Generalized linear models (GLM) are a classic method for analyzing RNA-seq expression data. In contrast to exact tests, GLMs allow for more general comparisons. The types of comparisons you can make will depend on the design of your study. In the following example we will use the raw counts of ...

Exact tests often are a good place to start with differential expression analysis of genomic data sets. As usual, the types of contrasts you can make will depend on the design of your study and data set. In the following example we will use the raw counts of differentially expressed (...

Venn diagrams are a great way to visualize informative comparisons between data sets. It can be particularly helpful to use venn diagrams to look at how similar data is across multiple data sets, or within the same data set. The types of comparisons you can make will depend on how ...

One of the best ways to compare the characteristics of any data set is to create descriptive plots. The following R scripts have been improved to generate plots of sequence, line, and size statistics for a set of input fasta files. The example outputs have been generated from these scripts ...

To calculate min, median, mean, and max intron lengths from a gff file use the intronsByTranscript function of GenomicFeatures in R. Be sure to first use the makeTxDbFromGFF function of GenomicFeatures to create a TxDb object of th...