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This is the development version of weitrix; for the stable release version, see weitrix.

Tools for matrices with precision weights, test and explore weighted or sparse data

Bioconductor version: Development (3.20)

Data type and tools for working with matrices having precision weights and missing data. This package provides a common representation and tools that can be used with many types of high-throughput data. The meaning of the weights is compatible with usage in the base R function "lm" and the package "limma". Calibrate weights to account for known predictors of precision. Find rows with excess variability. Perform differential testing and find rows with the largest confident differences. Find PCA-like components of variation even with many missing values, rotated so that individual components may be meaningfully interpreted. DelayedArray matrices and BiocParallel are supported.

Author: Paul Harrison [aut, cre]

Maintainer: Paul Harrison <paul.harrison at>

Citation (from within R, enter citation("weitrix")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

1. Concepts and practical details HTML
2. poly(A) tail length example HTML R Script
3. Alternative polyadenylation HTML R Script
4. RNA-Seq expression example HTML R Script
5. Proportions data example with SLAM-Seq HTML R Script
Reference Manual PDF


biocViews DataRepresentation, DimensionReduction, GeneExpression, RNASeq, Regression, SingleCell, Software, Transcriptomics
Version 1.17.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License LGPL-2.1 | file LICENSE
Depends R (>= 3.6), SummarizedExperiment
Imports methods, utils, stats, grDevices, assertthat, S4Vectors, DelayedArray, DelayedMatrixStats, BiocParallel, BiocGenerics, limma, topconfects, dplyr, purrr, ggplot2, rlang, scales, reshape2, splines, Ckmeans.1d.dp, glm2, RhpcBLASctl
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Suggests knitr, rmarkdown, BiocStyle, tidyverse, airway, edgeR, EnsDb.Hsapiens.v86, org.Sc.sgd.db, AnnotationDbi, ComplexHeatmap, patchwork, testthat (>= 2.1.0)
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Follow Installation instructions to use this package in your R session.

Source Package weitrix_1.17.0.tar.gz
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macOS Binary (x86_64) weitrix_1.17.0.tgz
macOS Binary (arm64) weitrix_1.17.0.tgz
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Source Repository (Developer Access) git clone
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