This is most likely a very basic issue, but I could not find it documented anywhere.
rule all:
input:
"fasta_file.fna"
output:
"headers.txt"
shell:
"grep "^>" {input} > {output}"
I want to run this for a set of files that are not necessarily in the same folder. Is there a way to provide as command (or config file) the input file name from another directory?
Okay never mind, this was probably no smart question indeed.
rule all:
input:
"input/{sample}.fna"
output:
"output/{sample}_headers.txt"
shell:
"grep "^>" {input} > {output}"
And with that I can just run snakemake for my target file, something like snakemake output/A1_headers.txt, or build a for loop over my input sequences.
Related
As part of a Snakemake pipeline that I'm building, I have to use a program that does not allow me to specify the file path or name of an output file.
E.g. when running the program in the working directory workdir/ it produces the following output:
workdir/output.txt
My snakemake rule looks something like this:
rule NAME:
input: "path/to/inputfile"
output: "path/to/outputfile"
shell: "somecommand {input} {output}"
So every time the rule NAME runs, I get an additional file output.txt in the snakemake working directory, which is then overwritten if the rule NAME runs multiple times or in parallel.
I'm aware of shadow rules, and adding shadow: "full" allows me to simply ignore the output.txt file. However, I'd like to keep output.txt and save it in the same directory as the outputfile. Is there a way of achieving this, either with the shadow directive or otherwise?
I was also thinking I could prepend somecommand with a cd command, but then I'd probably run into other issues downstream when linking up other rules to the outputs of the rule NAME.
How about simply moving it directly afterwards in the shell part (provided somecommand completes successfully)?
rule NAME:
input: "path/to/inputfile"
output: "path/to/outputfile"
params:
output_dir = "path/to/output_dir",
shell: "somecommand {input} {output} && mv output.txt {params.output_dir}/output.txt"
EDIT: for multiple executions of NAME in parallel, combining with shadow: "full" could work:
rule NAME:
input: "path/to/inputfile"
output:
output_file = "path/to/outputfile"
output_txt = "path/to/output_dir/output.txt"
shadow: "full"
shell: "somecommand {input} {output.output_file} && mv output.txt {output.output_txt}"
That should run each execution of the rule in its own temporary dir, and by specifying the moved output.txt as an output Snakemake should move it to the real output dir once the rule is done running.
I was also thinking I could prepend somecommand with a cd command, but then I'd probably run into other issues downstream when linking up other rules to the outputs of the rule NAME.
I think you are on the right track here. Each shell block is run in a separate process with the working directory inherited from the snakemake process (specified with the --directory argument on the command line). Accordingly, cd commands in one shell block will not affect other jobs from the same rule or other downstream/upstream jobs.
rule NAME:
input: "path/to/inputfile"
output: "path/to/outputfile"
shell:
"""
input_file=$(realpath "{input}") # get the absolute path, before the `cd`
base_dir=$(dirname "{output}")
cd "$base_dir"
somecommand ...
"""
i'm sorry if my question may seem a bit dumb.
So, i'm currently trying to write a workflow on snakemake (my first, as a trainee), i've to automate a couple of steps, those steps dependings all on python scripts already made.
My trouble is that the input and outputs of those scripts are folders themselves (and their content corresponding of files linked of the first directory content..).
So far, i did this (which is not working, as we can expect)
configfile: "config.yaml"
rule all:
input:
"{dirname}/directory_results/sub_dir2", dirname=config["dirname"]
rule script1:
input:
"{dirname}/reference/{files}.gbff", dirname=config["dirname"]
output:
"{dirname}/directory_results", dirname=config["dirname"]
shell:
"python script_1.py -i {dirname}/reference -o {output}"
rule script2:
input:
"{dirname}/directory_results/sub_dir1/{files}.gbff.gff", dirname=config["dirname"]
output:
"{dirname}/directory_results/sub_dir2", dirname=config["dirname"]
shell:
"python script_2.py -i {dirname}/directory_results/sub_dir1"
As for config.yaml, it's a simple file that i used for now, to put the path of the said "dirname"
dirname:
Sero_1: /project/work/test_snake/Sero_1
I know that there is much to refactor (i'm still not accustomed to snakemake since, beside the tutorial, it's my first workflow ever made). I also understand that the problem lie probably in the fact that, input can't be directories. I tried a couple of things since a couple of days, and i thought i may ask some advice since i'm struggling
How can i put an input that will permit to use for scripts directories?
If it may help, i solved my rule "script1" by doing:
configfile: "config.yaml"
dirname = config["dirname"]
rule all:
input:
expand("{dirname}/directory_results/", "{dirname}/directory_results/subdir2" dirname=dirname)
rule script1:
input:
expand("{dirname}/reference/", dirname=dirname)
output:
directory(expand("{dirname}/directory_results", dirname=dirname))
shell:
"python script_1.py -i {input} -o {output}"
rule script2:
input:
rules.script1.output
output:
directory(extend("{dirname}/directory_results/sub_dir2", dirname=dirname))
shell:
"python script_2.py -i {input}"
As for the config.yaml file:
dirname:
- /project/work/test_snake/Sero_1
- /project/work/test_snake/Sero_2
I have been trying to run metabat2 with snakemake. I can run it but the output files in metabat2/ are missing. The checkM that works after it does use the data and can work I just cant find the files later. There should be files created with numbers but it is imposible to predict how many files will be created. Is there a way I can specify it to make sure that the files are created in that file?
rule all:
[f"metabat2/" for sample in samples],
[f"checkm/" for sample in samples]
rule metabat2:
input:
"input/consensus.fasta"
output:
directory("metabat2/")
conda:
"envs/metabat2.yaml"
shell:
"metabat2 -i {input} -o {output} -v"
rule checkM:
input:
"metabat2/"
output:
c = "bacteria/CheckM.txt",
d = directory("checkm/")
conda:
"envs/metabat2.yaml"
shell:
"checkm lineage_wf -f {output.c} -t 10 -x fa {input} {output.d}"
the normal code to run metabat2 would be
metabat2 -i path/to/consensus.fasta -o /outputdir/bin -v
this will create in outputdir files with bin.[number].fa
I can't tell what the problem is but I have a couple of suggestions...
[f"metabat2/" for sample in samples]: I doubt this will do what you expect as it will simply create a list with the string metabat2/ repeat len(samples) times. Maybe you want [f"metabat2/{sample}" for sample in samples]? The same for [f"checkm/" for sample in samples]
The samples variable is not used anywhere in the rules following all. I suspect somewhere it should be used and/or you should use something like output: directory("metabat2/{sample}")
Execute snakemake with -p option to see what commands are executed. It may be useful to post the stdout from it.
I am absolute beginner to snakemake. I am building a pipeline as I learn. My question is if the Snakefile is placed with data file that I want to process an NameError: occurs but if I move the Snakefile to a parent directory and edit the path information of input: and output: the code works. what am I missing?
rule sra_convert:
input:
"rna/{id}.sra"
output:
"rna/fastq/{id}.fastq"
shell:
"fastq-dump {input} -O {output}"
above code works fine when I run with
snakemake -p rna/fastq/SRR873382.fastq
However, if I move the file to "rna" directory where the SRR873382.sra file is and edit the code as below
rule sra_convert:
input:
"{id}.sra"
output:
"fastq/{id}.fastq"
message:
"Converting from {id}.sra to {id}.fastq"
shell:
"fastq-dump {input} -O {output}"
and run
snakemake -p fastq/SRR873382.fastq
I get the following error
Building DAG of jobs...
Job counts:
count jobs
1 sra_convert
1
RuleException in line 7 of /home/sarc/Data/rna/Snakefile:
NameError: The name 'id' is unknown in this context. Please make sure that you defined that variable. Also note that braces not used for variable access have to be escaped by repeating them, i.e. {{print $1}}
Solution
rule sra_convert:
input:
"{id}.sra"
output:
"fastq/{id}.fastq"
message:
"Converting from {wildcards.id}.sra to {wildcards.id}.fastq"
shell:
"fastq-dump {input} -O {output}"
above code runs fine without error
I believe that the best source that answers your actual question is:
https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards
If the rule’s output matches a requested file, the substrings matched
by the wildcards are propagated to the input files and to the variable
wildcards, that is here also used in the shell command. The wildcards
object can be accessed in the same way as input and output, which is
described above.
I'm using snakemake for the first time in order to build a basic pipeline using cutadapt, bwa and GATK (trimming ; mapping ; calling). I would like to run this pipeline on every fastq file contained in a directory, without having to specify their name or whatever in the snakefile or in the config file. I would like to succeed in doing this.
The first two steps (cutadapt and bwa / trimming and mapping) are running fine, but I'm encountering some problems with GATK.
First, I have to generate g.vcf files from bam files. I'm doing this using these rules:
configfile: "config.yaml"
import os
import glob
rule all:
input:
"merge_calling.g.vcf"
rule cutadapt:
input:
read="data/Raw_reads/{sample}_R1_{run}.fastq.gz",
read2="data/Raw_reads/{sample}_R2_{run}.fastq.gz"
output:
R1=temp("trimmed_reads/{sample}_R1_{run}.fastq.gz"),
R2=temp("trimmed_reads/{sample}_R2_{run}.fastq.gz")
threads:
10
shell:
"cutadapt -q {config[Cutadapt][Quality_value]} -m {config[Cutadapt][min_length]} -a {config[Cutadapt][forward_adapter]} -A {config[Cutadapt][reverse_adapter]} -o {output.R1} -p '{output.R2}' {input.read} {input.read2}"
rule bwa_map:
input:
genome="data/genome.fasta",
read=expand("trimmed_reads/{{sample}}_{pair}_{{run}}.fastq.gz", pair=["R1", "R2"])
output:
temp("mapped_bam/{sample}_{run}.bam")
threads:
10
params:
rg="#RG\\tID:{sample}\\tPL:ILLUMINA\\tSM:{sample}"
shell:
"bwa mem -t 2 -R '{params.rg}' {input.genome} {input.read} | samtools view -Sb - > {output}"
rule picard_sort:
input:
"mapped_bam/{sample}.bam"
output:
"sorted_reads/{sample}.bam"
shell:
"java -Xmx4g -jar /home/alexandre/picard-tools/picard.jar SortSam I={input} O={output} SO=coordinate VALIDATION_STRINGENCY=SILENT"
rule picard_rmdup:
input:
bam="sorted_reads/{sample}.bam"
output:
"rmduped_reads/{sample}.bam",
"picard_stats/{sample}.bam"
params:
reads="rmduped_reads/{sample}.bam",
stats="picard_stats/{sample}.bam",
shell:
"java -jar -Xmx2g /home/alexandre/picard-tools/picard.jar MarkDuplicates "
"I={input.bam} "
"O='{params.reads}' "
"VALIDATION_STRINGENCY=SILENT "
"MAX_FILE_HANDLES_FOR_READ_ENDS_MAP=1000 "
"REMOVE_DUPLICATES=TRUE "
"M='{params.stats}'"
rule samtools_index:
input:
"rmduped_reads/{sample}.bam"
output:
"rmduped_reads/{sample}.bam.bai"
shell:
"samtools index {input}"
rule GATK_raw_calling:
input:
bam="rmduped_reads/{sample}.bam",
bai="rmduped_reads/{sample}.bam.bai",
genome="data/genome.fasta"
output:
"Raw_calling/{sample}.g.vcf",
shell:
"java -Xmx4g -jar /home/alexandre/GenomeAnalysisTK-3.7/GenomeAnalysisTK.jar -ploidy 2 --emitRefConfidence GVCF -T HaplotypeCaller -R {input.genome} -I {input.bam} --genotyping_mode DISCOVERY -o {output}"
These rules work fine. For example, if I have the files :
Cla001d_S281_L001_R1_001.fastq.gz
Cla001d_S281_L001_R2_001.fastq.gz
I can create one bam file (Cla001d_S281_L001_001.bam) and from that bam file create a GVCF file (Cla001d_S281_L001_001.g.vcf). I have a lot of sample like this one, and I need to create one GVCF file for each, and then merge these GVCF files into one file. The problem is that I'm unable to give the list of the file to merge to the following rule:
rule GATK_merge:
input:
???
output:
"merge_calling.g.vcf"
shell:
"java -Xmx4g -jar /home/alexandre/GenomeAnalysisTK-3.7/GenomeAnalysisTK.jar "
"-T CombineGVCFs "
"-R data/genome.fasta "
"--variant {input} "
"-o {output}"
I tried several things in order to do that, but cannot succeed. The problem is the link between the two rules (GATK_raw_calling and GATK_merge that is supposed to merge the output of GATK_raw_calling). I can't output one single file if I'm specifying the output of GATK_raw_calling as the input of the following rule (Wildcards in input files cannot be determined from output files), and I'm unable to make a link between the two rules if I'm not specifying these files as an input...
Is there a way to succeed in doing that? The difficulty is that I'm not defining a list of names or whatever, I think.
Thanks you in advance for your help.
You can try to generate a list of sample IDs using glob_wildcards on the initial fastq.gz files:
sample_ids, run_ids = glob_wildcards("data/Raw_reads/{sample}_R1_{run}.fastq.gz")
Then, you can use this to expand the input of GATK_merge:
rule GATK_merge:
input:
expand("Raw_calling/{sample}_{run}.g.vcf",
sample=sample_ids, run=run_ids)
If the same run ID always come with the same sample ID, you will need to zip instead of expanding, in order to avoid non-existing combinations:
rule GATK_merge:
input:
["Raw_calling/{sample}_{run}.g.vcf".format(
sample=sample_id,
run=run_id) for sample_id, run_id in zip(sample_ids, run_ids)]
You can achieve this by using a python function as an input for your rule, as described in the snakemake documentation here.
Could look like this for example:
# Define input files
def gatk_inputs(wildcards):
files = expand("Raw_calling/{sample}.g.vcf", sample=<samples list>)
return files
# Rule
rule gatk:
input: gatk_inputs
output: <output file name>
run: ...
Hope this helps.