Sign in
BioinformaticsBioinformatics Advances
Peer-reviewed journal article

TraceTrack, an Open-Source Software for Batch Processing, Alignment and Visualization of Sanger Sequencing Chromatograms

Kveta BrazdilovaiD, David PříhodaiD, Quynh V. ToniD, Heath E. Klock, Danny A. BittoniD

Abstract

BackgroundDespite the advent of Next Generation Sequencing technology and its widespread applications, Sanger sequencing remains instrumental for molecular biology subcloning work in biological and medical research and indispensable for drug discovery campaigns. Although Sanger sequencing technology has been long established, existing software for processing and visualization of trace file chromatograms are limited in terms of functionality, scalability, and availability for commercial use. ResultsTo fill this gap, we developed TraceTrack, an open-source web application tool for batch alignment, analysis and visualization of Sanger trace files. TraceTrack offers high throughput matching of trace files to reference sequences, rapid identification of mutations and an intuitive chromatogram analysis. Comparative analysis between TraceTrack and existing software tools highlights the advantages of TraceTrack with regards to batch processing, visualization and export functionalities. TraceTrack is available at https://github.com/Merck/TraceTrack and also at https://tracetrack.dichlab.org as a web application. ConclusionTraceTrack is a web application for batch processing and visualization of Sanger trace file chromatograms that meets the increasing demand of industrial sequence validation workflows in pharmaceutical settings.

PDFDOICode

02 /Specification & Classification

Click any tag to browse matching papers
Citations
4
FWCI
0.36
Field percentile
48th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBrekke '26Chao '21Oki '14Jiang '26Hebert '18Wang '23
58% semantic matchBioinformatics
Thomas Brekke, Thomas Weeks, Robert Barber+8 more·Biodiversity Data Journal·Sep 30, 2026· 1 citations