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

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-scale ge...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	BMC bioinformatics Ročník 19; číslo 1; s. 247 - 9
Hlavní autori:	Stricker, Georg, Galinier, Mathilde, Gagneur, Julien
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 27.06.2018 BioMed Central Ltd Springer Nature B.V BMC
Predmet:	Algorithms Applied mathematics Binomial distribution Bioinformatics Biomedical and Life Sciences ChIP-Seq Cholesky factorization Chromatin Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer memory Data processing Factorial design Generalized additive models Genome-wide analysis Genomes Genomic libraries Genomics Genomics - methods Humans Life Sciences Mathematical models Microarrays Parameters Proteins Results and data Scale (ratio) Software Sparse inverse subset algorithm Sparsity Statistical analysis Statistical models Transcription factors Yeast Transcription factors ChIP-Seq Sparse inverse subset algorithm Generalized additive models Genome-wide analysis
ISSN:	1471-2105, 1471-2105
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!