refactor: Fgbio read clipping

workflow/rules/read_clipping.smk

@@ -20,63 +20,48 @@ rule samtools_sort:
         "v1.15.1/bio/samtools/sort"
 
 
-rule bed_to_bedpe:
+rule bed_to_tsv:
     input:
         check_bed_for_URL(config["preprocessing"]["amplicon-primers"]),
     output:
-        "resources/primer.bedpe",
+        "resources/primer.tsv",
     log:
         "logs/bed-to-bedpe.log",
     conda:
         "../envs/python.yaml"
     script:
-        "../scripts/bed-to-bedpe.py"
+        "../scripts/bed-to-tsv.py"
 
 
-rule bamclipper:
+rule trim_primers_fgbio:
     input:
         bam="results/{date}/read-sorted/{read_type}~position/{sample}.initial.bam",
         bai="results/{date}/read-sorted/{read_type}~position/{sample}.initial.bam.bai",
-        bedpe="resources/primer.bedpe",
-    output:
-        temp(
-            "results/{date}/read-clipping/softclipped/{read_type}/{sample}/{sample}.initial.primerclipped.bam"
+        ref="resources/genomes/{reference}.fasta".format(
+            reference=config["preprocessing"]["amplicon-reference"]
         ),
-    params:
-        output_dir=get_output_dir,
-        cwd=lambda w: os.getcwd(),
-        bed_path=lambda w, input: os.path.join(os.getcwd(), input.bedpe),
-        bam=lambda w, input: os.path.basename(input.bam),
+        primers="resources/primer.tsv",
+    output:
+        "results/{date}/read-clipping/hardclipped/{read_type}/{sample}/{sample}.bam",
     log:
-        "logs/{date}/bamclipper/{read_type}/{sample}.log",
+        "logs/{date}/fgbio_primer_clipping/{read_type}/{sample}.log",
     conda:
-        "../envs/bamclipper.yaml"
-    threads: 6
+        "../envs/fgbio.yaml"
     shell:
-        "(cp {input.bam} {params.output_dir} &&"
-        " cp {input.bai} {params.output_dir} &&"
-        " cd {params.output_dir} &&"
-        " bamclipper.sh -b {params.bam} -p {params.bed_path} -n {threads} -u 5 -d 5) "
-        " > {params.cwd}/{log} 2>&1"
+        "fgbio TrimPrimers -i {input.bam} -p {input.primers} -o {output} -H true -r {input.ref} > {log} 2>&1"
 
 
-rule fgbio:
+rule filter_bam_fgbio:
     input:
-        bam="results/{date}/read-clipping/softclipped/{read_type}/{sample}/{sample}.initial.primerclipped.bam",
-        bai="results/{date}/read-clipping/softclipped/{read_type}/{sample}/{sample}.initial.primerclipped.bam.bai",
-        ref="resources/genomes/{reference}.fasta".format(
-            reference=config["preprocessing"]["amplicon-reference"]
-        ),
+        bam="results/{date}/read-clipping/hardclipped/{read_type}/{sample}/{sample}.bam",
     output:
-        temp(
-            "results/{date}/read-clipping/hardclipped/{read_type}/{sample}/{sample}.bam"
-        ),
+        "results/{date}/read-clipping/hc_filtered/{read_type}/{sample}/{sample}.bam",
     log:
-        "logs/{date}/fgbio/{read_type}/{sample}.log",
+        "logs/{date}/fgbio_filter_bam/{read_type}/{sample}.log",
     conda:
         "../envs/fgbio.yaml"
     shell:
-        "fgbio --sam-validation-stringency=LENIENT ClipBam -i {input.bam} -o {output} -H true -r {input.ref} > {log} 2>&1"
+        "fgbio FilterBam -i {input.bam} -o {output} --min-insert-size 100 --remove-single-end-mappings > {log} 2>&1"
 
 
 rule samtools_fastq_pe:
@@ -131,7 +116,7 @@ rule plot_primer_clipping:
         ),
     params:
         samples=lambda wildcards: get_samples_for_date(wildcards.date),
-        bedpe="resources/primer.bedpe",
+        bedpe="resources/primer.tsv",
     log:
         "logs/{date}/plot-primer-clipping.log",
     conda:

workflow/scripts/bed-to-bedpe.py → workflow/scripts/bed-to-tsv.py

@@ -23,10 +23,9 @@
     df_sense["chrom"],
     df_sense["start"],
     df_sense["end"],
-    df_antisense["chrom"],
     df_antisense["start"],
     df_antisense["end"],
 ]
-headers = ["chrom1", "start1", "end1", "chrom2", "start2", "end2"]
+headers = ["chrom", "left_start", "left_end", "right_start", "right_end"]
 df_bedpe = pd.concat(data, axis=1, keys=headers)
-df_bedpe.to_csv(snakemake.output[0], header=None, index=None, sep="\t", mode="a")
+df_bedpe.to_csv(snakemake.output[0], index=None, sep="\t", mode="a")

workflow/scripts/plot-primer-clipping.py

@@ -13,8 +13,10 @@
 from intervaltree import IntervalTree
 
 # read primer bedpe to df
-PRIMER = pd.read_csv(snakemake.params.get("bedpe", ""), delimiter="\t", header=None)
-PRIMER.drop(PRIMER.columns[[0, 3]], axis=1, inplace=True)
+PRIMER = pd.read_csv(snakemake.params.get("bedpe", ""), delimiter="\t", header=0)
+print(PRIMER)
+PRIMER.drop(PRIMER.columns[[0]], axis=1, inplace=True)
+print(PRIMER)
 PRIMER.columns = ["p1_start", "p1_end", "p2_start", "p2_end"]
 
 # convert df to interval trees
@@ -116,7 +118,7 @@ def count_intervals(file):
                     "uncut primer within",
                     "cut primer exact",
                     "cut primer within",
-                    "no mathing win",
+                    "no matching win",
                 ],
             }
         )