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December 8, 2025Blood

Maximizing the potential of optical genome mapping through comprehensive automated data analysis in multiple myeloma

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Authors

DMDavid Martı́nezESEsperanza SuchJRJavier de la Rubia

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Overview

Automated analysis reveals copy number variations and aneuploidies in newly diagnosed multiple myeloma, suggesting bioinformatics can improve diagnostics.

Key Points

  • To evaluate the use of automated bioinformatics analysis of optical genome mapping in detecting cytogenetic abnormalities in multiple myeloma.
  • Analyzed samples from 62 patients with newly diagnosed multiple myeloma.
  • Developed an automated pipeline for detection of structural variants and copy number variations.
  • Compared automated results with manual reporting using statistical tests.
  • Detected aneuploidies in 95% of cases, with an average of 3 per patient.
  • Automated analysis and manual review showed about 89% concordance.
  • Bioinformatics methods discovered MYC translocations not reported previously.

Cite This Study

Martı́nez et al. (2025) studied this question.

synapsesocial.com/papers/69362f514fa91c937236d923https://doi.org/10.1182/blood-2025-7449
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