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baySeq:Empirical Bayesian analysis of patterns of differential expression in count data
This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.
Maintained by Samuel Granjeaud. Last updated 5 months ago.
sequencingdifferentialexpressionmultiplecomparisonsagebayesiancoverage
7.75 score 79 scripts 3 dependentsbioc
RIVER:R package for RIVER (RNA-Informed Variant Effect on Regulation)
An implementation of a probabilistic modeling framework that jointly analyzes personal genome and transcriptome data to estimate the probability that a variant has regulatory impact in that individual. It is based on a generative model that assumes that genomic annotations, such as the location of a variant with respect to regulatory elements, determine the prior probability that variant is a functional regulatory variant, which is an unobserved variable. The functional regulatory variant status then influences whether nearby genes are likely to display outlier levels of gene expression in that person. See the RIVER website for more information, documentation and examples.
Maintained by Yungil Kim. Last updated 5 months ago.
geneexpressiongeneticvariabilitysnptranscriptionfunctionalpredictiongeneregulationgenomicvariationbiomedicalinformaticsfunctionalgenomicsgeneticssystemsbiologytranscriptomicsbayesianclusteringtranscriptomevariantregressionfunctional-variantsvariant
11 stars 5.52 score 5 scripts