Chromothripsis detection with multiple myeloma patients based on deep graph learning.

ABSTRACT:

Motivation

Chromothripsis, associated with poor clinical outcomes, is prognostically vital in multiple myeloma. The catastrophic event is reported to be detectable prior to the progression of multiple myeloma. As a result, chromothripsis detection can contribute to risk estimation and early treatment guidelines for multiple myeloma patients. However, manual diagnosis remains the gold standard approach to detect chromothripsis events with the whole-genome sequencing technology to retrieve both copy number variation (CNV) and structural variation data. Meanwhile, CNV data are much easier to obtain than structural variation data. Hence, in order to reduce the reliance on human experts' efforts and structural variation data extraction, it is necessary to establish a reliable and accura

SUBMITTER: Yu J 

PROVIDER: S-EPMC10343948 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature