Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions

Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions

Abstract Background Accurate prediction of copy number variations (CNVs) from targeted capture next-generation sequencing (NGS) data relies on effective normalization of read coverage profiles. The normalization process is particularly challenging due to hidden systemic biases such as GC bias, which...

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Bibliographic Details
Main Authors: Zoltán Maróti, Peter Juma Ochieng, József Dombi, Miklós Krész, Tibor Kalmár
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Bioinformatics
Subjects:
Targeted capture
Oligo capture baits
Copy number variation
Machine learning
Online Access:https://doi.org/10.1186/s12859-024-06006-y
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https://doi.org/10.1186/s12859-024-06006-y

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