Delete taxonomy.smk

workflow/rules/Multi/Collate/taxonomy.smk

-checkpoint collate_kraken:
-    input:
-        lambda wildcards: expand("{raw_directory}/Analysis/taxonomy/kraken/{{type}}.kraken.report",raw_directory=samples.loc[[a and b for a,b in zip(samples.taxonomy == 1,samples[wildcards.type] == 1)],"path"])
-    output:
-        "Collection/multi_{type}.kraken.Rdata"
-    threads: 1
-    resources:
-        runtime = "12:00:00",
-        mem = MEMCORE 
-    params:
-        samples = lambda wildcards: samples.loc[[a and b for a,b in zip(samples.taxonomy == 1,samples[wildcards.type] == 1)],"sample"],
-        out_prefix = lambda wildcards: "Collection/multi_" + wildcards.type + ".kraken."
-    log: "logs/collate_kraken_{type}.kraken.log"
-    message: 'collate_kraken: collecting kraken {wildcards.type} data.'
-    threads: 1
-    conda: ENVDIR + "/IMP_multi.yaml"
-    script:
-        SRCDIR + "/multi_collect_kraken.R"
-
-rule collate_mOTUs:
-    input:
-        lambda wildcards: expand("{raw_directory}/Analysis/taxonomy/mOTUs/{{type}}.mOTU.counts.tsv",raw_directory=samples.loc[[a and b for a,b in zip(samples.taxonomy == 1,samples[wildcards.type] == 1)],"path"])
-    output:
-        "Collection/multi_{type}.mOTUs.Rdata",
-        expand("Collection/multi_{{type}}.mOTUs.{rank}.tsv",rank=["k","p","c","o","f","g","s"])
-    threads: 1
-    resources:
-        runtime = "12:00:00",
-        mem = MEMCORE
-    params:
-        samples = lambda wildcards: samples.loc[[a and b for a,b in zip(samples.taxonomy == 1,samples[wildcards.type] == 1)],"sample"]
-    log: "logs/collate_mOTUs_{type}.mOTUs.log"
-    message: 'collate_mOTUs: collecting mOTUs {wildcards.type} data.'
-    threads: 1
-    conda: ENVDIR + "/IMP_multi.yaml"
-    script:
-        SRCDIR + "/multi_collect_mOTUs.R"
-        
-
-checkpoint collate_EukDetect:
-    input:
-        lambda wildcards: expand("{raw_directory}/Analysis/taxonomy/EukDetect/{{type}}_filtered_hits_table.txt",raw_directory=samples.loc[[a and b for a,b in zip(samples.EukDetect == 1,samples[wildcards.type] == 1)],"path"])
-    output:
-        "Collection/multi_{type}.EukDetect.Rdata",
-        expand("Collection/multi_{{type}}.EukDetect.{kind}.tsv",kind=["Read_counts","Total_marker_coverage","Percent_identity"])
-    threads: 1
-    resources:
-        runtime = "12:00:00",
-        mem = MEMCORE
-    params:
-        samples = lambda wildcards: samples.loc[[a and b for a,b in zip(samples.EukDetect == 1,samples[wildcards.type] == 1)],"sample"],
-        out_prefix = lambda wildcards: "Collection/multi_" + wildcards.type + ".EukDetect."
-    log: "logs/collate_EukDetect_{type}.EukDetect.log"
-    message: 'collate_EukDetect: collecting EukDetect {wildcards.type} data.'
-    threads: 1
-    conda: ENVDIR + "/IMP_multi.yaml"
-    script:
-        SRCDIR + "/multi_collect_eukdetect.R"
-
-localrules:  ctrl_tax_collation
-
-classifiers=["kraken","mOTUs"]
-if 1 in samples.EukDetect.unique():
-    classifiers.append("EukDetect")
-
-rule ctrl_tax_collation:
-    input:
-        expand("Collection/multi_{type}.{classifier}.Rdata",type=TYPES,classifier=classifiers)
-    output:
-        touch("status/taxonomy.collated")
-