R-universe search: exports:estimateSizeFactors

Showing 6 of total 6 results (show query)

bioc

DESeq2:Differential gene expression analysis based on the negative binomial distribution

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Maintained by Michael Love. Last updated 25 days ago.

sequencing rnaseq chipseq geneexpression transcription normalization differentialexpression bayesian regression principalcomponent clustering immunooncology openblas cpp

375 stars 16.11 score 17k scripts 115 dependents

bioc

BiocGenerics:S4 generic functions used in Bioconductor

The package defines many S4 generic functions used in Bioconductor.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure bioconductor-package core-package

12 stars 14.22 score 612 scripts 2.2k dependents

bioc

OUTRIDER:OUTRIDER - OUTlier in RNA-Seq fInDER

Identification of aberrant gene expression in RNA-seq data. Read count expectations are modeled by an autoencoder to control for confounders in the data. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. Furthermore, OUTRIDER provides useful plotting functions to analyze and visualize the results.

Maintained by Christian Mertes. Last updated 5 months ago.

immunooncology rnaseq transcriptomics alignment sequencing geneexpression genetics count-data diagnostics expression-analysis mendelian-genetics outlier-detection rna-seq openblas cpp

50 stars 9.07 score 110 scripts 1 dependents

bioc

DEXSeq:Inference of differential exon usage in RNA-Seq

The package is focused on finding differential exon usage using RNA-seq exon counts between samples with different experimental designs. It provides functions that allows the user to make the necessary statistical tests based on a model that uses the negative binomial distribution to estimate the variance between biological replicates and generalized linear models for testing. The package also provides functions for the visualization and exploration of the results.

Maintained by Alejandro Reyes. Last updated 1 months ago.

immunooncology sequencing rnaseq differentialexpression alternativesplicing differentialsplicing geneexpression visualization

7.75 score 330 scripts 6 dependents

tushiqi

MAnorm2:Tools for Normalizing and Comparing ChIP-seq Samples

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the premier technology for profiling genome-wide localization of chromatin-binding proteins, including transcription factors and histones with various modifications. This package provides a robust method for normalizing ChIP-seq signals across individual samples or groups of samples. It also designs a self-contained system of statistical models for calling differential ChIP-seq signals between two or more biological conditions as well as for calling hypervariable ChIP-seq signals across samples. Refer to Tu et al. (2021) <doi:10.1101/gr.262675.120> and Chen et al. (2022) <doi:10.1186/s13059-022-02627-9> for associated statistical details.

Maintained by Shiqi Tu. Last updated 2 years ago.

chip-seq differential-analysis empirical-bayes winsorize-values

32 stars 5.48 score 19 scripts

bioc

easyRNASeq:Count summarization and normalization for RNA-Seq data

Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package.

Maintained by Nicolas Delhomme. Last updated 5 months ago.

geneexpression rnaseq genetics preprocessing immunooncology

5.43 score 15 scripts 1 dependents