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RNA-seq

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Evaluation of de novo transcriptome assemblies from RNA-Seq data.

Bo Li, Nathanael Fillmore, Yongsheng Bai

|January 23, 2015

Summary

Evaluating RNA-Seq assemblies without a reference genome is difficult. We developed RSEM-EVAL, a novel scoring method, to assess transcriptome assembly accuracy, improving transcriptomic studies for non-model organisms.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

De novo RNA-Seq assembly is crucial for transcriptomic analysis in species lacking sequenced genomes.
Selecting the most accurate assembly from multiple outputs remains a significant challenge.

Purpose of the Study:

To develop a reliable method for evaluating transcriptome assembly accuracy when the ground truth is unknown.
To provide a tool that aids researchers in selecting the best assembly for downstream analysis.

Main Methods:

Development of RSEM-EVAL, a model-based score for assembly evaluation.
Creation of REF-EVAL, a refined set of ground-truth-based scores for benchmarking.
Application of RSEM-EVAL to guide the assembly of the axolotl limb transcriptome.

Main Results:

RSEM-EVAL accurately reflects assembly accuracy, correlating well with REF-EVAL.
The RSEM-EVAL guided assembly of the axolotl transcriptome demonstrated improved quality compared to a previous assembly.
A software package, DETONATE, was developed to implement these evaluation methods.

Conclusions:

RSEM-EVAL offers a robust solution for assessing de novo transcriptome assembly quality without requiring a reference genome.
The developed methods and software facilitate more reliable transcriptomic studies in non-model organisms.
Improved transcriptome assemblies can advance research in areas such as developmental biology and regenerative medicine.