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PLoS One. 2014 Feb 25;9(2):e89445. doi: 10.1371/journal.pone.0089445. eCollection 2014.

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

Author information

1
Department of Computer Science, University of New Orleans Lakefront, New Orleans, Louisiana, United States of America.
2
Department of Pathology, Tulane University, New Orleans, Louisiana, United States of America.
3
Department of Mathematics, Tulane University, New Orleans, Louisiana, United States of America.
4
Department of Microbiology, Immunology & Parasitology, Louisiana State University Health Sciences Center, New Orleans, Louisiana, United States of America ; Research Institute for Children, Children's Hospital of New Orleans, New Orleans, Louisiana, United States of America.

Abstract

High-throughput RNA sequencing (RNA-seq) has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing (NGS) analysis tools, the analysis of RNA-seq data sets poses a challenge for many biomedical researchers who are not familiar with command-line tools. Here we present RNA CoMPASS, a comprehensive RNA-seq analysis pipeline for the simultaneous analysis of transcriptomes and metatranscriptomes from diverse biological specimens. RNA CoMPASS leverages existing tools and parallel computing technology to facilitate the analysis of even very large datasets. RNA CoMPASS has a web-based graphical user interface with intrinsic queuing to control a distributed computational pipeline. RNA CoMPASS was evaluated by analyzing RNA-seq data sets from 45 B-cell samples. Twenty-two of these samples were derived from lymphoblastoid cell lines (LCLs) generated by the infection of naïve B-cells with the Epstein Barr virus (EBV), while another 23 samples were derived from Burkitt's lymphomas (BL), some of which arose in part through infection with EBV. Appropriately, RNA CoMPASS identified EBV in all LCLs and in a fraction of the BLs. Cluster analysis of the human transcriptome component of the RNA CoMPASS output clearly separated the BLs (which have a germinal center-like phenotype) from the LCLs (which have a blast-like phenotype) with evidence of activated MYC signaling and lower interferon and NF-kB signaling in the BLs. Together, this analysis illustrates the utility of RNA CoMPASS in the simultaneous analysis of transcriptome and metatranscriptome data. RNA CoMPASS is freely available at http://rnacompass.sourceforge.net/.

PMID:
24586784
PMCID:
PMC3934900
DOI:
10.1371/journal.pone.0089445
[Indexed for MEDLINE]
Free PMC Article

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