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ChimeraLM: Structural Variant Detection in WGA Long-Read Sequencing
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ChimeraLM: Structural Variant Detection in WGA Long-Read Sequencing

·53 words·1 min· ·
Bioinformatics Machine Learning Deep Learning Language Model Whole-Genome Amplification Structural Variants
Yangyang Li
Author
Yangyang Li
PhD Candidate at Northwestern University

ChimeraLM is a language model for accurate structural variant detection in whole-genome amplified (WGA) long-read sequencing data. It is described in the paper A Language Model Enables Accurate Structural Variant Detection in Whole-Genome Amplified Long-Read Sequencing.

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ylab-hi/ChimeraLM

A language model enables accurate structural variant detection in whole-genome amplified long-read sequencing

Python
3
0

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