EasyMAF

Introduction

EasyMAF is an interactive web based application developed in R using Shiny, to analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. The application aims to provide users with an easy and interactive user interface to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualizations with minimal effort.

1. Data Input

The input data for this app requires 2 files in '.maf.gz' and '.tsv' format.

Required input files:

• a MAF file - can be gz compressed.
• an optional but recommended clinical data associated with each sample/Tumor_Sample_Barcode in MAF.
• an optional copy number data if available. Can be GISTIC output or a custom table containing sample names, gene names and copy-number status.

An example of MAF file named as 'sample_maf.tsv' can be accessed here. Similarly an example of copy-number data named as 'sample_copy-number_data.tsv' can be accessed here.

2. Summary and Visualization

maftools package provides various functions to perform widely used analyses in cancer genomics and to create feature rich customizable visualizations.

Information on sample summary, gene summary, clinical data associated with samples, fields in MAF file can be obtained. It also provides various functions to visualize MAF files. These include:

• Plotting MAF summary
• Oncoplots
• Oncostrip
• Transitions and Transversions
• Lollipop Plot
• Rainfall Plot
• Compare mutation load against TCGA cohorts
• VAF Plots
• Genecloud

3. Processing copy-number data

Varoius functions are available in the package for processing copy-number data. Summary of output files generated by GISTIC programme can be obtained. As mentioned earlier, we need four files that are generated by GISTIC, i.e, all_lesions.conf_XX.txt, amp_genes.conf_XX.txt, del_genes.conf_XX.txt and scores.gistic, where XX is the confidence level. See GISTIC documentation for details. There are 3 types of plots available to visualize gistic results:

• Genome Plot
• Bubble Plot
• Oncoplot

4. Analysis

maftools package also provides numerous functions for analyzing copy-number data. These functions are implemented in the interface for easy understanding of the analyses process.

Functions available in the package for analysis include:

• Somatic Interactions
• Detecting cancer driver genes based on positional clustering
• Adding and summarizing pfam domains
• Pan-Cancer comparision
• Survival analysis
• Clinical Enrichment Analysis
• Oncogenic signalling pathways