Novel Ensemble Feature Selection Approach and Application in Repertoire Sequencing Data.
Novel Ensemble Feature Selection Approach and Application in Repertoire Sequencing Data.
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DOI:
10.3389/fgene.2022.821832
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发表时间:
2022
影响因子:
3.7
通讯作者:
中科院分区:
文献类型:
--
作者:
The T and B cell repertoire make up the adaptive immune system and is mainly generated through somatic V(D)J gene recombination. Thus, the VJ gene usage may be a potential prognostic or predictive biomarker. However, analysis of the adaptive immune system is challenging due to the heterogeneity of the clonotypes that make up the repertoire. To address the heterogeneity of the T and B cell repertoire, we proposed a novel ensemble feature selection approach and customized statistical learning algorithm focusing on the VJ gene usage. We applied the proposed approach to T cell receptor sequences from recovered COVID-19 patients and healthy donors, as well as a group of lung cancer patients who received immunotherapy. Our approach identified distinct VJ genes used in the COVID-19 recovered patients comparing to the healthy donors and the VJ genes associated with the clinical response in the lung cancer patients. Simulation studies show that the ensemble feature selection approach outperformed other state-of-the-art feature selection methods based on both efficiency and accuracy. It consistently yielded higher stability and sensitivity with lower false discovery rates. When integrated with different classification methods, the ensemble feature selection approach had the best prediction accuracy. In conclusion, the proposed novel approach and the integration procedure is an effective feature selection technique to aid in correctly classifying different subtypes to better understand the signatures in the adaptive immune response associated with disease or the treatment in order to improve treatment strategies.
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影响因子:
8.9
作者:
Huang, J;Ling, CX
通讯作者:
Ling, CX
影响因子:
4.4
作者:
Wang P;Jin X;Zhou W;Luo M;Xu Z;Xu C;Li Y;Ma K;Cao H;Huang Y;Xue G;Jin S;Nie H;Jiang Q
通讯作者:
Jiang Q
影响因子:
8
作者:
Hua, Jianping;Tembe, Waibhav D.;Dougherty, Edward R.
通讯作者:
Dougherty, Edward R.
影响因子:
2.7
作者:
KENT, JT
通讯作者:
KENT, JT
影响因子:
5.8
作者:
Kursa, Miron B.;Rudnicki, Witold R.
通讯作者:
Rudnicki, Witold R.