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sm.shape-map.mutrate.pipeline.acrc.snakemake
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sm.shape-map.mutrate.pipeline.acrc.snakemake
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## __doc__="""
## this sctrip is using for Shape-Map which seem no difference between
## SC or BULK
##
## the update of version 1.5
## cutadapt twice to remove the internal adapter which ligated which reverse transcript
##
## the change in version 2.5:
## 1) change to zy made reference
## 2) bowtie2 used two params: -k 20, -R 4
## """
##
## __author__="noahzy"
## __version__="3.0"
## __last_modify__="17-Aug-2022"
shell.executable("/bin/bash")
## unofficial bash strict mode
shell.prefix("source ~/.bashrc; set -euo pipefail;")
#ADAPTER = {"a":"TGTCTCTTATACACATCT", "A":"TGTCTCTTATACACATCT"}
ADAPTER = {"a":"CCGAGCCCACGAGAC", "A":"GACGCTGCCGACGA"} ## i5, i7
INTERADAPTER = {"g":"AAGCAGTGGTATCAACGCAGAGTACATGGG","a":"GTACTCTGCGTTGATACCAGTGCTT","G":"AAGCAGTGGTATCAACGCAGAGTACATGGG","A":"GTACTCTGCGTTGATACCAGTGCTT"}
## Riboswithes and rRNAs
RiboSwitch_WT_REF = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_WT/RiboSwitch_Ref_WT.bowtie2/RiboSwitch_Ref_WT"
RiboSwitch_MT_REF = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_MT/RiboSwitch_Ref_MT.bowtie2/RiboSwitch_Ref_MT"
Riboswitch_WT_FASTA = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_WT/RiboSwitch_Ref_WT.fa"
Riboswitch_MT_FASTA = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_MT/RiboSwitch_Ref_MT.fa"
Riboswitch_WT_SAF = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_WT/RiboSwitch_Ref_WT.saf"
Riboswitch_MT_SAF = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_MT/RiboSwitch_Ref_MT.saf"
RiboSwitches_WT_BED = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_WT/RiboSwitch_Ref_WT.bed"
RiboSwitches_MT_BED = "/home/users/astar/gis/zhangyu2/scratch/Projects/Genome_Reference/RiboSwitches_Ref/RiboSwitches_MT/RiboSwitch_Ref_MT.bed"
CUTADAPT = "/home/users/astar/gis/zhangyu2/.conda/envs/Env_py3/bin/cutadapt"
BOWTIE2 = "/home/users/astar/gis/zhangyu2/.conda/envs/Env_py3/bin/bowtie2"
BEDTOOLS = "/home/users/astar/gis/zhangyu2/.conda/envs/Env_py3/bin/bedtools"
SAMTOOLS = "/home/users/astar/gis/zhangyu2/local_bin/samtools"
FEATURECOUNT = "/home/users/astar/gis/zhangyu2/.conda/envs/Env_py3/bin/featureCounts"
BAMREADCOUNT = "/home/users/astar/gis/zhangyu2/local_bin/bam-readcount"
GETMUTRATE = "/home/users/astar/gis/zhangyu2/scratch/Projects/scSHAPE_Map/scSHAPE_scripts/get_mutrate.v3.4.py"
FILTERMUTRATE = "/home/users/astar/gis/zhangyu2/scratch/Projects/scSHAPE_Map/scSHAPE_scripts/filter_mutrate.py"
def get_id():
import os
import glob
fqi = glob.glob("merged*fq.gz")[0]
id = os.path.abspath(fqi).split('/')[-2]
return id
ID = get_id()
print (ID)
if "WT" in ID:
BOWTIEIDX = RiboSwitch_WT_REF
ANNOTATED_SAF = Riboswitch_WT_SAF
TX_EBD = RiboSwitches_WT_BED
REFFA = Riboswitch_WT_FASTA
elif "MT" in ID:
BOWTIEIDX = RiboSwitch_MT_REF
ANNOTATED_SAF = Riboswitch_MT_SAF
TX_EBD = RiboSwitches_MT_BED
REFFA = Riboswitch_MT_FASTA
ID = ID.split("_")[0]
print (ID)
def get_fq(r):
import glob
#print (glob.glob("R*_R{}_001.fastq.gz".format(r)))
#return glob.glob("R*_R{}.fastq.gz".format(r))
#print (glob.glob("merged*{}.fq.gz".format(r)))
return glob.glob("merged.R*.{}.fq.gz".format(r))
rule all:
input:
bai1 = ID+".transcripts.bam.bai",
bai2 = ID+".transcripts.md.bam.bai",
filter_pos_bed = ID+".mutrate.filter_pos.merge.bed",
#out_gzip = ID+".mutrate.txt.gz",
#filtered_mutrate = ID+".mutrate.filter.gz",
rule cutadapt:
input:
fqi = get_fq(1),
fqj = get_fq(2),
output:
trim_fqi = temp("{ID}.R1.cutadapt.fastq.gz"),
trim_fqj = temp("{ID}.R2.cutadapt.fastq.gz"),
params: min_len=30
shell:"""
{CUTADAPT} -m {params.min_len} -a {ADAPTER[a]} -A {ADAPTER[A]} \
-o {output.trim_fqi} -p {output.trim_fqj} {input.fqi} {input.fqj}
"""
rule cutadapt2:
input:
fqi = rules.cutadapt.output.trim_fqi,
fqj = rules.cutadapt.output.trim_fqj,
output:
trim_fqi = "{ID}.R1.cutadapt2.fastq.gz",
trim_fqj = "{ID}.R2.cutadapt2.fastq.gz",
params: min_len=30
shell:"""
{CUTADAPT} -m {params.min_len} -g {INTERADAPTER[g]} -a {INTERADAPTER[a]} -G {INTERADAPTER[G]} -A {INTERADAPTER[A]} \
-o {output.trim_fqi} -p {output.trim_fqj} {input.fqi} {input.fqj}
"""
rule bowtie_map:
input:
fqi = rules.cutadapt2.output.trim_fqi,
fqj = rules.cutadapt2.output.trim_fqj,
bowtie_index = BOWTIEIDX
output:
bam="{ID}.transcripts.bam"
params: k=20, R=4,
shell:"""
{BOWTIE2} --quiet -k {params.k} -R {params.R} -p 4 -x {input.bowtie_index} \
-1 {input.fqi} -2 {input.fqj} | \
{SAMTOOLS} view -@ 4 -bS | {SAMTOOLS} sort -@ 4 -o {output.bam}
"""
rule bam_idx:
input:
bam1 = rules.bowtie_map.output.bam,
output:
bai1 = "{ID}.transcripts.bam.bai",
shell:"""
{SAMTOOLS} index {input.bam1} {output.bai1};
"""
rule featurecounts:
input:
bam = rules.bowtie_map.output.bam,
annotation=ANNOTATED_SAF,
output:
fcout= "{ID}.featurecount"
params:
T=1,
F='SAF',
shell:"""
{FEATURECOUNT} -M -d 20 -D 100000 -T {params.T} -F {params.F} \
-a {input.annotation} -o {output.fcout} {input.bam}
"""
rule calculate_md:
input:
bam = rules.bowtie_map.output.bam,
reffa=REFFA
output:
mdbam = temp("{ID}.transcripts.md.bam")
params:
T=2
shell:"""
{SAMTOOLS} fillmd -@ {params.T} -euArE {input.bam} {input.reffa} > {output.mdbam}
"""
rule bam_idx_2:
input:
bam1 = rules.calculate_md.output.mdbam,
output:
bai1 = "{ID}.transcripts.md.bam.bai",
shell:"""
{SAMTOOLS} index {input.bam1} {output.bai1};
"""
rule bam_readcount:
input:
bam = rules.calculate_md.output.mdbam,
reffa=REFFA,
txbed=TX_EBD,
bai = rules.bam_idx_2.output.bai1
output:
pos_count = "{ID}.bam_readcount.txt.gz"
shell:"""
{BAMREADCOUNT} -w 0 -f {input.reffa} -l {input.txbed} {input.bam} | gzip -c > {output.pos_count}
"""
rule calculate_mutrate:
input:
pos_count = rules.bam_readcount.output.pos_count,
fc = rules.featurecounts.output.fcout
output:
out_gzip = "{ID}.mutrate.txt.gz",
params:
win_len = 0, ## window length must be > 50% of the gene length
gene_output_cov_threshold = 10 ## coverage threshold is 10/1M reads
shell:"""
{GETMUTRATE} -i {input.pos_count} -e {input.fc} -o {output.out_gzip} \
-d each_gene -w {params.win_len} -gc {params.gene_output_cov_threshold}
"""
rule filter_by_cov:
input:
mutrate = rules.calculate_mutrate.output.out_gzip,
output:
filtered_mutrate = "{ID}.mutrate.filter.gz",
params:
cov_threshold=10,
type="ncov"
shell:"""
{FILTERMUTRATE} -i {input.mutrate} -o {output.filtered_mutrate} -c {params.cov_threshold} -t {params.type}
"""
rule merge_to_filter_pos_bed:
input:
filter_mutrate = rules.filter_by_cov.output.filtered_mutrate
output:
filter_pos_bed = "{ID}.mutrate.filter_pos.merge.bed"
shell:"""
{BEDTOOLS} merge -i {input.filter_mutrate} > {output.filter_pos_bed}
"""