fastGenoGAM: fastGenoGAM: A package providing a framework to analyse...
In gstricker/fastGenoGAM: A GAM based framework for analysis of ChIP-Seq data
Description
Author(s)
See Also
Description
This package allows statistical analysis of genome-wide
data with smooth functions using generalized additive models
based on the implementation from the R-package 'mgcv'. It
provides methods for the statistical analysis of ChIP-Seq data
including inference of protein occupancy, and pointwise and
region-wise differential analysis. Estimation of dispersion and
smoothing parameters is performed by cross-validation. Scaling
of generalized additive model fitting to whole chromosomes is
achieved by parallelization over overlapping genomic intervals.
Author(s)
Maintainer: Georg Stricker georg.stricker@in.tum.de
Authors:
Alexander Engelhardt alexander.engelhardt@ibe.med.uni-muenchen.de
Julien Gagneur gagneur@in.tum.de
See Also
Useful links:
gstricker/fastGenoGAM documentation built on May 17, 2019, 8:56 a.m.
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Description Author(s) See Also
Description
This package allows statistical analysis of genome-wide data with smooth functions using generalized additive models based on the implementation from the R-package 'mgcv'. It provides methods for the statistical analysis of ChIP-Seq data including inference of protein occupancy, and pointwise and region-wise differential analysis. Estimation of dispersion and smoothing parameters is performed by cross-validation. Scaling of generalized additive model fitting to whole chromosomes is achieved by parallelization over overlapping genomic intervals.
Author(s)
Maintainer: Georg Stricker georg.stricker@in.tum.de
Authors:
Alexander Engelhardt alexander.engelhardt@ibe.med.uni-muenchen.de
Julien Gagneur gagneur@in.tum.de
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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