LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes

Abstract

Structured AbstractMotivationDespite the abundance of species with transcriptomic data, a significant number of the species still lack genomes, making it difficult to study gene function and expression in these organisms. Whilede novotranscriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily-selected or similar experimental conditions which might fail to capture condition-specific transcripts.ResultsWe developed the Large-Scale Transcriptome Assembly Pipeline forde novoassembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovocan (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses.Availability and ImplementationLSTrAP-denovois easy to implement, written in python, and is freely available athttps://github.com/pengkenlim/LSTrAP-denovo/.Supplementary InformationSupplementary data are available in the forms of supplementary figures, supplementary tables, and supplementary methods.