Package: MBttest 1.33.0

Yuan-De Tan

MBttest: Multiple Beta t-Tests

MBttest method was developed from beta t-test method of Baggerly et al(2003). Compared to baySeq (Hard castle and Kelly 2010), DESeq (Anders and Huber 2010) and exact test (Robinson and Smyth 2007, 2008) and the GLM of McCarthy et al(2012), MBttest is of high work efficiency,that is, it has high power, high conservativeness of FDR estimation and high stability. MBttest is suit- able to transcriptomic data, tag data, SAGE data (count data) from small samples or a few replicate libraries. It can be used to identify genes, mRNA isoforms or tags differentially expressed between two conditions.

Authors:Yuan-De Tan

MBttest_1.33.0.tar.gz
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NEWS

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

Peer review:

Datasets:
  • dat - The Transcriptomic data and t-test results.
  • jkttcell - Jurkat T-cell Transcritomic Data
  • skjt - Simulated Null Transcriptomic data

On BioConductor:MBttest-1.33.0(bioc 3.20)MBttest-1.32.0(bioc 3.19)

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

bioconductor-package

13 exports 1.00 score 5 dependencies

Last updated 2 months agofrom:46a7e7ae58

Exports:betaparametabbetaparametVPbetaparametwbetattestmaplotmbetattestmtproceduremtpvadjustmyheatmapoddratiopratiosimulatsmbetattest

Dependencies:bitopscaToolsgplotsgtoolsKernSmooth

Analysing RNA-Seq count data with the "MBttest" package

Rendered fromMBttest.Rnwusingutils::Sweaveon Jul 01 2024.

Last update: 2018-04-28
Started: 2016-02-25