Commit b10af531 authored by Slaheddine Kastalli's avatar Slaheddine Kastalli
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README modification

parent 3034b24e
# DADA2 pipeline
DADA2 is a pipeline based on dada2 (Callahan et al., 2016) R package which consists of a series of steps to filter the raw sequences obtained through Illumina sequencing. The final step aims to obtain the taxonomy of the sequences that have been filtered in order to study the microbial community.
DADA2 is a Snakemake workflow based on dada2 (Callahan and al., 2016) and FROGS (Escudié and al, 2018) method which consists of a series of steps to filter the raw sequences obtained through Illumina sequencing. The final step aims to obtain the taxonomy of the sequences that have been filtered in order to study the microbial community.
Running DADA2 consists on calling a single command from the command line.
The output data format include biom format, phyloseq objets and R data sets.
## Getting ready
First we clone the git repository, in your line command go to your working directory and past the line below.
......@@ -28,16 +29,19 @@ mkdir DATA
![global_graph-1](/uploads/7d1f46b682826deb35e9df6506a2b73d/global_graph-1.png)
## Steps of dada2
* primer removal - using preprocess
* quality filtering and trimming - using preprocess
* learn the error rates - using dada2
* sample inference - using dada2
* construct the sequence table - using dada2
* chimera removal - using dada2
* track reads through the pipeline - using dada2
* primer removal - using preprocess.smk
* quality filtering and trimming - using preprocess.smk
* learn the error rates - using dada2.smk
* sample inference - using dada2.smk
* construct the sequence table - using dada2.smk
* chimera removal - using dada2.smk
* track reads through the pipeline - using dada2.smk
* taxonomic classification- using FROGS with affiliation.smk
* treeing- using affiliation.smk
* hand-off in biom-format, as R object, as R phyloseq object, and tab-separated tables- using affiliation.smk
## Running snakemake manually
Once you have all the files, edit the config.json file with your raw fastq
Once you have all the files, edit the config.json file with your raw fastq and other requirements.
* Example
```json
{
......@@ -62,3 +66,5 @@ At this point you have all the data needed to run the pipeline.
```shell
./RunSnake.sh global.smk
```
* The config file (in json format) is read by Snakemake to determine the inputs, steps, arguments and outputs.
* All raw data (usually fastq gziped files) need to be in one directory (DATA).
\ No newline at end of file
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