preprocess_rnaseq

Groovy Map containing sample information
e.g. [ id:‘test’ ]

Channel with input FastQ files of size 1 and 2 for single-end and
paired-end data, respectively.

Channel with genome sequence in fasta format

Channel with transcriptome sequence in fasta format

Channel with features in GTF format

Directory containing Salmon index

Directory containing sortmerna index

Path to directory or tar.gz archive for pre-built BBSplit index

Channel with text file containing paths to fasta files (one per line)
that will be used to create the database for SortMeRNA

Whether to skip BBSplit for removal of non-reference genome reads

Whether to skip FastQC

Whether to skip trimming

Skip the UMI extraction from the read in case the UMIs have been moved
to the headers in advance of the pipeline run

Whether to create salmon index before running salmon quant

Whether to create sortmerna index before running sortmerna

Specifies the trimming tool to use - available options are ‘trimgalore’
and ‘fastp’

Minimum number of trimmed reads below which samples are removed from
further processing

Save the trimmed FastQ files in the results directory?

Enable the removal of reads derived from ribosomal RNA using SortMeRNA?

Enable UMI-based read deduplication

After UMI barcode extraction discard either R1 or R2 by setting this
parameter to 1 or 2, respectively