The DE Quick Start tutorial provides an introduction to basic DE functionality and navigation.
Please work through the documentation and add your comments on the bottom of this page, or email comments to email@example.com.
RMTA is a high throughput RNA-seq read mapping and transcript assembly workflow. RMTA incorporates the standard RNA-seq analysis programs traditionally used one at a time into a single, easy to use workflow that can rapidly assemble and process any amount of local (FASTq) or NCBI-stored RNA-seq (SRA) data. RMTA maps reads to user-provided reference genome using either HISAT2 (transcript analysis) or Bowtie2 (SNP analysis), assembles transcripts using StringTie, and then performs read quantification using FeatureCounts. Beyond read mapping and assembly, RMTA has a number of additional features that automate onerous data transformation and quality control steps, thus producing outputs that can be directly used for differential expression analysis, data visualization, or novel gene identification - data analyses that can all be performed in the DE or at CoGe.
Choose an appropriate name for your analysis and make comments if you wish. Default name is shown in the figure below.
Select the output folder for the results of the analysis.
***Select at least one of the below two options for the indexing of the Reference Genome***
If you have many files to process through the Discovery Environment, an HT Analysis Path List File may prove useful, as this app takes only 1 file at a time. For information on how to create an HT path list, click here.
***Only one of the following three read options (d, e, or f) may be selected per job.***
FASTQ Files (Read 2): HT path list of read 2 files of paired-end data
***When inserting multiple paired end FASTQ files, be sure to add Read 2 files in the same order as Read 1 files; the SRA ids of both lists (Reads 1 and 2) must be in the same order.***
***Only one of the below two options needs to be selected. Both cannot be selected.***
HISAT2 is a splice-aware algorithm used to perform reference genome-based read mapping. Stringtie is then used to assemble transcripts based on this read mapping.
The read aligner Bowtie2 has been included as an optional aligner in the RMTA workflow for users wishing to call single nucleotide polymorphisms (SNPs) from their RNA-seq (or DNA-seq) data in a high throughput manner. When the Bowtie2 option is selected, HISAT2 and Stringtie are both removed from the workflow, but the additional option to remove duplicate reads (important for population level analyses) becomes available.
Select the Type of Strandedness. The three options include unstranded, stranded, and reversely stranded.
Please refer to your Genome Annotation File (.gtf), and confirm that these settings match your data. For Gene Attribute, be sure that gene_id is written before the name of each gene.
Remove duplicate reads
Phred gives a quality score of how confidently nucleotides were identified during sequencing. Here, Phred33 is default. Phred 64 should be used if sequencing was performed using Illumina technology 1.3 - 1.8. An error will occur and the run will fail if the wrong quality score has been selected.
FastQC provides the user with both an overview of potential issues with the data, as well as summary graphs highlighting issues such as per base sequence quality and Kmer content. When the FastQC option has been selected, BAM files are converted back into FASTq, with mapped and unmapped reads, along with their associated quality score retained. This FASTq file is then used as input for FastQC. If issues are detected at the 5’ or 3’ of sequencing reads, RMTA includes additional options for specifically trimming bases off of either end during the next analysis. Sequencing reads of overall poor quality will simply not be mapped and therefore do not need to be trimmed. FASTq files are removed following FastQC analysis.
If the user chose Bowtie2 as the read aligner and “remove duplicate reads” as an additional option, then the RMTA_Output folder will only contain a sorted BAM file with duplicates removed for each SRA/FASTq input file, as well as a mapped.txt file. No additional files will be generated.
When using Bowtie2, be sure to check the box labeled "Remove duplicate reads," as shown in the figure below. Duplicate removal is suggested when performing SNP analysis
Name of the output folder (Default is RMTA_Output)
The following test data using Arabidopsis are provided for testing RMTA in here - /iplant/home/shared/iplantcollaborative/example_data/RMTA (this path can be copied and pasted into the navigation bar in a data window within the DE)
***Note that when testing SRA IDs, only one of steps 3, 4, or 5 may be used at a time per test run.***
All other settings should be left as default.
Successful execution of RMTA will generate three output folders: