snakemake

问题 I know there is way to declare rules that need to be executed on the local machine using localrules as: localrules: all, foo Is there a similar option to declare rules that need to be executed on the cluster? Perhaps a clusterrules option? I have a bunch of rules in my pipeline that don't need to be executed on the cluster and while I can list them all with localrules , it will be easier to just enter the one or two rules that need to be executed on the cluster. An alternative option is the

问题 I stuck in a Snakemake issue for a lone while. Propose I have a dict like: dict_A = {A:"id1","id2","id3", B:"id2","id3","id4","id5", C:"id1","id4","id5"} and I want to write rules like: input: "{dict_A.keys()}/{dict_A[key]}_R1.txt" output: "{dict_A.keys()}/{dict_A[key]}_R1_filter.txt" shell: "XXX {input} > {output}" While, I try to search on google and StackOverflow but I can't figure out this problem. Really hope there is someone can help me ! Really thanks! 回答1: Snakemake works by providing

问题 Hello Snakemake community, I am having quite some troubles to define correctly a function in Snakemake and call it in the params section. The output of the function is a list and my aim is to use each item of the list as a parameter of a shell command. In other words, I would like to run multiple jobs in parallel of the same shell command with a different parameter. This is the function: import os, glob def get_scontigs_names(wildcards): scontigs = glob.glob(os.path.join("reference",

问题 I tried to create a snakemake file to run sortmeRNA pipeline: SAMPLES = ['test'] READS=["R1", "R2"] rule all: input: expand("Clean/4.Unmerge/{exp}.non_rRNA_{read}.fastq", exp = SAMPLES, read = READS) rule unzip: input: fq = "trimmed/{exp}.{read}.trimd.fastq.gz" output: ofq = "Clean/1.Unzipped/{exp}.{read}.trimd.fastq" shell: "gzip -dkc < {input.fq} > {output.ofq}" rule merge_paired: input: read1 = "Clean/1.Unzipped/{exp}.R1.trimd.fastq", read2 = "Clean/1.Unzipped/{exp}.R2.trimd.fastq" output:

问题 Major EDIT : Having fixed a couple of issues thanks to comments and written a minimal reproducible example to help my helpers, I've narrowed down the issue to a difference between execution locally and using DRMAA. Here is a minimal reproducible pipeline that does not require any external file download and can be executed out of the box or clone following git repository: git clone git@github.com:kevinrue/snakemake-issue-all.git When I run the pipeline using DRMAA I get the following error:

问题 Major EDIT : Having fixed a couple of issues thanks to comments and written a minimal reproducible example to help my helpers, I've narrowed down the issue to a difference between execution locally and using DRMAA. Here is a minimal reproducible pipeline that does not require any external file download and can be executed out of the box or clone following git repository: git clone git@github.com:kevinrue/snakemake-issue-all.git When I run the pipeline using DRMAA I get the following error:

问题 I'm creating a Snakemake workflow that will wrap up some of the tools in the nvidia clara parabricks pipelines. Because these tools run on GPU's, they typically can only handle one sample at a time, otherwise the GPU will run out of memory. However, Snakemake shoves all the samples through to Parabricks at one time - seemingly unaware of the GPU memory limits. One solution would be to tell Snakemake to process one sample at a time, thus the question: How do I get Snakemake to process one

问题 I'm creating a Snakemake workflow that will wrap up some of the tools in the nvidia clara parabricks pipelines. Because these tools run on GPU's, they typically can only handle one sample at a time, otherwise the GPU will run out of memory. However, Snakemake shoves all the samples through to Parabricks at one time - seemingly unaware of the GPU memory limits. One solution would be to tell Snakemake to process one sample at a time, thus the question: How do I get Snakemake to process one

问题 I'm creating a Snakemake workflow that will wrap up some of the tools in the nvidia clara parabricks pipelines. Because these tools run on GPU's, they typically can only handle one sample at a time, otherwise the GPU will run out of memory. However, Snakemake shoves all the samples through to Parabricks at one time - seemingly unaware of the GPU memory limits. One solution would be to tell Snakemake to process one sample at a time, thus the question: How do I get Snakemake to process one

问题 I am having some trouble implementing a pipeline in which the first step is downloading the data from some server. As far as I understand, all rules must have inputs which are files. However, in my case the "input" is an ID string given to a script which accesses the server and downloads the data. I am aware of the remote files option in snakemake, but the server I am downloading from (ENA) is not on that list. Moreover, I am using a script which calls aspera in order to improve download