recipe bioconductor-narrowpeaks

Shape-based Analysis of Variation in ChIP-seq using Functional PCA






The package applies a functional version of principal component analysis (FPCA) to: (1) Postprocess data in wiggle track format, commonly produced by generic ChIP-seq peak callers, by applying FPCA over a set of read-enriched regions (ChIP-seq peaks). This is done to study variability of the the peaks, or to shorten their genomic locations accounting for a given proportion of variation among the enrichment-score profiles. (2) Analyse differential variation between multiple ChIP-seq samples with replicates. The function 'narrowpeaksDiff' quantifies differences between the shapes, and uses Hotelling's T2 tests on the functional principal component scores to identify significant differences across conditions. An application of the package for Arabidopsis datasets is described in Mateos, Madrigal, et al. (2015) Genome Biology: 16:31.

package bioconductor-narrowpeaks

(downloads) docker_bioconductor-narrowpeaks



Required By


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-narrowpeaks

and update with:

conda update bioconductor-narrowpeaks

or use the docker container:

docker pull<tag>

(see bioconductor-narrowpeaks/tags for valid values for <tag>)