119 lines
3.6 KiB
Plaintext
119 lines
3.6 KiB
Plaintext
def get_model_name(wildcards):
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config_param=f'{wildcards.model}_model_name'
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return config[config_param]
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def get_model_requirement(wildcards):
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config_param=f'{wildcards.model}_model_name'
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return config['dorado_model_dir']+'/'+config[config_param]
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def get_benchmarking_file(wildcards):
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config_param = f'{wildcards.model}_benchmarks_file'
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if config[config_param]:
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return f'--batchsize-benchmarks-file {config[config_param]}'
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return ''
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def get_qscore(wildcards):
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config_param = f'{wildcards.model}_min_q'
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if config[config_param]:
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return f'--min-qscore {config[config_param]}'
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return ''
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def get_batch_names(input_file):
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with open(input_file,'rt') as ih:
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return [line.strip().split('/')[-1].split('.')[0] for line in ih]
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def get_run_name(wildcards):
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if wildcards.dataset == 'nomiss':
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return 'PBK98658_853a956f_57f83f46'
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if wildcards.dataset == 'trap':
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return 'ATCC_25922_202309'
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def get_batch_range(wildcards):
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if wildcards.dataset == 'nomiss':
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return range(1,config['pod5_dataset_size']+1,config['pod5_stride'])
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if wildcards.dataset == 'trap':
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return [0]
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rule download_nomiss_pod5:
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output:
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'../data/raw_pod5/nomiss/PBK98658_853a956f_57f83f46_{batch}.pod5'
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threads: 1
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wildcard_constraints:
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batch="\d+"
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shell:
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"""
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aws s3 cp --no-sign-request s3://ont-open-data/nomiss_96BC_P2I_SUP_2026/raw/pod5/PBK98658_853a956f_57f83f46_{wildcards.batch}.pod5 {output}
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"""
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rule download_trap_pod5:
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output:
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'../data/raw_pod5/trap/ATCC_25922_202309_0.pod5'
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threads: 1
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wildcard_constraints:
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batch='\d+'
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shell:
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"""
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curl -L "https://api.figshare.com/v2/file/download/45408628" -o {output}
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"""
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rule basecall_pod5:
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input:
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pod5='../data/raw_pod5/{dataset}/{run}_{batch}.pod5',
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model=get_model_requirement
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output:
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temp('../data/basecalled_reads/{dataset}/{model}/{run}_{batch}.fastq')
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threads:
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32
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resources:
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gpu=1
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params:
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benchmarking=get_benchmarking_file,
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min_qscore=get_qscore,
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dorado_model=get_model_name
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wildcard_constraints:
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batch="\d+",
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model="hac|fast"
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shell:
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"""
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dorado basecaller --models-directory {config[dorado_model_dir]} --emit-fastq {params.benchmarking} {params.min_qscore} {params.dorado_model} {input.pod5} > {output}
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"""
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rule concatenate_basecalled_fastq:
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input:
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expand('../data/basecalled_reads/{{dataset}}/{{model}}/{run}_{batch}.fastq',batch=get_batch_range,run=get_run_name)
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output:
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'../data/basecalled_reads/{dataset}_{model}.fastq.gz'
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threads: 1
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wildcard_constraints:
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model="hac|fast"
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shell:
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"""
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cat {input} | gzip -c > {output}
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"""
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rule align_reads_to_reference:
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input:
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fastq='../data/basecalled_reads/{dataset}_{model}.fastq.gz',
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ref='../data/reference_genomes/full_reference.mmi'
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output:
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'../data/aligned_reads/{dataset}_{model}_to_genome.sam'
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threads: 32
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conda:
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'../envs/minimap.yaml'
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shell:
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"""
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minimap2 -ax map-ont -t {threads} {input.ref} {input.fastq} > {output}
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"""
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rule convert_sam_to_bam:
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input:
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'../data/aligned_reads/{dataset}_{model}_to_genome.sam'
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output:
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'../data/aligned_reads/{dataset}_{model}_to_genome.sorted.bam'
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threads: 32
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conda:
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'../envs/samtools.yaml'
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shell:
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"""
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samtools view -b -@ {threads} {input} | samtools sort -@ {threads} > {output}
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samtools index -@ {threads} {output}
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""" |