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Statistical Analysis

Read summarization and statistical analyses on RNA-seq and ChIP-seq data

Count the number of reads mapped to genomic features of interest. Perform statistical analyses on the read counts, such as identifying differentially expressed genes from RNA-seq data, and performing genome-wide analysis of transcription factors from ChIP-seq data.

Functions

mattestPerform two-sample t-test to evaluate differential expression of genes from two experimental conditions or phenotypes
mafdrEstimate false discovery rate (FDR) for multiple hypothesis testing
nbintestUnpaired hypothesis test for count data with small sample sizes
featurecountCompute the number of reads mapped to genomic features
metafeaturesAttractor metagene algorithm for feature engineering using mutual information-based learning
rankfeaturesRank key features by class separability criteria
randfeaturesGenerate randomized subset of features
knnimputeImpute missing data using nearest-neighbor method
classperfEvaluate performance of classifier
crossvalindGenerate cross-validation indices

Classes

NegativeBinomialTestUnpaired hypothesis test result

Featured Examples

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