https://github.com/pnnl/fqc
:chart_with_upwards_trend: Extensible quality control dashboard built around FASTQ assessment.
https://github.com/pnnl/fqc
dashboard fastq fastq-qa
Last synced: 6 months ago
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:chart_with_upwards_trend: Extensible quality control dashboard built around FASTQ assessment.
- Host: GitHub
- URL: https://github.com/pnnl/fqc
- Owner: pnnl
- License: mit
- Created: 2017-02-28T15:34:47.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-05-17T21:11:07.000Z (over 6 years ago)
- Last Synced: 2025-04-12T05:14:15.426Z (6 months ago)
- Topics: dashboard, fastq, fastq-qa
- Language: JavaScript
- Homepage: https://pnnl.github.io/fqc/
- Size: 35.5 MB
- Stars: 14
- Watchers: 8
- Forks: 11
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# FASTQ QA/QC Dashboard
FQC is designed to better group FastQC result data across groups where each
group is comprised of FASTQs related to an experiment or sequencing batch.
Individual samples are grouped into paired-end sets when available and the
dashboard's extensibility allows a user to add plots or tables as desired.
# Complete Documentation
To see the full documentation and get started, see:
https://pnnl-fqc.readthedocs.io/
Live example:
https://pnnl.github.io/fqc/
# Requires
Parsing the table and running `FastQC` is performed with code written for
Python 3. We recommend using [Anaconda](https://www.continuum.io/downloads) to
install the FastQC dependency.
## Set Up BIOCONDA channels
```
conda config --add channels conda-forge
conda config --add channels defaults
conda config --add channels bioconda
```
## Install Dependency
```
conda install fastqc
```
# Install
The dashboard reads local files, so install where you will eventually be
serving the site.
```
git clone https://github.com/pnnl/fqc.git
cd fqc
python setup.py install
```
This installs `fqc` command-line tool to process FASTQs and create the
dashboard.
Then to deploy a local copy from within the `fqc` directory, you can run:
```
python -m http.server --bind localhost 8000
```
And navigate to `localhost:8000` in your browser.
By default, this will show the test data QC as determined by the data
directory in `js/fqc.js`:
```
var filePath = "/example/plot_data/"
```
Edit `fqc.js` to your local path **within** the `fqc` directory tree.
# Processing a FASTQ
The first time this is run, it will build the entire backend of the site.
Additional FASTQs being written to the same output directory are added to
the backend according to Group ID and UID.
## Single-end FASTQ
```
$ fqc qc group sample sample_r1.fastq.gz
[2016-07-26 13:24 INFO] Writing data to: plot_data/group/sample
[2016-07-26 13:24 INFO] Running FastQC
[2016-07-26 13:27 INFO] Extracting data from FastQC archives
[2016-07-26 13:27 INFO] Processing of sample1 complete
```
## Paired-end FASTQs
```
fqc qc --r2 sample_r2.fastq.gz 2016 sample sample_r1.fastq.gz
```
# Citation
Joseph Brown, Meg Pirrung, Lee Ann McCue; FQC Dashboard: integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool. Bioinformatics 2017 doi: [10.1093/bioinformatics/btx373](https://doi.org/10.1093/bioinformatics/btx373)