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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq.

Ruolin Liu¹, Julie Dickerson¹

¹Department of Electrical and Computational Engineering, Iowa State University, Ames, Iowa, United States of America.

Plos Computational Biology

|November 28, 2017

Summary

This summary is machine-generated.

Strawberry is a new open-source tool for RNA-Seq analysis, accurately reconstructing transcripts and quantifying their expression. It outperforms existing methods in simulations and real-world data analysis for transcriptomics.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

RNA-Seq (Ribonucleic acid sequencing) is a powerful technology for studying gene expression.
Accurate transcript reconstruction and quantification are crucial for understanding cellular processes.
Existing tools face challenges in handling large datasets and achieving high accuracy.

Purpose of the Study:

To introduce Strawberry, a novel method and software tool for transcript reconstruction and quantification from RNA-Seq data.
To develop an efficient, expandable, and accurate algorithm capable of handling large datasets.
To provide an open-source solution for transcriptomics analysis.

Main Methods:

Strawberry utilizes a two-module approach: assembly and quantification.
The assembly module employs network flow algorithms on splicing graphs derived from aligned reads.
The quantification module uses a latent class model and an EM algorithm for transcript abundance estimation and bias correction.

Main Results:

Simulations demonstrate Strawberry's superior accuracy in both transcript assembly and quantification compared to Cufflinks and StringTie.
Analysis of real RNA-Seq data shows Strawberry's transcript expression estimates highly correlate with Nanostring probe counts.
The software tool is implemented in C++14 and designed for efficiency and scalability.

Conclusions:

Strawberry offers a highly efficient, expandable, and accurate solution for transcript reconstruction and quantification from RNA-Seq data.
The method's performance surpasses existing tools in both simulated and real-world datasets.
Strawberry provides a valuable open-source resource for the genomics and bioinformatics communities.