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2.4. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis

NX Ning Xie
YB Yunfan Bai
LQ Lu Qiao
YB Yuru Bai
JW Jian Wu
YL Yan Li
MJ Mingzuo Jiang
BX Bing Xu
ZN Zhen Ni
TY Ting Yuan
YS Yongquan Shi
KW Kaichun Wu
FX Feng Xu
JW Jinhai Wang
LD Lei Dong
NL Na Liu
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GSE15459 cohort (tumour, n = 200) in the Gene Expression Omnibus (GEO) was utilized to perform the prognostic analyses of ARLs in GC patients (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE34942). LASSO Cox regression analysis was conducted using the 'glmnet R package. Tuning parameter (λ) selection in the LASSO model used 10‐fold cross‐validation via minimum criteria. A λ value of 0.0379 was chosen (λ.min) according to 10‐fold cross‐validation.

Copyright and License information:  ©2021 The Authors. published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.
This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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