Package: DGEobj.utils 1.0.6
DGEobj.utils: Differential Gene Expression (DGE) Analysis Utility Toolkit
Provides a function toolkit to facilitate reproducible RNA-Seq Differential Gene Expression (DGE) analysis (Law (2015) <doi:10.12688/f1000research.9005.3>). The tools include both analysis work-flow and utility functions: mapping/unit conversion, count normalization, accounting for unknown covariates, and more. This is a complement/cohort to the 'DGEobj' package that provides a flexible container to manage and annotate Differential Gene Expression analysis results.
Authors:
DGEobj.utils_1.0.6.tar.gz
DGEobj.utils_1.0.6.zip(r-4.5)DGEobj.utils_1.0.6.zip(r-4.4)DGEobj.utils_1.0.6.zip(r-4.3)
DGEobj.utils_1.0.6.tgz(r-4.4-any)DGEobj.utils_1.0.6.tgz(r-4.3-any)
DGEobj.utils_1.0.6.tar.gz(r-4.5-noble)DGEobj.utils_1.0.6.tar.gz(r-4.4-noble)
DGEobj.utils_1.0.6.tgz(r-4.4-emscripten)DGEobj.utils_1.0.6.tgz(r-4.3-emscripten)
DGEobj.utils.pdf |DGEobj.utils.html✨
DGEobj.utils/json (API)
NEWS
# Install 'DGEobj.utils' in R: |
install.packages('DGEobj.utils', repos = c('https://cb4ds.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cb4ds/dgeobj.utils/issues
Last updated 2 years agofrom:5ddde6ff86. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 05 2024 |
R-4.5-win | NOTE | Sep 05 2024 |
R-4.5-linux | NOTE | Sep 05 2024 |
R-4.4-win | NOTE | Sep 05 2024 |
R-4.4-mac | NOTE | Sep 05 2024 |
R-4.3-win | OK | Sep 05 2024 |
R-4.3-mac | OK | Sep 05 2024 |
Exports:convertCountsextractCollowIntFilterrsqCalcrunContrastsrunEdgeRNormrunIHWrunPowerrunQvaluerunSVArunVoomsummarizeSigCountstopTable.mergetpm.directtpm.on.subset
Dependencies:assertthatcliDGEobjdplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigR6rlangstringistringrtibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
DGEobj.utils Package Overview | DGEobj.utils-package |
Convert count matrix to CPM, FPKM, FPK, or TPM | convertCounts |
Extract a named column from a series of df or matrices | extractCol |
Apply low intensity filters to a DGEobj | lowIntFilter |
Calculate R-squared for each gene fit | rsqCalc |
Build contrast matrix and calculate contrast fits | runContrasts |
Run edgeR normalization on DGEobj | runEdgeRNorm |
Apply Independent Hypothesis Weighting (IHW) to a list of topTable dataframes | runIHW |
Run a power analysis on counts and design matrix | runPower |
Calculate and add q-value and lFDR to dataframe | runQvalue |
Test for surrogate variables | runSVA |
Run functions in a typical voom/lmFit workflow | runVoom |
Summarize a contrast list | summarizeSigCounts |
Merge specified topTable df cols | topTable.merge |
Convert countsMatrix and geneLength to TPM units | tpm.direct |
Calculate TPM for a subsetted DGEobj | tpm.on.subset |