RMTA

RMTA automates read mapping and transcript assembly for RNA sequencing (RNA-seq) data to produce quality-filtered transcripts and read counts for downstream differential expression and transcriptome analyses.

Key Features:

• Scalability and High-Throughput Processing: Handles thousands of RNA-seq datasets and supports both paired-end and single-end reads from FASTQ files as well as direct processing of SRA accessions.
• Automated Quality Analysis and Filtering: Performs automated read quality analysis and applies filters for lowly expressed transcripts.
• Differential Expression Analysis: Produces read counts required for differential expression analyses.
• Containerization and Deployment: Distributed as a Docker container and deployable on cloud, local, and high-performance computing environments with integration into CyVerse's Discovery Environment for data management.
• High-Throughput Parallelized Version (OSG-RMTA): Provides a parallelized implementation optimized for the Open Science Grid (OSG) to enable distributed high-throughput processing and job submission via the Discovery Environment.

Scientific Applications:

• Transcriptomic Profiling: Captures comprehensive snapshots of gene expression from cells, tissues, or organisms using RNA-seq.
• Comparative Genomics: Enables differential gene expression comparisons across biological conditions or species.
• Functional Genomics: Supports investigation of functional elements and regulatory mechanisms through transcript-level analyses.

Methodology:

Performs read mapping and transcript assembly on FASTQ and SRA inputs, conducts automated read quality analysis, filters lowly expressed transcripts, and generates read counts; packaged in Docker with an OSG-parallelized option and integrated with CyVerse's Discovery Environment for data management and job submission.