Practical selection of representative sets of RNA-seq samples using a hierarchical approach.

ABSTRACT:

Motivation

Despite numerous RNA-seq samples available at large databases, most RNA-seq analysis tools are evaluated on a limited number of RNA-seq samples. This drives a need for methods to select a representative subset from all available RNA-seq samples to facilitate comprehensive, unbiased evaluation of bioinformatics tools. In sequence-based approaches for representative set selection (e.g. a k-mer counting approach that selects a subset based on k-mer similarities between RNA-seq samples), because of the large numbers of available RNA-seq samples and of k-mers/sequences in each sample, computing the full similarity matrix using k-mers/sequences for the entire set of RNA-seq samples in a large database (e.g. the SRA) has memory and runtime challenges; this makes direct represen

SUBMITTER: Tung LH 

PROVIDER: S-EPMC8275344 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature