TRACE: Open-Source Software for Quantifying Somatic Variation of Tandem Repeats by Capillary Electrophoresis
Jiang, A.; Correia, K.; Gillis, T.; Oliver, E. L.; Jones, B. P.; McAllister, B.; Mejia Maza, A.; MacDonald, M. E.; Mouro Pinto, R.; Wheeler, V.; Gusella, J.; McLean, Z. L.
Show abstract
Expanded short tandem DNA repeats are implicated in over 60 human disorders. In many, somatic instability (SI) of the repeat plays a critical role in disease pathogenesis. For example, SI in vulnerable neurons is a key driver of clinical symptoms in Huntingtons disease. Quantifying SI has traditionally relied on PCR followed by capillary electrophoresis, with metrics describing the shape of repeat size distributions, such as the expansion index. However, current tools often require costly proprietary software, are time-consuming, and rely on custom pipelines that vary between labs. To address these challenges, we developed Tandem Repeats Analysis by Capillary Electrophoresis (TRACE), an open-source software that processes fragment analysis data end-to-end, from raw files to SI metrics. Additionally, we created an associated web app TRACE-shiny (https://traceshiny.mgh.harvard.edu/), for interactive usage. Outputs from TRACE benchmarked against published datasets confirm its utility for studying genetic and pharmacological modifiers of SI. TRACE eliminates the need for proprietary software or custom pipelines, making advanced tools for analysis of somatic repeat expansion widely accessible.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Low-pass sequencing plus imputation using avidity sequencing displays comparable imputation accuracy to sequencing by synthesis while reducing duplicates 92%
- GenoTools: An Open-Source Python Package for Efficient Genotype Data Quality Control and Analysis 92%
- Concerning the eXclusion in human genomics: The choice of sex chromosome representation in the human genome drastically affects number of identified variants 91%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.