My NGS workflows based on snakemake
workflows include:
- RNA-seq (Salmon,hisat2)
- ChIP-seq (MACS2)
- ATAC-seq (MACS2)
- CITE-seq (Antibody captured, 10X genomics)
- Germline SNV calling (GATK, BCFtools)
- Germline Structural Variant calling
- short-read: Speedseq + svtools
- long-read:
- Pacbio: ngmlr/minimap2 + sniffiles
-
General
- samtools, deeptools, bedtools
- fastqc, rseqc, multiqc, fastp
- graphviz
-
python 3
- numpy
- pandas
- snakemake
- matplotlib
- seaborn
- gseapy
- macs2
- rseqc
-
R
- DESeq2
- tximport
- readr
- pheatmap
- ggplot2
- ggrepel
- clusterProfiler
- ChIPSeeker
- EnsDb.Hsapiens.v86
-
Variant calling
- GATK (> 4.0)
- BCFtools
- Speedseq + svtools
- minimap2
- ngmlr
- sniffiles
-
RNA-seq
- hisat2, salmon
- rMATS-turbo, rmats2sashimiplot
-
Single cell genomics
- cellranger
bash snakeflow-enviroment-setup.sh
# Step1: activate snakemake
source activate snakeflow
# Step2: clone this repo
# Step3: copy all your fastq files into fastq dir
find . -name "*fastq.gz" | while read id; do cp $id fastq/; done;
# Step4: modify config.yml with your own paramter
# Note: put config.yml in the same dir with your snakefile.
vim config.yml
# Step5: run snakemake with -np option. this test your ``commands`` runs without any errors.
snakemake -s salmon-tximport-deseq2-v0.2.snakefile -np
# Step6: export workflow charts
snakemake -s salmon-tximport-deseq2-v0.2.snakefile --dag | dot -Tpdf > dag.pdf
# Step7: or using the default snakemake environment you've created above.
snakemake -s salmon-tximport-deseq2-v0.1.snakefile -p -j 8