Package: qsvaR 1.11.0

Hedia Tnani

qsvaR: Generate Quality Surrogate Variable Analysis for Degradation Correction

The qsvaR package contains functions for removing the effect of degration in rna-seq data from postmortem brain tissue. The package is equipped to help users generate principal components associated with degradation. The components can be used in differential expression analysis to remove the effects of degradation.

Authors:Joshua Stolz [aut], Hedia Tnani [ctb, cre], Leonardo Collado-Torres [ctb]

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qsvaR.pdf |qsvaR.html✨
qsvaR/json (API)
NEWS

# Install 'qsvaR' in R:

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

Bug tracker:https://github.com/lieberinstitute/qsvar/issues

Datasets:

covComb_tx_deg - RSE object of RNA-seq data that serves as output for degradation analysis
degradation_tstats - Degradation time t-statistics
transcripts - Transcripts for Degradation Models

On BioConductor:qsvaR-1.11.0(bioc 3.21)qsvaR-1.10.0(bioc 3.20)

software workflowstep normalization biologicalquestion differentialexpression sequencing coverage bioconductor brain degradation human qsva

5.18 score 4 scripts 372 downloads 8 exports 147 dependencies

Last updated 21 days agofrom:4754d53954. Checks:OK: 1 WARNING: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 18 2024
R-4.5-win	WARNING	Nov 18 2024
R-4.5-linux	WARNING	Nov 18 2024
R-4.4-win	WARNING	Nov 18 2024
R-4.4-mac	WARNING	Nov 18 2024
R-4.3-win	WARNING	Nov 18 2024
R-4.3-mac	WARNING	Nov 18 2024

Exports:check_tx_names DEqual get_qsvs getDegTx getPCs k_qsvs qSVA select_transcripts

Dependencies:abind annotate AnnotationDbi askpass backports base64enc BH Biobase BiocGenerics BiocParallel Biostrings bit bit64 blob broom bslib cachem callr cellranger cli clipr codetools colorspace conflicted cpp11 crayon curl data.table DBI dbplyr DelayedArray digest dplyr dtplyr edgeR evaluate fansi farver fastmap fontawesome forcats formatR fs futile.logger futile.options gargle genefilter generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue googledrive googlesheets4 gtable haven highr hms htmltools httr ids IRanges isoband jquerylib jsonlite KEGGREST knitr labeling lambda.r lattice lifecycle limma locfit lubridate magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime modelr munsell nlme openssl pillar pkgconfig plogr png prettyunits processx progress ps purrr R6 ragg rappdirs RColorBrewer readr readxl rematch rematch2 reprex rlang rmarkdown RSQLite rstudioapi rvest S4Arrays S4Vectors sass scales selectr snow SparseArray statmod stringi stringr SummarizedExperiment survival sva sys systemfonts textshaping tibble tidyr tidyselect tidyverse timechange tinytex tzdb UCSC.utils utf8 uuid vctrs viridisLite vroom withr xfun XML xml2 xtable XVector yaml zlibbioc

Introduction to qsvaR

Joshua M. Stolz, Hedia Tnani, Leonardo Collado-Torres

Rendered fromIntro_qsvaR.Rmdusingknitr::rmarkdownon Nov 18 2024.

Last update: 2023-06-21
Started: 2021-12-14

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Check validity of transcript vectors	check_tx_names
RSE object of RNA-seq data that serves as output for degradation analysis	covComb_tx_deg
Degradation time t-statistics	degradation_tstats
Differential expression quality (DEqual) plot	DEqual
Generate matrix of qsvs	get_qsvs
Obtain expression matrix for degraded transcripts	getDegTx
PCs from transcripts	getPCs
Apply num.sv algorithm to determine the number of pcs to be included	k_qsvs
A wrapper function used to perform qSVA in one step.	qSVA
Select transcripts associated with degradation	select_transcripts
Transcripts for Degradation Models	transcripts