PICARD SOMTOFASTQ¶
Converts a SAM or BAM file to FASTQ.
URL:
Example¶
This wrapper can be used in the following way:
rule bam_to_fastq:
input:
"mapped/{sample}.bam"
output:
fastq1="reads/{sample}.R1.fastq",
fastq2="reads/{sample}.R2.fastq"
log:
"logs/picard/sam_to_fastq/{sample}.log"
params:
extra="" # optional: Extra arguments for picard.
# 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:
"0.80.1/bio/picard/samtofastq"
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==2.22.1
snakemake-wrapper-utils==0.1.3
Authors¶
- Patrik Smeds
Code¶
"""Snakemake wrapper for picard SortSam."""
__author__ = "Julian de Ruiter"
__copyright__ = "Copyright 2017, Julian de Ruiter"
__email__ = "julianderuiter@gmail.com"
__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=False, stderr=True)
fastq1 = snakemake.output.fastq1
fastq2 = snakemake.output.get("fastq2", None)
fastq_unpaired = snakemake.output.get("unpaired_fastq", None)
if not isinstance(fastq1, str):
raise ValueError("f1 needs to be provided")
output = " FASTQ=" + fastq1
if isinstance(fastq2, str):
output += " SECOND_END_FASTQ=" + fastq2
if isinstance(fastq_unpaired, str):
if not isinstance(fastq2, str):
raise ValueError("f2 is required if fastq_unpaired is set")
output += " UNPAIRED_FASTQ=" + fastq_unpaired
shell(
"picard"
" SamToFastq"
" {java_opts}"
" {extra}"
" INPUT={snakemake.input[0]}"
" {output}"
" {log}"
)