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

Bioconductor version: Release (3.1)

The package applies a functional version of principal component analysis (FPCA) to: (1) Process data in wiggle track format (WIG) commonly produced by ChIP-Seq peak callers by applying FPCA over a set of read-enriched regions (ChIP-Seq peaks). This is done in order to shorten the genomic locations accounting for a given proportion of variation among the enrichment-score profiles. The function 'narrowpeaks' allows splitting and trimming binding sites in close proximity to each other, narrowing down the length of the putative transcription factor binding sites while preserving the information present in the variability of the dataset and capturing major sources of variation. (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.

Author: Pedro Madrigal <pm59 at>, Pawel Krajewski <pkra at>

Maintainer: Pedro Madrigal <pmb59 at>

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PDF R Script NarrowPeaks Vignette. Shape-based splitting and trimming ChIP-Seq peaks using functional Principal Components
PDF   Reference Manual
Text   NEWS


biocViews ChIPSeq, Genetics, Sequencing, Software, Transcription, Visualization
Version 1.12.0
In Bioconductor since BioC 2.10 (R-2.15) (3.5 years)
License Artistic-2.0
Depends R (>= 2.10.0), splines
Imports BiocGenerics, S4Vectors, IRanges, GenomicRanges, GenomeInfoDb, fda, CSAR, ICSNP
Suggests rtracklayer, BiocStyle, GenomicRanges, CSAR
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