Package: aggregateBioVar 1.17.0

Jason Ratcliff

aggregateBioVar: Differential Gene Expression Analysis for Multi-subject scRNA-seq

For single cell RNA-seq data collected from more than one subject (e.g. biological sample or technical replicates), this package contains tools to summarize single cell gene expression profiles at the level of subject. A SingleCellExperiment object is taken as input and converted to a list of SummarizedExperiment objects, where each list element corresponds to an assigned cell type. The SummarizedExperiment objects contain aggregate gene-by-subject count matrices and inter-subject column metadata for individual subjects that can be processed using downstream bulk RNA-seq tools.

Authors:Jason Ratcliff [aut, cre], Andrew Thurman [aut], Michael Chimenti [ctb], Alejandro Pezzulo [ctb]

aggregateBioVar_1.17.0.tar.gz
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aggregateBioVar.pdf |aggregateBioVar.html
aggregateBioVar/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/jasonratcliff/aggregatebiovar/issues

Datasets:

On BioConductor:aggregateBioVar-1.17.0(bioc 3.21)aggregateBioVar-1.16.0(bioc 3.20)

softwaresinglecellrnaseqtranscriptomicstranscriptiongeneexpressiondifferentialexpression

4.95 score 5 stars 18 scripts 362 downloads 6 exports 41 dependencies

Last updated 23 days agofrom:76d82e68b2. Checks:OK: 3 WARNING: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-winWARNINGNov 08 2024
R-4.5-linuxWARNINGNov 08 2024
R-4.4-winWARNINGNov 08 2024
R-4.4-macOKNov 08 2024
R-4.3-winWARNINGNov 08 2024
R-4.3-macOKNov 08 2024

Exports:aggregateBioVarcountsByCellcountsBySubjectscSubjectssubjectMetaDatasummarizedCounts

Dependencies:abindaskpassBiobaseBiocGenericsclicrayoncurlDelayedArrayfansigenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesgluehttrIRangesjsonlitelatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmimeopensslpillarpkgconfigR6rlangS4ArraysS4VectorsSingleCellExperimentSparseArraySummarizedExperimentsystibbleUCSC.utilsutf8vctrsXVectorzlibbioc

Multi-subject scRNA-seq Analysis

Rendered frommulti-subject-scRNA-seq.Rmdusingknitr::rmarkdownon Nov 08 2024.

Last update: 2020-09-03
Started: 2020-09-03