STAR-ARRIBA
A subworkflow for fusion detection from RNA-seq data with arriba. The fusion calling is based on splice-aware, chimeric alignments done with STAR. STAR is used with specific parameters to ensure optimal functionality of the arriba fusion detection, for details, see the documentation.
Usage
Via module
This usage is recommended with Snakemake >=7.9.
You can include this meta-wrapper in your workflow via the Snakemake module system:
module star_arriba:
meta_wrapper: "v9.0.1/meta/bio/star_arriba"
pathvars:
results="...", # Path to results directory
resources="...", # Path to resources directory
logs="...", # Path to logs directory
genome_sequence="...", # Path to FASTA file with genome sequence
genome_annotation="...", # Path to GTF file with genome annotation
reads_r1="...", # Path/pattern for FASTQ files with R1 reads
reads_r2="...", # Path/pattern for FASTQ files with R2 reads
per="...", # Pattern for sample identifiers, e.g. ``"{sample}"``
use rule * from star_arriba as star_arriba_*
Upon using the rules, you can additionally modify input, output, log, and params as needed (see the definition of each rule below and the modules documentation). For additional parameters in each individual wrapper, please refer to their corresponding documentation (see links below).
Via copy-paste
Alternatively, you can directly copy-paste and modify the full meta-wrapper code below into your workflow.
Execution
When running with
snakemake --sdm conda
the software dependencies will be automatically deployed into an isolated environment before execution.
Used wrappers
The following individual wrappers are used in this meta-wrapper:
Please refer to each wrapper in above list for additional configuration parameters and information about the executed code.
Code
rule star_index:
input:
fasta="<genome_sequence>",
gtf="<genome_annotation>",
output:
directory("<resources>/star_genome"),
threads: 4
params:
sjdbOverhang=100,
extra="",
log:
"<logs>/star_index_genome.log",
cache: True # mark as eligible for between workflow caching
wrapper:
"v3.3.7/bio/star/index"
rule star_align:
input:
# use a list for multiple fastq files for one sample
# usually technical replicates across lanes/flowcells
fq1="<reads_r1>",
fq2="<reads_r2>", #optional
idx="<resources>/star_genome",
annotation="<genome_annotation>",
output:
# see STAR manual for additional output files
aln="<results>/star/<per>/Aligned.out.bam",
reads_per_gene="<results>/star/<per>/ReadsPerGene.out.tab",
log:
"<logs>/star/<per>.log",
params:
# specific parameters to work well with arriba
extra=lambda wc, input: (
f"--quantMode GeneCounts --sjdbGTFfile {input.annotation}"
" --outSAMtype BAM Unsorted --chimSegmentMin 10 --chimOutType WithinBAM SoftClip"
" --chimJunctionOverhangMin 10 --chimScoreMin 1 --chimScoreDropMax 30 --chimScoreJunctionNonGTAG 0"
" --chimScoreSeparation 1 --alignSJstitchMismatchNmax 5 -1 5 5 --chimSegmentReadGapMax 3"
),
threads: 12
wrapper:
"v3.3.7/bio/star/align"
rule arriba:
input:
bam=rules.star_align.output.aln,
genome="<genome_sequence>",
annotation="<genome_annotation>",
# optional: # A custom tsv containing identified artifacts, such as read-through fusions of neighbouring genes.
# default blacklists are selected via blacklist parameter
# see https://github.com/suhrig/arriba/wiki/04-Input-files#blacklist
custom_blacklist=[],
output:
fusions="<results>/arriba/<per>.fusions.tsv",
discarded="<results>/arriba/<per>.fusions.discarded.tsv",
params:
# required if blacklist or known_fusions is set
genome_build="GRCh38",
default_blacklist=False,
default_known_fusions=True,
extra="",
log:
"<logs>/arriba/<per>.log",
threads: 1
wrapper:
"v7.3.0/bio/arriba"