Package: scry 1.25.0

Kelly Street

scry: Small-Count Analysis Methods for High-Dimensional Data

Many modern biological datasets consist of small counts that are not well fit by standard linear-Gaussian methods such as principal component analysis. This package provides implementations of count-based feature selection and dimension reduction algorithms. These methods can be used to facilitate unsupervised analysis of any high-dimensional data such as single-cell RNA-seq.

Authors:Kelly Street [aut, cre], F. William Townes [aut, cph], Davide Risso [aut], Stephanie Hicks [aut]

scry_1.25.0.tar.gz
scry_1.25.0.zip(r-4.7-any)scry_1.25.0.zip(r-4.6-any)scry_1.25.0.zip(r-4.5-any)
scry_1.25.0.tgz(r-4.6-any)scry_1.25.0.tgz(r-4.5-any)
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scry_1.25.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
scry/json (API)

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

Bug tracker:https://github.com/kstreet13/scry/issues

On BioConductor:scry-1.25.0(bioc 3.24)scry-1.24.0(bioc 3.23)

dimensionreductiongeneexpressionnormalizationprincipalcomponentrnaseqsoftwaresequencingsinglecelltranscriptomics

6.99 score 25 stars 1 packages 262 scripts 827 downloads 1 mentions 3 exports 36 dependencies

Last updated from:abf8f7fa96. Checks:1 NOTE, 7 WARNING, 1 ERROR, 1 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE201
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source / vignettesERROR326
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macos-oldrelWARNING206
windows-develWARNING975
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Exports:devianceFeatureSelectionGLMPCAnullResiduals

Dependencies:abindassortheadbeachmatBHBiobaseBiocGenericsBiocParallelBiocSingularcodetoolscpp11DelayedArrayformatRfutile.loggerfutile.optionsgenericsGenomicRangesglmpcaIRangesirlbalambda.rlatticeMASSMatrixMatrixGenericsmatrixStatsRcpprsvdS4ArraysS4VectorsScaledMatrixSeqinfoSingleCellExperimentsnowSparseArraySummarizedExperimentXVector

Readme and manuals

Help Manual

Help pageTopics
Feature selection by approximate multinomial deviancedevianceFeatureSelection devianceFeatureSelection,DelayedArray-method devianceFeatureSelection,Matrix-method devianceFeatureSelection,matrix-method devianceFeatureSelection,SummarizedExperiment-method
Generalized principal components analysis for non-normally distributed dataGLMPCA GLMPCA,Matrix-method GLMPCA,matrix-method GLMPCA,SummarizedExperiment-method
Residuals from an approximate multinomial null modelnullResiduals nullResiduals,ANY-method nullResiduals,Matrix-method nullResiduals,matrix-method nullResiduals,SingleCellExperiment-method nullResiduals,SummarizedExperiment-method