding windows/regions. One set of functions focusses on set-operations retaining mcols for GRanges objects, whilst another group of functions are to aid visualisation of results. Coercion to tibble objects is also implemented.

extraChIPs

Workflows

Standard Workflow

This package builds on existing tools and adds some simple but extremely useful capabilities for working wth ChIP-Seq data. The focus is on detecting differential binding windows/regions. One set of functions focusses on set-operations retaining mcols for GRanges objects, whilst another group of functions are to aid visualisation of results. Coercion to tibble objects is also implemented.

library(extraChIPs)
library(GenomicRanges)

# Define chromosome information
sq <- defineSeqinfo("GRCh37")

# Create mock GRangesList for consensus peak calling
gr1 <- GRanges("chr10:1000-2000", seqinfo = sq)
gr2 <- GRanges("chr10:1200-2200", seqinfo = sq)
peaks <- GRangesList(sample1 = gr1, sample2 = gr2)

# Generate consensus peaks
consensus <- makeConsensus(peaks, p = 0.5)

# Plot overlaps
plotOverlaps(peaks)

Input: A GRangesList of peak calls; Output: A consensus GRanges object and overlap plots.

When to Use

• Consensus Peak Definition: To define consensus peaks across replicates using makeConsensus.
• Peak Importing and Filtering: To import and filter peaks with blacklists/greylists using importPeaks.
• Differential Signal Analysis: To perform differential signal analysis on window/region counts using fitAssayDiff.
• Gene Mapping: To map peaks/regions to genes and promoters using mapByFeature.
• Visualization: To visualize peak overlaps with plotOverlaps and signal profiles with plotProfileHeatmap or getProfileData.

When NOT to Use

• De Novo Motif Discovery: For de novo motif discovery, use memes or universalmotif instead.
• De Novo Peak Calling: For peak calling itself, use MACS2 or epigraHMM as extraChIPs is designed for downstream analysis of existing peak calls.

Data Requirements

• Peak Files: Peak files in narrowPeak format or GRanges objects.
• Read Counts: BAM files for read counting, or a pre-computed RangedSummarizedExperiment object.
• Annotations: Annotation files (GTF/GFF) for mapping peaks to genes.

Key Parameters

• p (0.5): Minimum proportion of replicates in which a peak must be present to be included in the consensus.
• norm ("TMM"): Normalization method in fitAssayDiff (e.g., "TMM" or library-size).
• fc (1.2): Fold-change threshold incorporated into testing in fitAssayDiff.
• asRanges (TRUE): Logical indicating whether to return results as a GRanges object.
• upstream (2500): Upstream distance for defining promoters.
• downstream (500): Downstream distance for defining promoters.

Best Practices

• Define Seqinfo: Define a consistent Seqinfo object at the start of the workflow using defineSeqinfo.
• Exclude Artifacts: Exclude blacklisted and grey-listed regions using importPeaks to avoid false positives.
• Normalization Check: Test whether group-specific count distributions are similar using quantro before applying TMM normalization.
• Classify Status: Use addDiffStatus to classify regions as "Increased", "Decreased", or "Unchanged" for downstream visualization.

Common Pitfalls

• Inappropriate Normalization: Applying TMM normalization when group-specific distributions differ significantly; use quantro to test this assumption first.
• Metadata Loss: Losing metadata columns during GRanges set operations; use reduceMC or makeConsensus to retain metadata.
• Mapping Coordinates: Mapping peaks to genes without resetting the core ranges; use colToRanges to restore the original peak boundaries before mapping.

Alternatives

• DiffBind: For standard affinity-based differential analysis.
• csaw: For sliding window-based differential binding analysis.
• ChIPseeker: For peak annotation and visualization.

Citations

• Ross-Innes et al. 2012, Nature (for DiffBind-style approaches)
• Hicks and Irizarry 2015, Genome Biol. (for quantro)

References

• Homepage: bioconductor.org/packages/extraChIPs
• Vignette: https://bioconductor.org/packages/release/bioc/vignettes/extraChIPs/inst/doc/extraChIPs.html