GenoGAM 2.0: scalable and efficient implementation of genome-wide generalized additive models for gigabase-scale genomes

GenoGAM 2.0: scalable and efficient implementation of genome-wide generalized additive models for gigabase-scale genomes

Abstract Background GenoGAM (Genome-wide generalized additive models) is a powerful statistical modeling tool for the analysis of ChIP-Seq data with flexible factorial design experiments. However large runtime and memory requirements of its current implementation prohibit its application to gigabase...

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Bibliographic Details
Main Authors: Georg Stricker, Mathilde Galinier, Julien Gagneur
Format: Article
Language:English
Published: BMC 2018-06-01
Series:BMC Bioinformatics
Subjects:
Genome-wide analysis
ChIP-Seq
Generalized additive models
Sparse inverse subset algorithm
Transcription factors
Online Access:http://link.springer.com/article/10.1186/s12859-018-2238-7

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http://link.springer.com/article/10.1186/s12859-018-2238-7

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