geva-package: geva: Gene Expression Variation Analysis (GEVA)

In sbcblab/geva: Gene Expression Variation Analysis (GEVA)

Description

Statistic methods to evaluate variations of differential expression (DE) between multiple biological conditions. It takes into account the fold-changes and p-values from previous differential expression (DE) results that use large-scale data (*e.g.*, microarray and RNA-seq) and evaluates which genes would react in response to the distinct experiments. This evaluation involves an unique pipeline of statistical methods, including weighted summarization, quantile detection, cluster analysis, and ANOVA tests, in order to classify a subset of relevant genes whose DE is similar or dependent to certain biological factors.

Statistic methods to evaluate variation between multiple biological conditions.

Author(s)

Maintainer: Itamar José Guimarães Nunes [e-mail] (ORCID)

Other contributors:

• Murilo Zanini David [e-mail] [contributor]

• Bruno César Feltes [e-mail] (ORCID) [contributor]

• Marcio Dorn [e-mail] (ORCID) [contributor]

See Also

Useful links:

• https://github.com/sbcblab/geva

sbcblab/geva documentation built on March 15, 2021, 10:08 p.m.