Package: sincell 1.39.0

Miguel Julia

sincell: R package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data

Cell differentiation processes are achieved through a continuum of hierarchical intermediate cell-states that might be captured by single-cell RNA seq. Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework. Furthermore, Sincell contributes new algorithms to provide cell-state hierarchies with statistical support while accounting for stochastic factors in single-cell RNA seq. Graphical representations and functional association tests are provided to interpret hierarchies.

Authors:Miguel Julia <[email protected]>, Amalio Telenti <[email protected]>, Antonio Rausell <[email protected]>

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sincell.pdf |sincell.html
sincell/json (API)
NEWS

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • ExpressionMatrix - Single-cell expression data for genes differentially expressed in differentiating human skeletal muscle myoblasts cells
  • geneset.list - Example of a geneset collection

On BioConductor:sincell-1.39.0(bioc 3.21)sincell-1.38.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncologysequencingrnaseqclusteringgraphandnetworkvisualizationgeneexpressiongenesetenrichmentbiomedicalinformaticscellbiologyfunctionalgenomicssystemsbiology

4.00 score 6 scripts 221 downloads 1 mentions 17 exports 50 dependencies

Last updated 2 months agofrom:e455929c5b. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-win-x86_64NOTENov 20 2024
R-4.5-linux-x86_64NOTENov 20 2024
R-4.4-win-x86_64NOTENov 20 2024
R-4.4-mac-x86_64NOTENov 20 2024
R-4.4-mac-aarch64NOTENov 20 2024
R-4.3-win-x86_64NOTENov 20 2024
R-4.3-mac-x86_64NOTENov 20 2024
R-4.3-mac-aarch64NOTENov 20 2024

Exports:f_distance2vectorknnalgorithmpseudoreplicatesbymodelpseudoreplicatesbynoisepseudoreplicatesbynoise_cv2sc_AssociationOfCellsHierarchyWithAGeneSetsc_clusterObjsc_ComparissonOfGraphssc_DimensionalityReductionObjsc_distanceObjsc_GraphBuilderObjsc_InitializingSincellObjectsc_InSilicoCellsReplicatesObjsc_marker2colorsc_StatisticalSupportByGeneSubsamplingsc_StatisticalSupportByReplacementWithInSilicoCellsReplicatessstalgorithm

Dependencies:cliclustercodetoolscolorspacecpp11dotCall64entropyfansifarverfastICAfieldsforeachggplot2gluegtableigraphisobanditeratorslabelinglatticelifecyclemagrittrmapsMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrproxyR6RColorBrewerRcppreshape2rlangRtsnescalesscatterplot3dspamstatmodstringistringrtibbleTSPutf8vctrsviridisLitewithr

Sincell: Analysis of cell state hierarchies from single-cell RNA-seq

Rendered fromsincell-vignette.Rnwusingknitr::knitron Nov 20 2024.

Last update: 2022-10-07
Started: 2015-01-23

Readme and manuals

Help Manual

Help pageTopics
Single-cell expression data for genes differentially expressed in differentiating human skeletal muscle myoblasts cellsExpressionMatrix
Conversion of the lower triangular matrix of a distance matrix into an arrayf_distance2vector
Example of a geneset collectiongeneset.list
Auxiliary function for KNN and IMC algorithmsknnalgorithm
Auxiliary function of sc_InSilicoCellsReplicatesObj function used when its parameter method="lognormal-3parameters"pseudoreplicatesbymodel
Auxiliary function of sc_InSilicoCellsReplicatesObj function used when its parameter method="variance.deciles"pseudoreplicatesbynoise
Auxiliary function of sc_InSilicoCellsReplicatesObj function used when its parameter method="cv2.deciles"pseudoreplicatesbynoise_cv2
Association of a cell-state hierarchy with a functional gene setsc_AssociationOfCellsHierarchyWithAGeneSet
Clustering of individual cells based on a metric of choicesc_clusterObj
Comparisson of graphssc_ComparissonOfGraphs
Dimensionality reduction of an expression matrixsc_DimensionalityReductionObj
Assessment of a cell-to-cell distance matrix with a metric of choicesc_distanceObj
Graph building function for assessment of cell-state hierarchiessc_GraphBuilderObj
Function to initialize a sincell objectsc_InitializingSincellObject
In silico generation of replicates of individual cellssc_InSilicoCellsReplicatesObj
Palette of colors from the expression values of a marker genesc_marker2color
Statistical support of cell-state hierarchies by gene subsamplingsc_StatisticalSupportByGeneSubsampling
Statistical support of cell-state hierarchies by random cell substitution with in silico-generated cell replicatesc_StatisticalSupportByReplacementWithInSilicoCellsReplicates
Auxiliary function for SST algorithm within function sc_GraphBuilderObj()sstalgorithm