NCGAS Makes Robust Transcriptome Assembly Even Easier with Added Features to an Accessible de novo Transcriptome Assembly Workflow

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Date

2019-01-12

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Plant and Animal Genome XXVII

Abstract

The National Center for Genome Analysis Support (NCGAS) assists research groups with de novo transcriptome assembly. Following best practice for combined de novo transcriptome assemblies can put a technical burden on genomic researchers who may not be fully computationally trained on efficient use of HPC clusters or the variety of available software packages. NCGAS has created a workflow template to move RNAseq data through 19 parallelized assemblies using four software packages (Trinity, SOAP-denovo, transABySS, and Velvet Oases) and multiple kmers. The transcripts are then combined and filtered using EviGenes to output putative transcripts and alternative forms in a replicable manner. The process is semi-automated but flexible enough to allow researchers to adjust parameters if they desire. This workflow provides a low bar for entry into robust transcriptome assembly that follows best practices, while also providing a replicable means of filtering large numbers of transcripts into a draft version of a transcriptome. We will highlight the main work flow in this demo but will concentrate on the additional features added to the workflow in the last year, including annotation via Trinotate, differential expression handling, and the automated creation of table of assembly metrics via BUSCO and Quast for each sub-assembly. As this workflow has now been adopted by several groups, we will also discuss available training and current implementations of the tool.

Description

Keywords

Transcriptome, Bioinformatics, de novo assembly

Citation

Sanders, S., B. Papudeshi, C. Ganote, T. Doak. 2019. NCGAS Makes Robust Transcriptome Assembly Even Easier with Added Features to an Accessible de novo Transcriptome Assembly Workflow. Plant and Animal Genomes XXVII, San Diego, CA. Retrieved from http://hdl.handle.net/2022/22653.

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Presentation

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