Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis

Identifying mutation-derived neoantigens by proteogenomics requires robust strategies for quality control. Here, the authors propose peptide retention time as an evaluation metric for proteogenomics quality control methods, and develop a deep learning algorithm for accurate retention time prediction...

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Main Authors:	Bo Wen, Kai Li, Yun Zhang, Bing Zhang
Format:	Article
Language:	English
Published:	Nature Publishing Group 2020-04-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-020-15456-w

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spelling	doaj-e193f272716f4fd7ac8dbd5e93d0c9092021-05-11T09:03:52ZengNature Publishing GroupNature Communications2041-17232020-04-0111111410.1038/s41467-020-15456-wCancer neoantigen prioritization through sensitive and reliable proteogenomics analysisBo Wen0Kai Li1Yun Zhang2Bing Zhang3Lester and Sue Smith Breast Center, Baylor College of MedicineLester and Sue Smith Breast Center, Baylor College of MedicineLester and Sue Smith Breast Center, Baylor College of MedicineLester and Sue Smith Breast Center, Baylor College of MedicineIdentifying mutation-derived neoantigens by proteogenomics requires robust strategies for quality control. Here, the authors propose peptide retention time as an evaluation metric for proteogenomics quality control methods, and develop a deep learning algorithm for accurate retention time prediction.https://doi.org/10.1038/s41467-020-15456-w
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Bo Wen Kai Li Yun Zhang Bing Zhang
spellingShingle	Bo Wen Kai Li Yun Zhang Bing Zhang Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis Nature Communications
author_facet	Bo Wen Kai Li Yun Zhang Bing Zhang
author_sort	Bo Wen
title	Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
title_short	Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
title_full	Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
title_fullStr	Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
title_full_unstemmed	Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
title_sort	cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2020-04-01
description	Identifying mutation-derived neoantigens by proteogenomics requires robust strategies for quality control. Here, the authors propose peptide retention time as an evaluation metric for proteogenomics quality control methods, and develop a deep learning algorithm for accurate retention time prediction.
url	https://doi.org/10.1038/s41467-020-15456-w
work_keys_str_mv	AT bowen cancerneoantigenprioritizationthroughsensitiveandreliableproteogenomicsanalysis AT kaili cancerneoantigenprioritizationthroughsensitiveandreliableproteogenomicsanalysis AT yunzhang cancerneoantigenprioritizationthroughsensitiveandreliableproteogenomicsanalysis AT bingzhang cancerneoantigenprioritizationthroughsensitiveandreliableproteogenomicsanalysis
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Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis

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