dawneve/snakemakeworkflow

Bioinformatics-pipeline in snakemake.

snakemakeworkflow's Issues

Paper of Snakemake

Paper list

2012: Snakemake—a scalable bioinformatics workflow engine

https://pubmed.ncbi.nlm.nih.gov/22908215/
https://academic.oup.com/bioinformatics/article/28/19/2520/290322

2021: Sustainable data analysis with Snakemake

https://f1000research.com/articles/10-33/v2

Code style:

Figure 3. Example Snakemake workflow.

(a) workflow definition; hypothesized knowledge requirement for line readability is color-coded on the left next to the line numbers.
(b) directed acyclic graph (DAG) of jobs, representing the automatically derived execution plan from the example workflow; job node colors reflect rule colors in the workflow definition.
(c) content of script plot-hist.py referred from rule plot_histogram.
(d) knowledge requirements for readability by statement category (see subsection 3.3).

The example workflow downloads data, plots histograms of city populations within a given list of countries, and converts these from SVG to PDF format. Note that this is solely meant as a short yet comprehensive demonstration of the Snakemake syntax.

Figure 7. Workflow composition capabilities of Snakemake.

Single or multiple external workflows can be declared as modules, along with the selection of all or specific rules. Properties of rules can be overwritten, and the analysis can be extended with further rules.

Figure 8. Additional design patterns for Snakemake workflows.

For brevity only rule properties that are necessary to understand each example are shown (e.g. omitting log directives and shell commands or script directives).
(a) scatter/gather process,
(b) streaming,
(c) non-file parameters,
(d) iteration,
(e) sample sheet based configuration,
(f) conditional execution,
(g) benchmarking,
(h) parameter space exploration. See subsection 3.2 for details.

ATAC-seq: from fastq to peaks

1. 可能是 ATAC-seq 方法的原始文献 (nature methods, 2023)

https://www.nature.com/articles/nmeth.2688
Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position
表观测序领域大牛William J Greenleaf和Howard Y Chang的经典之作，引用上千次的ATAC经典原文

2. ENCODE的ATAC-seq数据标准

• 来源：https://www.encodeproject.org/atac-seq ATAC-seq Data Standards and Processing Pipeline

3. 一个english博客，含代码

https://yiweiniu.github.io/blog/2019/03/ATAC-seq-data-analysis-from-FASTQ-to-peaks/

4. ATAC-seq 综述 （Genome Biol. 2020）

https://pubmed.ncbi.nlm.nih.gov/32014034/ From reads to insight: a hitchhiker's guide to ATAC-seq data analysis

---

其他的工具 macs，bowtie，igv 有对应的官网，也有网友写的中文博客