尽管包存在于conda环境中，但在snakemake管道中找不到命令错误

Question

我在snakemake管道中得到以下错误：

Building DAG of jobs...
Using shell: /usr/bin/bash
Provided cores: 16
Rules claiming more threads will be scaled down.
Job counts:
        count   jobs
        1       long_read_assembly
        1

[Wed Jan 15 11:35:18 2020]
rule long_read_assembly:
    input: long_reads/F19FTSEUHT1027.PSU4_ISF1A_long.fastq.gz
    output: canu-outputs/F19FTSEUHT1027.PSU4_ISF1A.subreads.contigs.fasta
    jobid: 0
    wildcards: sample=F19FTSEUHT1027.PSU4_ISF1A

/usr/bin/bash: canu: command not found
[Wed Jan 15 11:35:18 2020]
Error in rule long_read_assembly:
    jobid: 0
    output: canu-outputs/F19FTSEUHT1027.PSU4_ISF1A.subreads.contigs.fasta
    shell:
        canu -p F19FTSEUHT1027.PSU4_ISF1A -d canu-outputs genomeSize=8m -pacbio-raw long_reads/F19FTSEUHT1027.PSU4_ISF1A_long.fastq.gz
        (one of the commands exited with non-zero exit code; note that snakemake uses bash strict mode!)

Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message

我假设这意味着找不到canu命令。但是Canu包确实存在于conda环境中：

(hybrid_assembly) [lamma@fe1 Assembly]$ conda list | grep canu
canu                      1.9                  he1b5a44_0    bioconda

snakefile如下所示：

workdir: config["path_to_files"]
wildcard_constraints:
    separator = config["separator"],
    sample = '|' .join(config["samples"]),

rule all:
    input:
        expand("assembly-stats/{sample}_stats.txt", sample = config["samples"])

rule short_reads_QC:
    input:
        f"short_reads/{{sample}}_short{config['separator']}*.fq.gz"

    output:
        "fastQC-reports/{sample}.html"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        """
        mkdir fastqc-reports
        fastqc -o fastqc-reports {input}
        """

rule quallity_trimming:
    input:
        forward = f"short_reads/{{sample}}_short{config['separator']}1.fq.gz",
        reverse = f"short_reads/{{sample}}_short{config['separator']}2.fq.gz",

    output:
        forward = "cleaned_short-reads/{sample}_short_1-clean.fastq",
        reverse = "cleaned_short-reads/{sample}_short_2-clean.fastq"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        "bbduk.sh -Xmx1g in1={input.forward} in2={input.reverse} out1={output.forward} out2={output.reverse}  qtrim=rl trimq=10"

rule long_read_assembly:
    input:
        "long_reads/{sample}_long.fastq.gz"

    output:
        "canu-outputs/{sample}.subreads.contigs.fasta"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        "canu -p {wildcards.sample} -d canu-outputs genomeSize=8m -pacbio-raw {input}"
rule short_read_alignment:
    input:
        short_read_fwd = "cleaned_short-reads/{sample}_short_1-clean.fastq",
        short_read_rvs = "cleaned_short-reads/{sample}_short_2-clean.fastq",
        reference = "canu-outputs/{sample}.subreads.contigs.fasta"

    output:
        "bwa-output/{sample}_short.bam"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        "bwa mem {input.reference} {input.short_read_fwd} {input.short_read_rvs} |  samtools view -S -b > {output}"


rule indexing_and_sorting:
    input:
        "bwa-output/{sample}_short.bam"
    output:
        "bwa-output/{sample}_short_sorted.bam"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        "samtools sort {input} > {output}"

rule polishing:
    input:
        bam_files = "bwa-output/{sample}_short_sorted.bam",
        long_assembly = "canu-outputs/{sample}.subreads.contigs.fasta"

    output:
        "pilon-output/{sample}-improved.fasta"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        "pilon --genome {input.long_assembly} --frags {input.bam_files} --output {output} --outdir pilon-output"

rule assembly_stats:
    input:
        "pilon-output/{sample}-improved.fasta"
    output:
        "assembly-stats/{sample}_stats.txt"

    conda:
        "/home/lamma/env-export/hybrid_assembly.yaml"

    shell:
        "stats.sh in={input} gc=assembly-stats/{wildcards.sample}/{wildcards.sample}_gc.csv gchist=assembly-stats/{wildcards.sample}/{wildcards.sample}_gchist.csv shist=assembly-stats/{wildcards.sample}/{wildcards.sample}_shist.csv > assembly-stats/{wildcards.sample}/{wildcards.sample}_stats.txt"

据我所知，调用canu的规则的语法是正确的，所以我不确定是什么导致了这个错误。

编辑:添加snakemake命令

snakemake --latency-wait 60 --rerun-incomplete --keep-going --jobs 99 --cluster-status 'python /home/lamma/faststorage/scripts/slurm-status.py' --cluster 'sbatch  -t {cluster.time} --mem={cluster.mem} --cpus-per-task={cluster.c} --error={cluster.error}  --job-name={cluster.name} --output={cluster.output} --wait --parsable' --cluster-config bacterial-hybrid-assembly-config.json --configfile yaml-config-files/test_experiment3.yaml --snakefile bacterial-hybrid-assembly.smk

Answer 1

在运行snakemake工作流时，如果要在特定于规则的conda环境中运行某些规则，则命令行调用的形式应为

snakemake [... various options ...] --use-conda [--conda-prefix <some-directory>]

如果您不告诉snakemake使用conda，则规则中的所有conda: <some_path>条目都将被忽略，并且规则将在当前激活的任何环境中运行。

--conda-prefix <dir>是可选的，但它会告诉snakemake在哪里可以找到安装的环境(如果你不指定它，.snakemake文件夹中就会安装一个conda环境，这意味着.snakemake文件夹可能会变得非常大，并且多个项目的.snakemake文件夹可能包含很多重复的conda内容)