TraceTrack, an open-source software for batch processing, alignment and visualization of sanger sequencing chromatograms
- PMID: 37456510
- PMCID: PMC10348866
- DOI: 10.1093/bioadv/vbad083
TraceTrack, an open-source software for batch processing, alignment and visualization of sanger sequencing chromatograms
Abstract
Motivation: Despite 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 is limited in terms of functionality, scalability and availability for commercial use.
Results: To 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.
Availability and implementation: TraceTrack is available at https://github.com/MSDLLCpapers/TraceTrack and as a web application at https://tracetrack.dichlab.org. TraceTrack 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.
Supplementary information: Supplementary data are available at Bioinformatics Advances online.
© The Author(s) 2023. Published by Oxford University Press.
Conflict of interest statement
All authors are/were employees of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA and may hold stocks and/or stock options in Merck & Co., Inc., Rahway, NJ, USA.
Figures
References
-
- Fu J. et al. (2018) Evaluation genotypes of cancer cell lines HCC1954 and SiHa by short tandem repeat (STR) analysis and DNA sequencing. Mol. Biol. Rep., 45, 2689–2695. - PubMed
LinkOut - more resources
Full Text Sources
Miscellaneous
