Mutational Signatures of Small Insertions and Deletions

Small insertions and deletions, "indels", are mutations that add or delete short (< ~50 base pairs) sequences of DNA.

This web site presents corresponding signatures extracted from somatic indel mutations in 6,975 tumors from 36 cancer types using methods based on Non-negative Matrix Factorization and Hierarchical Dirichlet Processes.


476-Type Classification

This new classification (Koh et al., 2025) recognizes 476 types of indels. It provides the highest resolution for analyzing similarities and differences between signatures.

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89-Type Classification

This new classification (Koh et al., 2025) recognizes 89 types of indels. Often provides more informative granularity for indels in homopolymers.

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83-Type Classification

This widely used classification recognizes 83 types of indels. Described in Alexandrov et al., 2020 and used on the COSMIC mutational signatures web site.

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1. Upload VCF File

Upload your variant calling file to generate Mutational Signatures.

Or try our examples:

2. Process

Search Signatures

Enter a signature name (e.g., 'InsDel') to find matches

Project Overview

Indel mutational signatures provide crucial insights into the mutational processes operative in human cancer. While single base substitution (SBS) signatures have been extensively cataloged, the classification and analysis of small insertions and deletions (indels) present unique challenges due to their complexity.

This web application serves as a comprehensive interactive browser for exploring indel signatures derived from 6,975 tumors across 36 cancer types . It integrates multiple classification schemes (83-type, 89-type, and 476-type) to provide multi-granular perspectives.

Key Features

Multi-Granularity

Switch between 83, 89, and 476 classification systems to view data at different resolutions.

Interactive Visualization

High-resolution, interactive plots for signature profiles and sample decomposition analysis.

Comprehensive Data

Based on a robust dataset of somatic mutations processed with non-negative matrix factorization and Hierarchical Dirichlet Processes.

Methodology

Mutational signatures were extracted using the Hierarchical Dirichlet Process (HDP) framework via the R package mSigHdp (Liu et al., 2023, DOI: 10.1093/nargab/lqad005 ) and SigProfilerExtractor (Islam et al., 2022, DOI: 10.1016/j.xgen.2022.100179 ). The classification schemes were developed to capture specific biological phenomena, such as repeat-mediated mutagenesis and microhomology-mediated deletions.

Contact Us

We welcome feedback, questions, and collaboration opportunities. Please direct your inquiries to:

  • Xueming Wu: wuxm8523@gmail.com
  • Mo Liu : lmliumo@foxmail.com
  • Steve.G.Rozen: steverozen@pm.me
View Project on GitHub

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