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https://github.com/y9c/m6a-sacseq

🧪 Optimized protocol for m6A-SAC-seq
https://github.com/y9c/m6a-sacseq

docker epitranscriptome epitranscriptomics m6a modification ngs pipeline rna sac-seq single-base

Last synced: 2 days ago
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🧪 Optimized protocol for m6A-SAC-seq

Host: GitHub
URL: https://github.com/y9c/m6a-sacseq
Owner: y9c
License: gpl-3.0
Created: 2022-01-07T23:11:08.000Z (almost 3 years ago)
Default Branch: main
Last Pushed: 2023-01-30T07:14:42.000Z (almost 2 years ago)
Last Synced: 2023-08-14T15:48:19.281Z (over 1 year ago)
Topics: docker, epitranscriptome, epitranscriptomics, m6a, modification, ngs, pipeline, rna, sac-seq, single-base
Language: Python
Homepage: https://sacseq.chuan.science/
Size: 15 MB
Stars: 4
Watchers: 1
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

[![Docker](https://img.shields.io/docker/pulls/y9ch/sacseq.svg)](https://hub.docker.com/r/y9ch/sacseq)
[![DOI:10.1038/s41587-022-01243-z](https://zenodo.org/badge/DOI/10.1038/s41596-022-00765-9.svg)](https://doi.org/10.1038/s41596-022-00765-9)
[![Citation Badge](https://api.juleskreuer.eu/citation-badge.php?doi=10.1038/s41596-022-00765-9)](https://www.nature.com/articles/s41596-022-00765-9/metrics)

# m⁶A-SAC-seq

## Overview of the workflow

## How to use?

A [docker image](https://hub.docker.com/r/y9ch/sacseq) containing the source code and dependencies has been published for reproducibility. You can run it using the [singularity](https://sylabs.io/singularity) container runtime.

The entire analysis can be completed in just three steps:

1. **Specific the path (with label) of both rawdata and references for your project in a YAML format.**

data.yaml for example^{(Click to expand)}

```yaml
samples:
HeLa-WT:
input:
rep1:
- R1: ./rawdata/HeLa-WT-polyA-input-rep1-run1_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-input-rep1-run1_R2.fq.gz
- R1: ./rawdata/HeLa-WT-polyA-input-rep1-run2_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-input-rep1-run2_R2.fq.gz
rep2:
- R1: ./rawdata/HeLa-WT-polyA-input-rep2-run1_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-input-rep2-run1_R2.fq.gz
- R1: ./rawdata/HeLa-WT-polyA-input-rep2-run2_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-input-rep2-run2_R2.fq.gz
treated:
rep1:
- R1: ./rawdata/HeLa-WT-polyA-treated-rep1-run1_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-treated-rep1-run1_R2.fq.gz
- R1: ./rawdata/HeLa-WT-polyA-treated-rep1-run2_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-treated-rep1-run2_R2.fq.gz
rep2:
- R1: ./rawdata/HeLa-WT-polyA-treated-rep2-run1_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-treated-rep2-run1_R2.fq.gz
- R1: ./rawdata/HeLa-WT-polyA-treated-rep2-run2_R1.fq.gz
R2: ./rawdata/HeLa-WT-polyA-treated-rep2-run2_R2.fq.gz
references:
spike:
fa: ./ref/spike_expand.fa
bt2: ./ref/spike_expand
spikeN:
fa: ./ref/spike_degenerate.fa
blast: ./ref/spike_degenerate
rRNA:
fa: ./ref/Homo_sapiens.GRCh38.rRNA.fa
bt2: ./ref/Homo_sapiens.GRCh38.rRNA
smallRNA:
fa: ./ref/Homo_sapiens.GRCh38.smallRNA.fa
bt2: ./ref/Homo_sapiens.GRCh38.smallRNA
genome:
fa: ./ref/Homo_sapiens.GRCh38.genome.fa
star: ./ref/Homo_sapiens.GRCh38.genome
gtf: ./ref/Homo_sapiens.GRCh38.genome.gtf
gtf_collapse: ./ref/Homo_sapiens.GRCh38.genome.collapse.gtf
contamination:
fa: ./ref/contamination.fa
bt2: ./ref/contamination
```

_Read the [documentation](https://y9c.github.io/m6A-SACseq/Run-the-pipeline.html#refer-rawdata-and-references-in-the-configuration-file) on how to customize._

2. **Run all the analysis by one command**:

```bash
apptainer run docker://y9ch/sacseq:latest
```

Note that when you storge your input file in a mounted partition, don't forget to add `--bind / -B` command to mount the partition.
For example, using `apptainer run -B /data docker://sacseq:latest`...

default settings^{(Click to expand)}

- default config file: `data.yaml`
- default output dir: `./results`
- default jobs in parallel: `48`

_Read the [documentation](https://y9c.github.io/m6A-SACseq/Run-the-pipeline.html#customized-analysis-parameters) on how to customize._

3. **View the analytics report and use the m⁶A sites for downstream analysis**.

The output of all the steps will be in one folder (`./results`) under the current path. A webpage report of all the analysis will be in `./results/report.html` ^{([example](https://y9c.github.io/m6A-SACseq/demo_output.html))}.

## Documentation

https://y9c.github.io/m6A-SACseq/

## Citation

- Ge, R., Ye, C., Peng, Y. et al. m6A-SAC-seq for quantitative whole transcriptome m6A profiling. Nat Protoc (2022). https://doi.org/10.1038/s41596-022-00765-9