UMseqflow

Welcome. UMseqflow is an easy and updated snakemake bioinformatics workflow for simplying the analysis workflow.

structure:

.
├── LICENSE
├── RNA
│   ├── Snakefile_rna_v04
│   ├── configs
│   │   ├── config.yaml
│   │   └── metadata.csv
│   └── rules
│       ├── common.smk # Input and output
│       ├── preprocessing.smk # QC and trim
│       ├── hisat.smk # hisat2+featurecount
│       └── salmon.smk 
│       ├── multiqc.smk # multiqc for all steps
├── readme.md
└── setup.md

Only provide RNA mode currently.

TODO

Major

• WES mode
• package into docker
• Publish to GitHub
• reason: Code has changed since last execution, fix

Minor

• Revise trim mode
• Update Ref files into ali netdisk
• trim part qc is slow(run trim, run other part)

Prepare

First prepare analysis environment follow setup.md include conda, ref files.

Set up the configs/config.yaml, configs/metadata.csv

First move or use script from Other useful sript by soft link to ./raw folder:

$ ls raw
HB_1_1.fq.gz  HB_1_2.fq.gz  UH_1_1.fq.gz  UH_1_2.fq.gz

Then run for making metadata.csv :

echo "sample" > metadata.csv
ls raw/*.fq.gz | sed 's/_[12].fq.gz$//' | sed 's|^raw/||' | sort | uniq >> metadata.csv
mv metadata.csv configs/metadata.csv

RNA

You can decide call salmon, hisat2+featurecount or both by leaving the path for these index empty or not.

Run

nohup snakemake -p --cores 42 -s Snakefile_rna_v04 &

snakemake -np -s Snakefile_rna_v04
# dry-mode for test

You can visualize the pipeline through graphviz:

snakemake --dag -s RNA/Snakefile_rna_v04 | dot -Tpdf > workflow.pdf

snakemake --dag -s Snakefile_rna_v04 | dot -Tpng > workflow.png

Other useful sript

• soft link all fq into raw folder

find ../../X201SC24128617-Z01-F001/01.RawData -type f -name '*fq.gz' -exec ln -s {} . \;

• make a metadata

echo "sample" > config.yaml/metadata.csv && ls SRR* | sed 's/_[12]\.fastq\.gz$//' | sort | uniq >> config.yaml/metadata.csv

• rename fq

for file in *.fastq.gz; do mv "$file" "${file/fastq/fq}"; done

Milestones

250215

publish to github. Welcome!

Contribution

You can follow other projects which I also referenced:

Fred-White94/snakemake_rnaseq: A Snakemake pipeline to go from fastq mRNA sequencing files to raw and normalised counts (usable for downstream EDA and differential analysis)

tjbencomo/ngs-pipeline: Pipeline for Somatic Variant Calling with WES and WGS data

zhxiaokang/RASflow: RNA-Seq analysis workflow

基于GATK4标准找变异方法的自动化工作流程oVarFlow的使用-腾讯云开发者社区-腾讯云

toturial: Snakemake for Biostatistics Quick-Start Tutorial

https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/

#snakemake 北野茶缸子

Or you can connect with me: [email protected]

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Why I am choosing Smk instead of others

nextflow, galaxy...