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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.


cufflinksAssemble transcriptome from aligned reads
cuffcompareCompare assembled transcripts across multiple experiments
cuffdiffIdentify significant changes in transcript expression
cuffmergeMerge RNA-seq assemblies
cuffnormNormalize transcript expression levels
cuffquantQuantify gene and transcript expression profiles
cuffgffreadFilter and convert GFF and GTF files
cuffgtf2samConvert GTF files to SAM files
mattestPerform two-sample t-test to evaluate differential expression of genes from two experimental conditions or phenotypes
mafdrEstimate positive false discovery rate 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
rnaseqdePerform differential expression analysis on RNA-seq count data (Since R2021b)
knnimputeImpute missing data using nearest-neighbor method
crossvalindGenerate indices for training and test sets
classperfEvaluate classifier performance


NegativeBinomialTestUnpaired hypothesis test result
CuffCompareOptionsOption set for cuffcompare
CuffDiffOptionsOption set for cuffdiff
CuffGFFReadOptionsOption set for cuffgffread
CufflinksOptionsOption set for cufflinks
CuffMergeOptionsOption set for cuffmerge
CuffNormOptionsOption set for cuffnorm
CuffQuantOptionsOption set for cuffquant