- RMTA is a workflow that can rapidly process raw RNA-seq illumina data by mapping reads to a genome (HiSat2) and then assemble transcripts using Stringtie.
- RMTA can process FASTq files containing paired-end or single-end reads. Alternatively, RMTA can directly process one or more sequence read archives (SRA) from NCBI using a SRA ID.
- RMTA also supports read alignment directly to a transcriptome using the quasi-aligner and transcript abundance quantifier Salmon (Rob et al., 2017; Srivastava et al., 2019). Salmon maps reads to the provided transcript assembly and then counts the number of reads associated with each transcript, generating an output file (quant.sf) that can immediately be used for differential expression. Note: The utilization of Salmon is only appropriate when the user is wanting to rapidly test for differential expression and cannot facilitate the identification of novel genes or data visualization in a genome browser.
The OSG is a consortium of research communities which facilitates distributed high throughput computing for scientific research. The Open Science Grid (OSG) enables distributed computing at more than 120 institutions, supports efficient data processing and provides large scale scientific computing of more than 2 million CPU hours per day. More about OSG can be found here
RMTA is currently available as a Docker image and also as an app in CyVerse's Discovery Environment (DE). Many users find using RMTA in the DE to be quite useful because the DE provides a GUI (graphical user interface) for the RMTA tool and is coupled with CyVerse's Data store for storing the data. In addition, running jobs within the DE removes the computational requirements for running the analysis from the user. However, processing thousands of RNA-seq datasets in the DE is limited to the concurrent job restrictions in place (there is a limit of 8 concurrent jobs).
Thus, for processing large data sets in a timely manner, the OSG serves as the perfect alternative to the DE. However, jobs submitted to the OSG typically require command-line experience. In order to allow users with minimal command-line experience to address their large RNA-seq data set questions, we have developed OSG-RMTA which is a highly scalable RMTA for processing high-throughput RNA-Seq datasets using computational resources available to U.S-based researchers on the OSG. Users familiar with command line can run the OSG-RMTA workflow directly on the OSG by submitting the jobs to the HTCondor or run it in CyVerse Discovery Environment as the OSG-RMTA app. Running jobs through CyVerse's DE is recommended because these jobs are decomposed into multiple tasks that can be carried out in parallel. In sum, input data transfers from the DE to the OSG, compute tasks (read mapping and transcript assembly) are performed on the OSG, and then results are returned to CyVerse's Datastore.
Genome-guided RMTA minimally requires the following input data:
- Reference Genome (FASTA) or Hisat2 Indexed Reference Genome (in a subdirectory)
- RNA-Seq reads (FASTQ) - Single end or Paired end or NCBI SRA id or multiple NCBI SRA id's (list in a single column text file).
Transcriptome-guided RMTA minimally requires the following input data:
- Reference Transcriptome (FASTA)
- RNA-Seq reads (FASTQ) - Single end or Paired end or NCBI SRA id or multiple NCBI SRA id's (list in a single column text file).
More information about RMTA can be found here
The OSG-RMTA-v2.6.3 app is currently integrated in CyVerse’s Discovery Environment (DE) and is free to use by researchers. Register for a free account at CyVerse. The complete tutorial is available at this location CyVerse wiki. CyVerse's DE is a free and easy to use GUI that simplifies many aspects of running bioinformatics analyses. If you do not currently have access to a high performance computing cluster, consider taking advantange of the DE. You can submit thousands of jobs using the OSG-RMTA v2.6.3 app and they will run on OSG instead of on the DE.
The OSG-RMTA-v2.6.3 Docker image app is currently available on the OSG and is free to use by researchers. In order to run OSG-RMTA on OSG, you first need to have an account with OSG. Register for a free account at osg-connect. After you register, you need to add your keys because OSG no longer allows password access. You can find more information here.
The complete tutorial for running RMTA on the OSG is available in here.
If you experience any issues with running OSG-RMTA (DE app, source code, or Docker image), please open an issue on this github repo. Alternatively you can post your queries and feature requests in this google groups
The sources in this Github repository, are copyright free. Thus you are allowed to use these sources in which ever way you like. Here is the full MIT license.