DaMiRseq
This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see DaMiRseq.
Data Mining for RNA-seq data: normalization, feature selection and classification
Bioconductor version: 3.17
The DaMiRseq package offers a tidy pipeline of data mining procedures to identify transcriptional biomarkers and exploit them for both binary and multi-class classification purposes. The package accepts any kind of data presented as a table of raw counts and allows including both continous and factorial variables that occur with the experimental setting. A series of functions enable the user to clean up the data by filtering genomic features and samples, to adjust data by identifying and removing the unwanted source of variation (i.e. batches and confounding factors) and to select the best predictors for modeling. Finally, a "stacking" ensemble learning technique is applied to build a robust classification model. Every step includes a checkpoint that the user may exploit to assess the effects of data management by looking at diagnostic plots, such as clustering and heatmaps, RLE boxplots, MDS or correlation plot.
Author: Mattia Chiesa <mattia.chiesa at cardiologicomonzino.it>, Luca Piacentini <luca.piacentini at cardiologicomonzino.it>
Maintainer: Mattia Chiesa <mattia.chiesa at cardiologicomonzino.it>
citation("DaMiRseq")):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("DaMiRseq")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DaMiRseq")| Data Mining for RNA-seq data: normalization, features selection and classification - DaMiRseq package | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Classification, ImmunoOncology, RNASeq, Sequencing, Software |
| Version | 2.12.0 |
| In Bioconductor since | BioC 3.5 (R-3.4) (7 years) |
| License | GPL (>= 2) |
| Depends | R (>= 3.5.0), SummarizedExperiment, ggplot2 |
| Imports | DESeq2, limma, EDASeq, RColorBrewer, sva, Hmisc, pheatmap, FactoMineR, corrplot, randomForest, e1071, caret, MASS, lubridate, plsVarSel, kknn, FSelector, methods, stats, utils, graphics, grDevices, reshape2, ineq, arm, pls, RSNNS, edgeR, plyr |
| System Requirements | |
| URL |
See More
| Suggests | BiocStyle, knitr, testthat |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | GARS |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | DaMiRseq_2.12.0.tar.gz |
| Windows Binary | DaMiRseq_2.12.0.zip |
| macOS Binary (x86_64) | DaMiRseq_2.12.0.tgz |
| macOS Binary (arm64) | DaMiRseq_2.12.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/DaMiRseq |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/DaMiRseq |
| Bioc Package Browser | https://code.bioconductor.org/browse/DaMiRseq/ |
| Package Short Url | https://bioconductor.org/packages/DaMiRseq/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.17 | Source Archive |