Package: CEDA 1.1.1

Lianbo Yu

CEDA: CRISPR Screen and Gene Expression Differential Analysis

Provides analytical methods for analyzing CRISPR screen data at different levels of gene expression. Multi-component normal mixture models and EM algorithms are used for modeling.

Authors:Lianbo Yu [aut, cre], Yue Zhao [aut], Kevin R. Coombes [aut], Lang Li [aut]

CEDA_1.1.1.tar.gz
CEDA_1.1.1.tar.gz(r-4.7-any)CEDA_1.1.1.tar.gz(r-4.6-any)
CEDA_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CEDA/json (API)

# Install 'CEDA' in R:

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

Datasets:

mda231 - CRISPR screen data of cell line MDA-MB-231.

On CRAN:

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

3.40 score 3 scripts 285 downloads 5 mentions 10 exports 77 dependencies

Last updated from:e587a189b4. Checks:2 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	WARNING	171
source / vignettes	OK	300
linux-release-x86_64	WARNING	181
wasm-release	OK	125

Exports:calculateGeneLFC calculateGenePval densityPlot medianNormalization normalMM permuteLimma preparePlotData ridgePlot runLimma scatterPlot

Dependencies:askpass base64enc bslib cachem cli cpp11 crosstalk curl data.table digest dplyr evaluate farver fastmap fontawesome fs generics ggplot2 ggprism ggridges ggsci glue gtable highr htmltools htmlwidgets httr isoband jquerylib jsonlite kernlab knitr labeling later lattice lazyeval lifecycle limma magrittr MASS Matrix memoise mime mixtools nlme openssl otel pillar pkgconfig plotly promises purrr R6 rappdirs RColorBrewer Rcpp rlang rmarkdown S7 sass scales segmented statmod stringi stringr survival sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

CRISPR Screen and Gene Expression Differential Analysis

Rendered fromUserguide.Rmdusingknitr::rmarkdown

Last update: 2024-02-28
Started: 2022-01-07

Citation

Readme and manuals

Help Manual

Help page	Topics
Calculating a significance score of a gene based on the corresponding sgRNAs' p-values of the gene.	alphaBeta
Calculating gene-level log fold ratios	calculateGeneLFC
Calculating gene level p-values using modified robust rank aggregation (alpha-RRA method) on sgRNAs' p-values	calculateGenePval
2D density contour plot of gene log2 fold ratios against gene expression levels	densityPlot
Fitting multi-component normal mixture models by R package mixtools	EMFit
Generating the null distribution of the significance score of a gene.	makeRhoNull
CRISPR screen data of cell line MDA-MB-231.	mda231
Median normalization of sgRNA counts	medianNormalization
Performing empirical Bayes modeling on limma results	normalMM
Modeling CRISPR data with a permutation test between conditions by R package limma	permuteLimma
Prepare data for density plot and ridge plot	preparePlotData
Density ridgeline plot of gene expression levels for different FDR groups.	ridgePlot
Modeling CRISPR screen data by R package limma	runLimma
Scatter plot of log2 fold ratios against gene expression levels	scatterPlot

Package: CEDA 1.1.1

CEDA: CRISPR Screen and Gene Expression Differential Analysis

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)