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Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

ProSeq4: A user-friendly multiplatform program for preparation and analysis of large-scale DNA polymorphism datasets.

Dmitry A Filatov¹

¹Department of Biology, University of Oxford, Oxford, UK.

Molecular Ecology Resources

|April 22, 2024

Summary

This summary is machine-generated.

A new software, proSeq4, simplifies processing large DNA polymorphism datasets for evolutionary genetics. This tool aids researchers in analyzing genomic and transcriptomic data efficiently.

Keywords:

DNA polymorphism coalescent simulations data visualisation file conversion population genetics sequence alignment editing software

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Area of Science:

Evolutionary genetics
Molecular ecology
Bioinformatics

Background:

Preparing DNA polymorphism datasets is crucial but time-consuming for large-scale evolutionary genetic studies.
Existing software options are limited for processing thousands of sequence alignments efficiently.

Purpose of the Study:

To introduce "processor of sequences v4" (proSeq4), a multiplatform software designed for user-friendly preparation and analysis of large-scale sequence polymorphism datasets.
To provide a comprehensive tool for evolutionary genetic and molecular ecology research, including data visualization and common analyses.

Main Methods:

Development of a multiplatform software with a graphic user interface (GUI) and command-line tools.
Implementation of support for over two dozen file formats, a sequence editor, data visualization, quality control, and core evolutionary genetic analyses.
Inclusion of Neighbor-Joining (NJ) phylogeny reconstruction, DNA polymorphism analyses, and coalescent simulations.

Main Results:

proSeq4 offers a user-friendly interface for processing and analyzing thousands of genome- or transcriptome-scale datasets.
The software supports extensive file formats and includes essential tools for data preparation, quality control, and evolutionary genetic analyses.
Command-line tools facilitate integration into existing bioinformatic pipelines, enhancing workflow efficiency.

Conclusions:

proSeq4 significantly streamlines the analysis of large DNA polymorphism datasets, benefiting evolutionary genetics and molecular ecology research.
The software's versatility and ease of use make it valuable for both research and educational purposes, aiding in the illustration of evolutionary processes.