intial version
This commit is contained in:
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NCBI_API_KEY=
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import os
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from dotenv import load_dotenv
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load_dotenv()
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configfile: "config/main.yaml"
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configfile: "config/dependencies.yaml"
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configfile: "../reference/species_list.yaml"
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module preparation:
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snakefile: "rules/preparation.smk"
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config: config
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module baseline:
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snakefile: "rules/baseline_pipeline.smk"
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config: config
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# Pulldown
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rule all:
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input:
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#"binaries/datasets",
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#f"{config['dorado_model_dir']}/{config['fast_model_name']}",
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#f"{config['dorado_model_dir']}/{config['hac_model_name']}",
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#'../data/reference_genomes/full_reference.mmi',
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#'../data/raw_pod5/'
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#'../data/pod5_files_to_pull',
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#'../data/basecalled_reads/hac.fastq.gz'
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expand('../data/raw_pod5/PBK98658_853a956f_57f83f46_{batch}.fastq.gz',batch=range(1,config["pod5_dataset_size"]+1,config["pod5_stride"]))
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use rule * from preparation
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use rule * from baseline
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arch: "amd64"
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datasets_binary : "binaries/datasets"
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tmp_dir: "/tmp"
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# dorado
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dorado_model_dir : "../dorado_models"
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hac_model_name: "dna_r10.4.1_e8.2_400bps_hac@v6.0.0"
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hac_benchmarks_file: "" # add path if available
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hac_min_q: 9 # empty string or 0 to disable
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fast_model_name: "dna_r10.4.1_e8.2_400bps_fast@v5.2.0"
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fast_benchmarks_file: "" #add path if available
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fast_min_q: 8 # empty string or 0 to disable
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# squiqqle dataset
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pod5_dataset: "nomiss_96BC_P2I_SUP_2026"
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pod5_dataset_size : 293
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pod5_stride : 12 # Use 1 in x pod5 files from the ONT NO-MISS dataset to reduce dataset size / compute requirements
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channels:
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- bioconda
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dependencies:
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- minimap2
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channels:
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- conda-forge
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dependencies:
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- python=3.14
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- pip
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- pip:
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- pod5
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channels:
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- bioconda
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dependencies:
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- htslib
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- samtools
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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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return f"{config['dorado_model_dir']}/{config[f'{wildcards.model}_model_name']}
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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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rule download_pod5:
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output:
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'../data/raw_pod5/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 basecall_pod5:
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input:
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pod5='../data/raw_pod5/PBK98658_853a956f_57f83f46_{batch}.pod5',
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model=get_model_requirement
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output:
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'../data/basecalled_reads/{model}/PBK98658_853a956f_57f83f46_{batch}.fastq.gz'
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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/{{model}}/PBK98658_853a956f_57f83f46_{batch}.fastq.gz',batch=range(1,config["pod5_dataset_size"]+1,config["pod5_stride"]))
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output:
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'../data/basecalled_reads/{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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zcat {input} > {output}
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"""
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import os
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import hashlib
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# Prepwork
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def get_genome_file_name(wildcards):
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return '../data/reference_genomes/'+'_'.join(x.lower() for x in wildcards.species.split())+'.fasta'
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def get_unique_download_dir(wildcards):
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unique_id = hashlib.md5(wildcards.species.encode()).hexdigest()[:8]
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return config["tmp_dir"]+'/'+unique_id
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def format_cli_arg(wildcards):
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# Replaces underscores with spaces for the CLI command
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return wildcards.species.replace("_", " ")
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rule pull_ncbi_datasets_cli:
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output:
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config["datasets_binary"]
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params:
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arch=config["arch"]
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threads: 1
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shell:
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"""
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curl https://ftp.ncbi.nlm.nih.gov/pub/datasets/command-line/v2/linux-{params.arch}/datasets -o {output}
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chmod a+x {output}
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"""
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rule pull_dorado_models:
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output:
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directory(f"{config['dorado_model_dir']}/{config['fast_model_name']}"),
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directory(f"{config['dorado_model_dir']}/{config['hac_model_name']}")
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threads: 1
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shell:
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"""
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dorado download --models-directory {config[dorado_model_dir]} --model {config[fast_model_name]}
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dorado download --models-directory {config[dorado_model_dir]} --model {config[hac_model_name]}
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"""
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rule download_reference_genome:
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input:
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config["datasets_binary"]
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output:
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temp('../data/reference_genomes/{species}.fasta')
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params:
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api_key=os.environ['NCBI_API_KEY'],
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wd=get_unique_download_dir,
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ncbi_tax_name=lambda w: format_cli_arg(w)
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threads: 1
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shell:
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"""
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echo {wildcards.species}
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rm -rf {params.wd}
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mkdir {params.wd}
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{config[datasets_binary]} download genome taxon "{params.ncbi_tax_name}" --reference --no-progressbar --filename {params.wd}/{wildcards.species}.zip
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unzip -d {params.wd} -o {params.wd}/{wildcards.species}.zip
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mv {params.wd}/ncbi_dataset/data/*/*fna {output}
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rm -rf {params.wd}
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"""
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rule concatenate_reference_genomes:
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input:
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expand("../data/reference_genomes/{species}.fasta",species=config["species_list"])
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output:
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"../data/reference_genomes/full_reference.fasta"
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threads: 1
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shell:
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"""
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cat {input} > {output}
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"""
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rule create_minimap_index:
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input:
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"../data/reference_genomes/full_reference.fasta"
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output:
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"../data/reference_genomes/full_reference.mmi"
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threads:
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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 -x map-ont -t {threads} -d {output} {input}
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"""
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@@ -0,0 +1,11 @@
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from typing import TYPE_CHECKING
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from pathlib import Path
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if TYPE_CHECKING:
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from snakemake.iocontainers import snakemake
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def download_species_fasta(species_name:str, ncbi_datasets_binary: str, tmp_dir : Path) -> Path:
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"""Download the reference genome fasta for a given species"""
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output_fasta = tmp_dir / f'{species_name}.fasta'
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