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Author Spotlight: Modeling Brain Tumors In Vivo Using Electroporation-Based Delivery of Plasmid DNA Representing Patient Mutation Signatures

Author Spotlight: Modeling Brain Tumors In Vivo Using Electroporation-Based Delivery of Plasmid DNA Representing Patient Mutation Signatures

Published on: June 23, 2023

SigsPack, a package for cancer mutational signatures

Franziska Schumann^1,2, Eric Blanc^1,3, Clemens Messerschmidt^1,3

¹Core Unit Bioinformatics, Berlin Institute of Health, Charitéplatz 1, Berlin, 10117, Germany.

BMC Bioinformatics

|September 4, 2019

Summary

SigsPack is a new Bioconductor package that estimates a cancer sample's exposure to mutational processes and signature stability. It also normalizes mutation frequencies, aiding cancer etiology research.

Area of Science:

Genomics
Cancer Research
Bioinformatics

Background:

Mutational signatures represent patterns of somatic mutations from oncogenic processes.
Several mutational signatures are identified and linked to known oncogenic processes.
Identifying mutation-contributing processes aids understanding cancer etiology.

Purpose of the Study:

To introduce SigsPack, a Bioconductor package for estimating sample exposure to mutational processes.
To provide tools for assessing the stability of these mutational exposures.
To offer methods for normalizing mutation frequencies based on trinucleotide content.

Main Methods:

Utilizes a Bioconductor package (SigsPack) for exposure estimation.
Employs bootstrapping for estimating the stability of mutational exposures.
Includes functions for normalizing mutation frequencies by trinucleotide content.

Main Results:

SigsPack enables estimation of individual sample exposure to mutational signatures.
The package validates exposure and stability estimations using synthetic and real data.
Tools are provided for normalizing mutation frequencies relative to trinucleotide content.

Conclusions:

SigsPack offers a comprehensive toolkit for individual sample exposure estimation.
The package facilitates mutation catalogue and mutational signature normalization.
Provides essential tools for analyzing mutational processes in cancer samples.

Keywords:

Bioconductor Cancer Mutational signatures

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