MASHt: Software for statistical analysis of transcriptomes' qualitative features in factorial experiments

In Next-Generation Sequencing (NGS) data analysis, attention is given more often to the variation in gene expression levels in several experimental variants than to the qualitative differences between transcriptomes. We present the MASHt toolkit for analyzing qualitative variation in sequencing data from multifactorial experiments. The analysis involves computing pairwise Mash distances between datasets, conducting principal coordinate analysis of the resulting distance matrix, and applying univariate and multivariate analyses of variance to the principal coordinates. MASHt supports computations on data subsets, such as those annotated by a specific ontology. We demonstrate the use of MASHt with an example experiment examining the impact of temperature on the transcriptomes of different barley genotypes.