bnbc-package: Bandwise normalization and batch correction of Hi-C data

In bnbc: Bandwise normalization and batch correction of Hi-C data

Description

Tools to normalize (several) Hi-C data from replicates.

Details

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The package implements the bnbc method for normalizing Hi-C data across samples. The name is short for band-wise normalization and batch correction. The main workhorse is the bnbc function. We recommend using smoothing and library size normalization first.

The package implements the ContactGroup class for storing multiple Hi-C contact matrices. This is most naturally done with one object per chromosome, which is ugly.

We also have functions for applying over a ContactGroup (cgApply) and working with matrix bands band, getBandIdx.

Author(s)

Kipper Fletez-Brant [cre, aut], Kasper Daniel Hansen [aut]

Maintainer: Kipper Fletez-Brant <[e-mail]>

References

Fletez-Brant et al. Distance-dependent between-sample normalization for Hi-C experiments. In preparation.

See Also

bnbc, ContactGroup, band, cgApply.

Examples

data(cgEx)
batches <- colData(cgEx)$Batch
cgEx.cpm <- logCPM(cgEx)
cgEx.smooth <- boxSmoother(cgEx, 5, mc.cores=1)
cgEx.bnbc <- bnbc(cgEx.smooth, batches, 1e7, 4e4, bstart=2, nbands=4)

bnbc documentation built on Nov. 8, 2020, 8:15 p.m.