Package: speckle 1.13.0

Belinda Phipson

speckle: Statistical methods for analysing single cell RNA-seq data

The speckle package contains functions for the analysis of single cell RNA-seq data. The speckle package currently contains functions to analyse differences in cell type proportions. There are also functions to estimate the parameters of the Beta distribution based on a given counts matrix, and a function to normalise a counts matrix to the median library size. There are plotting functions to visualise cell type proportions and the mean-variance relationship in cell type proportions and counts. As our research into specialised analyses of single cell data continues we anticipate that the package will be updated with new functions.

Authors:Belinda Phipson [aut, cre]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
speckle/json (API)

# Install 'speckle' in R:

install.packages('speckle', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

pbmc_props - Cell type proportions from single cell PBMC data

On BioConductor:speckle-1.13.0(bioc 3.24)speckle-1.12.0(bioc 3.23)

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

singlecell rnaseq regression geneexpression

5.91 score 545 scripts 13 exports 159 dependencies

Last updated from:784ac53456. Checks:8 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	228
linux-devel-x86_64	NOTE	436
source / vignettes	OK	380
linux-release-x86_64	NOTE	444
macos-release-arm64	NOTE	220
macos-oldrel-arm64	NOTE	248
windows-devel	NOTE	301
windows-release	NOTE	321
windows-oldrel	NOTE	349
wasm-release	OK	231

Exports:convertDataToList estimateBetaParam estimateBetaParamsFromCounts getTransformedProps ggplotColors normCounts plotCellTypeMeanVar plotCellTypeProps plotCellTypePropsMeanVar propeller propeller.anova propeller.ttest speckle_example_data

Dependencies:abind askpass base64enc BH Biobase BiocGenerics bitops bslib cachem caTools cli cluster codetools commonmark cowplot cpp11 crosstalk curl data.table DelayedArray deldir digest dotCall64 dplyr dqrng edgeR evaluate farver fastDummies fastmap fitdistrplus FNN fontawesome fs future future.apply generics GenomicRanges ggplot2 ggrepel ggridges globals glue goftest gplots gridExtra gtable gtools here highr htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval lifecycle limma listenv lmtest locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mime miniUI nlme openssl otel parallelly patchwork pbapply pillar pkgconfig plotly plyr png polyclip progressr promises purrr R6 RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppProgress RcppTOML reshape2 reticulate rlang rmarkdown ROCR rprojroot RSpectra Rtsne S4Arrays S4Vectors S7 sass scales scattermore sctransform Seqinfo Seurat SeuratObject shiny SingleCellExperiment sitmo sourcetools sp spam SparseArray spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils statmod stringi stringr SummarizedExperiment survival sys tensor tibble tidyr tidyselect tinytex utf8 uwot vctrs viridisLite withr xfun xtable XVector yaml zoo

speckle: statistical methods for analysing single cell RNA-seq data

Rendered fromspeckle.Rmdusingknitr::rmarkdown

Last update: 2022-12-06
Started: 2022-08-19

Help page	Topics
Extract metadata from 'SingleCellExperiment' object	.extractSCE
Extract metadata from 'Seurat' object	.extractSeurat
Convert counts or proportions matrix to list object for propeller	convertDataToList
Estimate the parameters of a Beta distribution	estimateBetaParam
Estimate parameters of a Beta distribution from counts	estimateBetaParamsFromCounts
Calculates and transforms cell type proportions	getTransformedProps
Output a vector of colours based on the ggplot colour scheme	ggplotColors
Normalise a counts matrix to the median library size	normCounts
Cell type proportions from single cell PBMC data	pbmc_props
Plot cell type counts means versus variances	plotCellTypeMeanVar
Plot cell type proportions for each sample	plotCellTypeProps
Plot cell type proportions versus variances	plotCellTypePropsMeanVar
Finding statistically significant differences in cell type proportions	propeller
Performs F-tests for transformed cell type proportions	propeller.anova
Performs t-tests of transformed cell type proportions	propeller.ttest
Generate example data	speckle_example_data

Package: speckle 1.13.0

speckle: Statistical methods for analysing single cell RNA-seq data

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