Introduction

If you're running MultiQC all the time, then make use of that data!

MegaQC stores MultiQC results
in a database for long term analysis

An open-source web tool, scalable to hundreds of thousands of samples.
Monitor key metrics with trend plots, explore your data like never before.

Features

MegaQC works the way you do

Quickly answer questions and monitor long term trends

Explore your data

Interactive plots allow you to reproduce graphs from MultiQC, but with dynamic sample filtering across multiple projects.

How does read-1 sequence quality compare between the NovaSeq and the HiSeq 3000?

Plot metrics

Distribution and comparison plots allow you to study single-value metrics at scale.

Is there a sub-group of samples with low Ts/Tv variant rates?
Does sample GC content correlate with alignment rate?

Monitor trends

Trend plots allow you to track metrics over time and spot outliers or long-term trends.

Has the read coverage of the capture regions changed over the past six months?

Build dashboards

A drag-and-drop interface allows you to quickly and easily build dashboards showing your favourite plots.

Computer: Status update please.

Easy to install

Built using the Python Flask framework with support for any SQL database backend.

Quick testing on my laptop with flask and SQLite
Production installation using Docker image with Gunicorn and PostgreSQL

Multiple users

User accounts let people create their own favourite plots and dashboards.

Jack runs the sequencers and keeps an eye on the yield
Jill preps RNA libraries and monitors rRNA content
Getting Started

Are you familiar with MultiQC?

MegaQC relies on MultiQC; it's little brother.
If you're not sure what that is, then check out http://multiqc.info first…

Overview of features

A quick tour of what MegaQC can do: see the highlights and get the postcard!
[34s]

Basic usage

Screencast of logging in for the first time, uploading data and creating some plots
[4m 24s]

Installation instructions

An overview of how to install MegaQC - from personal laptop to production server.
[6m 49s]