Package: BisqueRNA 1.0.5

Brandon Jew

BisqueRNA: Decomposition of Bulk Expression with Single-Cell Sequencing

Provides tools to accurately estimate cell type abundances from heterogeneous bulk expression. A reference-based method utilizes single-cell information to generate a signature matrix and transformation of bulk expression for accurate regression based estimates. A marker-based method utilizes known cell-specific marker genes to measure relative abundances across samples. For more details, see Jew and Alvarez et al (2019) <doi:10.1101/669911>.

Authors:Brandon Jew [aut, cre], Marcus Alvarez [aut]

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BisqueRNA/json (API)

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

Peer review:

Bug tracker:https://github.com/cozygene/bisque/issues

On CRAN:

6 exports 68 stars 3.56 score 6 dependencies 110 scripts 855 downloads

Last updated 3 years agofrom:8640250dff. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 04 2024
R-4.5-winOKSep 04 2024
R-4.5-linuxOKSep 04 2024
R-4.4-winOKSep 04 2024
R-4.4-macOKSep 04 2024
R-4.3-winOKSep 04 2024
R-4.3-macOKSep 04 2024

Exports:CalculateSCCellProportionsGenerateSCReferenceMarkerBasedDecompositionReferenceBasedDecompositionSeuratToExpressionSetSimulateData

Dependencies:BiobaseBiocGenericslimSolvelpSolveMASSquadprog

Bisque Example Usage

Rendered frombisque.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2019-06-04
Started: 2019-05-30

Readme and manuals

Help Manual

Help pageTopics
Calculate cell proportions based on single-cell dataCalculateSCCellProportions
Correlate columns of data frameCorTri
Convert counts data in Expression Set to counts per million (CPM)CountsToCPM
Estimate cell type proportions using first PC of expression matrixEstimatePCACellTypeProportions
Remove genes in Expression Set with zero expression in all samplesFilterUnexpressedGenes
Remove genes in Expression Set with zero variance across samplesFilterZeroVarianceGenes
Generate reference profile for cell types identified in single-cell dataGenerateSCReference
Return cell type proportions from bulkGetCTP
Get number of genes to use with no weighted informationGetNumGenes
Get number of genes to use with weighted PCAGetNumGenesWeighted
Find overlapping genes in single-cell data, bulk data, and marker genesGetOverlappingGenes
Find overlapping samples in single-cell and bulk dataGetOverlappingSamples
Get unique markers present in only 1 cell typeGetUniqueMarkers
Performs marker-based decomposition of bulk expression using marker genesMarkerBasedDecomposition
Performs reference-based decomposition of bulk expression using single-cell dataReferenceBasedDecomposition
Transforms bulk expression of a gene using only single-cell dataSemisupervisedTransformBulk
Converts Seurat object to Expression SetSeuratToExpressionSet
Simulate barcode for decomposition illustrationSimulateBarcode
Simulate data for decomposition illustrationSimulateData
Transforms bulk expression of a gene given overlapping dataSupervisedTransformBulk