R-universe search: exports:plotAberrantPerSample

Showing 2 of total 2 results (show query)

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

FRASER:Find RAre Splicing Events in RNA-Seq Data

Detection of rare aberrant splicing events in transcriptome profiles. Read count ratio expectations are modeled by an autoencoder to control for confounding factors in the data. Given these expectations, the ratios are assumed to follow a beta-binomial distribution with a junction specific dispersion. Outlier events are then identified as read-count ratios that deviate significantly from this distribution. FRASER is able to detect alternative splicing, but also intron retention. The package aims to support diagnostics in the field of rare diseases where RNA-seq is performed to identify aberrant splicing defects.

Maintained by Christian Mertes. Last updated 5 months ago.

rnaseq alternativesplicing sequencing software genetics coverage aberrant-splicing diagnostics outlier-detection rare-disease rna-seq splicing openblas cpp

41 stars 8.50 score 155 scripts