Staff View: WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores

WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores

Genetic and genomic variations are primary drivers of tumor development. Identifying driver genes from numerous passenger genes across pan-cancer poses a significant challenge due to varying mutation loads. While independent studies have elucidated cancer-associated mutation patterns within speci...

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Main Authors:	Yanjie, Ren, Azlan, Mohd Zain, Yan, Zhang, Rozita, Abdul Jalil, Mahadi, Bahari, Norfadzlan, Bin Yusup, Mazlina, Abdul Majid, Azurah, A. Samah, Didik Dwi, Prasetya, Nurhafizah Moziyana, Mohd Yusop
Format:	Article
Language:	English
Published:	IEEE 2024
Subjects:	QA Mathematics QA75 Electronic computers. Computer science
Online Access:	http://ir.unimas.my/id/eprint/47093/1/WeiFu_A_Novel_Pan-Cancer_Driver_Gene_Identification_Method_Using_Incidence-Weighted_Mutation_Scores.pdf http://ir.unimas.my/id/eprint/47093/ https://ieeexplore.ieee.org/document/10807179?denied=
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id	my.unimas.ir-47093
record_format	eprints
spelling	my.unimas.ir-470932024-12-30T08:42:50Z http://ir.unimas.my/id/eprint/47093/ WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores Yanjie, Ren Azlan, Mohd Zain Yan, Zhang Rozita, Abdul Jalil Mahadi, Bahari Norfadzlan, Bin Yusup Mazlina, Abdul Majid Azurah, A. Samah Didik Dwi, Prasetya Nurhafizah Moziyana, Mohd Yusop QA Mathematics QA75 Electronic computers. Computer science Genetic and genomic variations are primary drivers of tumor development. Identifying driver genes from numerous passenger genes across pan-cancer poses a significant challenge due to varying mutation loads. While independent studies have elucidated cancer-associated mutation patterns within specific cancer types, a systematic approach to integrating these mutation data for assessing the impact of gene mutations has been lacking. This study addresses this gap by integrating pan-cancer genomic somatic mutation data and introducing a novel mutation weight fusion (WeiFu) score calculation method. WeiFu computes frequency and weighted fusion scores by cancer type, facilitating the identification of potential driver genes. Evaluation results on an integrated pan-cancer dataset comprising 29 different cancer types demonstrate that WeiFu significantly outperforms current well-known approaches in prediction accuracy, sensitivity, and specificity. Notably, WeiFu recovers 277 known cancer genes among the top 500 ranked candidates and successfully identifies potential driver genes supported by strong evidence. Consequently, WeiFu shows considerable promise for identifying driver genes within the rapidly expanding corpus of cancer genomic data. IEEE 2024-12-19 Article PeerReviewed text en http://ir.unimas.my/id/eprint/47093/1/WeiFu_A_Novel_Pan-Cancer_Driver_Gene_Identification_Method_Using_Incidence-Weighted_Mutation_Scores.pdf Yanjie, Ren and Azlan, Mohd Zain and Yan, Zhang and Rozita, Abdul Jalil and Mahadi, Bahari and Norfadzlan, Bin Yusup and Mazlina, Abdul Majid and Azurah, A. Samah and Didik Dwi, Prasetya and Nurhafizah Moziyana, Mohd Yusop (2024) WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores. IEEE Access, 12. pp. 194762-194773. ISSN 2169-3536 https://ieeexplore.ieee.org/document/10807179?denied= 10.1109/ACCESS.2024.3520550
institution	Universiti Malaysia Sarawak
building	Centre for Academic Information Services (CAIS)
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Sarawak
content_source	UNIMAS Institutional Repository
url_provider	http://ir.unimas.my/
language	English
topic	QA Mathematics QA75 Electronic computers. Computer science
spellingShingle	QA Mathematics QA75 Electronic computers. Computer science Yanjie, Ren Azlan, Mohd Zain Yan, Zhang Rozita, Abdul Jalil Mahadi, Bahari Norfadzlan, Bin Yusup Mazlina, Abdul Majid Azurah, A. Samah Didik Dwi, Prasetya Nurhafizah Moziyana, Mohd Yusop WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores
description	Genetic and genomic variations are primary drivers of tumor development. Identifying driver genes from numerous passenger genes across pan-cancer poses a significant challenge due to varying mutation loads. While independent studies have elucidated cancer-associated mutation patterns within specific cancer types, a systematic approach to integrating these mutation data for assessing the impact of gene mutations has been lacking. This study addresses this gap by integrating pan-cancer genomic somatic mutation data and introducing a novel mutation weight fusion (WeiFu) score calculation method. WeiFu computes frequency and weighted fusion scores by cancer type, facilitating the identification of potential driver genes. Evaluation results on an integrated pan-cancer dataset comprising 29 different cancer types demonstrate that WeiFu significantly outperforms current well-known approaches in prediction accuracy, sensitivity, and specificity. Notably, WeiFu recovers 277 known cancer genes among the top 500 ranked candidates and successfully identifies potential driver genes supported by strong evidence. Consequently, WeiFu shows considerable promise for identifying driver genes within the rapidly expanding corpus of cancer genomic data.
format	Article
author	Yanjie, Ren Azlan, Mohd Zain Yan, Zhang Rozita, Abdul Jalil Mahadi, Bahari Norfadzlan, Bin Yusup Mazlina, Abdul Majid Azurah, A. Samah Didik Dwi, Prasetya Nurhafizah Moziyana, Mohd Yusop
author_facet	Yanjie, Ren Azlan, Mohd Zain Yan, Zhang Rozita, Abdul Jalil Mahadi, Bahari Norfadzlan, Bin Yusup Mazlina, Abdul Majid Azurah, A. Samah Didik Dwi, Prasetya Nurhafizah Moziyana, Mohd Yusop
author_sort	Yanjie, Ren
title	WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores
title_short	WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores
title_full	WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores
title_fullStr	WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores
title_full_unstemmed	WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores
title_sort	weifu: a novel pan-cancer driver gene identification method using incidence-weighted mutation scores
publisher	IEEE
publishDate	2024
url	http://ir.unimas.my/id/eprint/47093/1/WeiFu_A_Novel_Pan-Cancer_Driver_Gene_Identification_Method_Using_Incidence-Weighted_Mutation_Scores.pdf http://ir.unimas.my/id/eprint/47093/ https://ieeexplore.ieee.org/document/10807179?denied=
_version_	1819914987237277696
score	13.226497

WeiFu: A Novel Pan-Cancer Driver Gene Identification Method Using Incidence-Weighted Mutation Scores

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