Package: SpeCond 1.61.0

Florence Cavalli

SpeCond: Condition specific detection from expression data

This package performs a gene expression data analysis to detect condition-specific genes. Such genes are significantly up- or down-regulated in a small number of conditions. It does so by fitting a mixture of normal distributions to the expression values. Conditions can be environmental conditions, different tissues, organs or any other sources that you wish to compare in terms of gene expression.

Authors:Florence Cavalli

SpeCond_1.61.0.tar.gz
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SpeCond.pdf |SpeCond.html
SpeCond/json (API)

# Install 'SpeCond' in R:
install.packages('SpeCond', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On BioConductor:SpeCond-1.61.0(bioc 3.21)SpeCond-1.60.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarraydifferentialexpressionmultiplecomparisonclusteringreportwriting

3.89 score 13 scripts 250 downloads 3 mentions 14 exports 12 dependencies

Last updated 23 days agofrom:84f04f80e3. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winNOTENov 19 2024
R-4.5-linuxNOTENov 19 2024
R-4.4-winNOTENov 19 2024
R-4.4-macNOTENov 19 2024
R-4.3-winNOTENov 19 2024
R-4.3-macNOTENov 19 2024

Exports:createParameterMatrixfitNoPriorWithExclusionfitPriorgetDefaultParametergetFullHtmlSpeCondResultgetGeneHtmlPagegetMatrixFromExpressionSetgetProfilegetSpecificOutliersStep1getSpecificResultSpeCondwriteGeneResultwriteSpeCondResultwriteUniqueProfileSpecificResult

Dependencies:BiobaseBiocGenericsdotCall64fieldsgenericshwritermapsmclustRColorBrewerRcppspamviridisLite

SpeCond

Rendered fromSpeCond.Rnwusingutils::Sweaveon Nov 19 2024.

Last update: 2013-11-01
Started: 2013-11-01