What is Cuffdiff?

Cuffdiff estimates the number of fragments that originated from each transcript, primary transcript, and gene in each sample. Primary transcript and gene counts are computed by summing the counts of transcripts in each primary transcript group or gene group.

What is TopHat2?

TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.

What is read count?

The Read Count quantitation is the simplest and most commonly used quantitation. It counts up the reads within a probe and can correct this raw count according to a few different factors which might bias the result – allowing it to be compared to other data sets.

Is FPKM normalized?

The name “FPKM” – fragments per kilobase of exon per million reads – implies that FPKM is a measure of gene expression normalized by exonic length and library size, in contrast to raw counts.

Why is a genome needed for RNA-seq analysis?

Summary of RNA-Seq. Within the organism, genes are transcribed and (in an eukaryotic organism) spliced to produce mature mRNA transcripts (red). These sequences can then be aligned to a reference genome sequence to reconstruct which genome regions were being transcribed.

What is TopHat alignment?

TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.

What is featureCounts?

featureCounts is a general-purpose read summarization function, which assigns to the genomic features (or meta-features) the mapped reads that were generated from genomic DNA and RNA sequencing.

How do you count a read?

Essentially, total read count associated with a gene (meta-feature) = the sum of reads associated with each of the exons (feature) that “belong” to that gene. There are other tools available that are able to account for multiple transcripts for a given gene.

What do you need to know about cuffdiff?

cuffdiff (transcriptsAnnot,alignmentFiles) identifies significant changes in transcript expression between the samples in alignmentFiles using the transcript annotation file transcriptsAnnot [1]. cuffdiff requires the Cufflinks Support Package for Bioinformatics Toolbox™.

What kind of file does cuffdiff take as input?

Cuffdiff takes a GTF2/GFF3 file of transcripts as input, along with two or more SAM files containing the fragment alignments for two or more samples. It produces a number of output files that contain test results for changes in expression at the level of transcripts, primary transcripts, and genes.

How is the cuffdiff function used in differential testing?

Assess the significance of changes in expression for genes and transcripts between conditions by performing the differential testing using cuffdiff . The cuffdiff function operates in two distinct steps: the function first estimates abundances from aligned reads, and then performs the statistical analysis.

How are transcript and gene counts calculated in cuffdiff?

Cuffdiff estimates the number of fragments that originated from each transcript, primary transcript, and gene in each sample. Primary transcript and gene counts are computed by summing the counts of transcripts in each primary transcript group or gene group. The results are output in count tracking files in the format described here.