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fqc's Introduction

FASTQ QA/QC Dashboard

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 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

fqc's People

Contributors

brwnj avatar meganap avatar

Stargazers

PRATYUSHA avatar  avatar johnsonz avatar soappp avatar wook2014 avatar Vivek Todur avatar L avatar Lee Bergstrand avatar  avatar Kohsuke Onoue avatar Hao avatar HuShuai avatar Brad Langhorst avatar  avatar

Watchers

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fqc's Issues

Highcharts non-commerical redistribution

The MIT license (commercial use) is probably not compatible with the Highcharts license (non-commercial use).

Non-Commercial Redistribution
You are allowed to distribute a Highsoft software product with non-commercial packages given that you fulfill two conditions:

  • Emphasize to your users that Highsoft software products are not free for commercial and Governmental use. You can do this on your download page or when your users activate a Highsoft Software Product in your application.
  • Provide a link back to www.highcharts.com in the same location.

Data tables

How do you generate values for data/tables from examples?

how to show fqc batch result?

I run fqc batch-qc to get all results. How I show using "python -m http.server --bind 192.168.1.xx 8000"? But I do not see them. I already editted js/fqc.js to change dir.

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