Protocol to identify functional doppelgängers and verify biomedical gene expression data using doppelgangerIdentifier

Protocol to identify functional doppelgängers and verify biomedical gene expression data using doppelgangerIdentifier

Functional doppelgängers (FDs) are independently derived sample pairs that confound machine learning model (ML) performance when assorted across training and validation sets. Here, we detail the use of doppelgangerIdentifier (DI), providing software installation, data preparation, doppelgänger ident...

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Bibliographic Details
Main Authors: Wang, Li Rong, Fan, Xiuyi, Goh, Wilson Wen Bin
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering
Science::Biological sciences
Gene Expression
Machine Learning
Online Access:https://hdl.handle.net/10356/164598
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Institution: Nanyang Technological University
Language: English
Description
Summary:Functional doppelgängers (FDs) are independently derived sample pairs that confound machine learning model (ML) performance when assorted across training and validation sets. Here, we detail the use of doppelgangerIdentifier (DI), providing software installation, data preparation, doppelgänger identification, and functional testing steps. We demonstrate examples with biomedical gene expression data. We also provide guidelines for the selection of user-defined function arguments. For complete details on the use and execution of this protocol, please refer to Wang et al. (2022).

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