Package: SeqGate 1.17.0
SeqGate: Filtering of Lowly Expressed Features
Filtering of lowly expressed features (e.g. genes) is a common step before performing statistical analysis, but an arbitrary threshold is generally chosen. SeqGate implements a method that rationalize this step by the analysis of the distibution of counts in replicate samples. The gate is the threshold above which sequenced features can be considered as confidently quantified.
Authors:
SeqGate_1.17.0.tar.gz
SeqGate_1.17.0.zip(r-4.5)SeqGate_1.17.0.zip(r-4.4)SeqGate_1.17.0.zip(r-4.3)
SeqGate_1.17.0.tgz(r-4.4-any)SeqGate_1.17.0.tgz(r-4.3-any)
SeqGate_1.17.0.tar.gz(r-4.5-noble)SeqGate_1.17.0.tar.gz(r-4.4-noble)
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SeqGate.pdf |SeqGate.html✨
SeqGate/json (API)
NEWS
# Install 'SeqGate' in R: |
install.packages('SeqGate', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/srialle/seqgate/issues
- data_MiTF_1000genes - Extract of a Transciptome Dataset from Human Melanoma Cell Line
On BioConductor:SeqGate-1.15.0(bioc 3.21)SeqGate-1.16.0(bioc 3.20)
differentialexpressiongeneexpressiontranscriptomicssequencingrnaseq
Last updated 26 days agofrom:9990f13d6c. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
R-4.4-win | OK | Oct 31 2024 |
R-4.4-mac | OK | Oct 31 2024 |
R-4.3-win | OK | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 2024 |
Exports:applySeqGate
Dependencies:abindaskpassBiobaseBiocGenericsBiocManagercrayoncurlDelayedArrayGenomeInfoDbGenomeInfoDbDataGenomicRangeshttrIRangesjsonlitelatticeMatrixMatrixGenericsmatrixStatsmimeopensslR6S4ArraysS4VectorsSparseArraySummarizedExperimentsysUCSC.utilsXVectorzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Filtering of Lowly Expressed Features | SeqGate-package SeqGate |
Performs a Filtering of Lowly Expressed Features | applySeqGate seqGate seqgate |
Extract of a Transciptome Dataset from Human Melanoma Cell Line | data_MITF_1000genes data_MiTF_1000genes data_mitf_1000genes |