PICARD COLLECTGCBIASMETRICS¶
Run picard CollectGcBiasMetrics to generate QC metrics pertaining to GC bias.
URL:
Example¶
This wrapper can be used in the following way:
rule alignment_summary:
input:
# BAM aligned to reference genome
bam="mapped/a.bam",
# reference genome FASTA from which GC-context is inferred
ref="genome.fasta"
output:
metrics="results/a.gcmetrics.txt",
chart="results/a.gc.pdf",
summary="results/a.summary.txt"
params:
# optional additional parameters, for example,
extra="MINIMUM_GENOME_FRACTION=1E-5"
log:
"logs/picard/a.gcmetrics.log"
# optional specification of memory usage of the JVM that snakemake will respect with global
# resource restrictions (https://snakemake.readthedocs.io/en/latest/snakefiles/rules.html#resources)
# and which can be used to request RAM during cluster job submission as `{resources.mem_mb}`:
# https://snakemake.readthedocs.io/en/latest/executing/cluster.html#job-properties
resources:
mem_mb=1024
wrapper:
"0.85.0/bio/picard/collectgcbiasmetrics"
Note that input, output and log file paths can be chosen freely.
When running with
snakemake --use-conda
the software dependencies will be automatically deployed into an isolated environment before execution.
Software dependencies¶
picard==2.25.4
snakemake-wrapper-utils==0.1.3
Input/Output¶
Input:
- BAM file of RNA-seq data aligned to genome
- REF_FLAT formatted file of transcriptome annotations
Output:
- GC metrics text file
- GC metrics PDF figure
- GC summary metrics text file
Notes¶
- For more information, see https://broadinstitute.github.io/picard/command-line-overview.html#CollectGcBiasMetrics.
Authors¶
- Brett Copeland
Code¶
__author__ = "Brett Copeland"
__copyright__ = "Copyright 2021, Brett Copeland"
__email__ = "brcopeland@ucsd.edu"
__license__ = "MIT"
from snakemake.shell import shell
from snakemake_wrapper_utils.java import get_java_opts
extra = snakemake.params.get("extra", "")
java_opts = get_java_opts(snakemake)
log = snakemake.log_fmt_shell(stdout=True, stderr=True)
shell(
"picard CollectGcBiasMetrics "
"{java_opts} {extra} "
"INPUT={snakemake.input.bam} "
"OUTPUT={snakemake.output.metrics} "
"CHART={snakemake.output.chart} "
"SUMMARY_OUTPUT={snakemake.output.summary} "
"REFERENCE_SEQUENCE={snakemake.input.ref} "
"{log}"
)