CGAT: computational genomics analysis toolkit.
Computational genomics seeks to draw biological inferences from genomic datasets, often by integrating and contextualizing next-generation sequencing data. CGAT provides an extensive suite of tools designed to assist in the analysis of genome scale data from a range of standard file formats. The too...
Main Authors: | Sims, D, Ilott, N, Sansom, S, Sudbery, I, Johnson, J, Fawcett, K, Berlanga-Taylor, A, Luna-Valero, S, Ponting, C, Heger, A |
---|---|
格式: | Journal article |
語言: | English |
出版: |
Oxford University Press
2014
|
相似書籍
-
CGAT-core: a python framework for building scalable, reproducible computational biology workflows
由: Cribbs, AP, et al.
出版: (2019) -
Sequencing depth and coverage: key considerations in genomic analyses.
由: Sims, D, et al.
出版: (2014) -
Evolutionary rate analyses of orthologs and paralogs from 12 Drosophila genomes.
由: Heger, A, et al.
出版: (2007) -
UMI-tools: Modelling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy.
由: Smith, T, et al.
出版: (2017) -
Predicting long non-coding RNAs using RNA sequencing.
由: Ilott, N, et al.
出版: (2013)