Package: broadSeq 1.1.0

Rishi Das Roy

broadSeq: broadSeq : for streamlined exploration of RNA-seq data

This package helps user to do easily RNA-seq data analysis with multiple methods (usually which needs many different input formats). Here the user will provid the expression data as a SummarizedExperiment object and will get results from different methods. It will help user to quickly evaluate different methods.

Authors:Rishi Das Roy [aut, cre]

broadSeq_1.1.0.tar.gz
broadSeq_1.1.0.zip(r-4.5)broadSeq_1.1.0.zip(r-4.4)broadSeq_1.1.0.zip(r-4.3)
broadSeq_1.1.0.tgz(r-4.4-any)broadSeq_1.1.0.tgz(r-4.3-any)
broadSeq_1.1.0.tar.gz(r-4.5-noble)broadSeq_1.1.0.tar.gz(r-4.4-noble)
broadSeq_1.1.0.tgz(r-4.4-emscripten)broadSeq_1.1.0.tgz(r-4.3-emscripten)
broadSeq.pdf |broadSeq.html✨
broadSeq/json (API)
NEWS

# Install 'broadSeq' in R:

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

Bug tracker:https://github.com/dasroy/broadseq/issues

On BioConductor:broadSeq-1.1.0(bioc 3.21)broadSeq-1.0.0(bioc 3.20)

geneexpression differentialexpression rnaseq transcriptomics sequencing coverage genesetenrichment go

4.95 score 2 stars 5 scripts 122 downloads 25 exports 222 dependencies

Last updated 2 months agofrom:78af4d8346. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 27 2024
R-4.5-win	NOTE	Nov 27 2024
R-4.5-linux	NOTE	Nov 27 2024
R-4.4-win	NOTE	Nov 27 2024
R-4.4-mac	NOTE	Nov 27 2024
R-4.3-win	NOTE	Nov 27 2024
R-4.3-mac	NOTE	Nov 27 2024

Exports:assay_plot biplotAnyPC combinedEnrichment genes_plot getFeatureLoadRanking normalizeEdgerCPM plot_MDS plotAnyPC plotHeatmapCluster prcompTidy round_df sampleAssay_plot transformDESeq2 use_DELocal use_deseq2 use_EBSeq use_edgeR use_edgeR_exact use_edgeR_GLM use_limma use_limma_trend use_limma_voom use_multDE use_NOIseq volcanoPlot

Dependencies:abind annotate AnnotationDbi ape aplot askpass backports base64enc BH Biobase BiocGenerics BiocManager BiocParallel BiocStyle Biostrings bit bit64 bitops blob blockmodeling bookdown boot brio broom bslib ca cachem callr car carData caTools circlize cli clue cluster clusterProfiler codetools colorspace ComplexHeatmap corrplot cowplot cpp11 crayon curl data.table DBI DelayedArray DELocal Deriv desc DESeq2 diffobj digest doBy doParallel DOSE dplyr EBSeq edgeR enrichplot evaluate fansi farver fastmap fastmatch fgsea fontawesome forcats foreach formatR Formula fs futile.logger futile.options gclus genefilter generics GenomeInfoDb GenomeInfoDbData GenomicRanges GetoptLong ggforce ggfun ggnewscale ggplot2 ggplotify ggpubr ggrepel ggsci ggsignif ggtangle ggtree GlobalOptions glue GO.db GOSemSim gplots gridExtra gridGraphics gson gtable gtools highr htmltools httr igraph IRanges isoband iterators jquerylib jsonlite KEGGREST KernSmooth knitr labeling lambda.r lattice lazyeval lifecycle limma lme4 locfit magrittr MASS Matrix MatrixGenerics MatrixModels matrixStats memoise mgcv microbenchmark mime minqa modelr munsell nlme nloptr nnet NOISeq numDeriv openssl patchwork pbkrtest permute pheatmap pillar pkgbuild pkgconfig pkgload plogr plyr png polyclip polynom praise processx ps purrr qap quantreg qvalue R.methodsS3 R.oo R.utils R6 randomcoloR rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen registry reshape2 rjson rlang rmarkdown rprojroot RSQLite rstatix Rtsne S4Arrays S4Vectors sass scales scatterpie sechm seriation shape snow SparseArray SparseM statmod stringi stringr SummarizedExperiment survival sys systemfonts testthat tibble tidyr tidyselect tidytree tinytex treeio TSP tweenr UCSC.utils utf8 V8 vctrs vegan viridisLite waldo withr xfun XML xtable XVector yaml yulab.utils zlibbioc

Using broadSeq to analyze RNA-seq data

Rendered frombroadSeq.Rmdusingknitr::rmarkdownon Nov 27 2024.

Last update: 2024-06-05
Started: 2024-03-08

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
broadSeq : for streamlined exploration of RNA-seq data	broadSeq-package broadSeq
Provides GO gene set enrichment and over-representation analysis	combinedEnrichment
Expression of multiple genes/features from a single assay as boxplot (or added dotplot)	assay_plot genes_plot
Use of edgeR package to normalize count data	normalizeEdgerCPM
Classical multidimensional scaling	plot_MDS
Plot clustered heatmaps	plotHeatmapCluster
Perform Principal Components Analysis	biplotAnyPC getFeatureLoadRanking plotAnyPC prcompTidy
Applies round function only on numeric columns of a data.frame.	round_df
Useful to visualize distribution of assay values for each sample. Plots 'boxplot' of any assay for each sample. Aesthetic can be added from colData.	sampleAssay_plot
Transform SummarizedExperiment with DESeq2 package	transformDESeq2
To use SummarizedExperiment with package DELocal	use_DELocal
To use SummarizedExperiment with package DESeq2	use_deseq2
To use SummarizedExperiment with package EBSeq	use_EBSeq
To use SummarizedExperiment with package edgeR	use_edgeR use_edgeR_exact use_edgeR_GLM
To use SummarizedExperiment with package limma	use_limma use_limma_trend use_limma_voom
To identify differentially expressed genes by multiple methods	use_multDE
Differential expression method for NOISeq	use_NOIseq
To use SummarizedExperiment with package samr	use_SAMseq
Volcano plot with formatted x and y axis label.	volcanoPlot