Using MultiQC Reports

How to Interpret Multi QC Reports

Introduction to Multi QC Reports

• This section introduces the concept of multi QC reports, explaining their purpose and functionality. The speaker mentions that users may have generated their own reports or received them from collaborators.

Structure of the Report

• The report header includes information about the generation date and data directories used. A navigation bar on the left allows access to different sections of the report, each corresponding to a specific module from various bioinformatics tools.

General Statistics Table

• At the top of every report is a general statistics table that consolidates key statistics from all modules into one view. This helps in comparing sample names and identifying potential issues like poor alignment scores based on GC content or duplication rates.

Plot Types and Interactivity

• Various plot types are included in the report, such as stacked bar plots and line graphs. Users can interact with these plots by hovering for details, switching between percentages and exact numbers, hiding/showing categories, and zooming in on specific regions.

Exporting Plots

• Users can export plots in different formats (PNG or SVG), adjust scaling options for legends/titles, and download multiple plots at once through a toolbox feature. This enhances usability for presentations or publications.

Highlighting Samples

• The toolbox allows users to highlight specific samples using search strings. This feature helps focus on relevant data while graying out non-matching samples throughout the report.

Renaming Samples

• Users can rename samples directly within the interface by removing substrings or applying regex patterns for more complex renaming tasks. This customization aids in better organization of sample data according to user preferences.