| Issue |
BIO Web Conf.
Volume 59, 2023
2023 5th International Conference on Biotechnology and Biomedicine (ICBB 2023)
|
|
|---|---|---|
| Article Number | 03011 | |
| Number of page(s) | 4 | |
| Section | Clinical Trials and Medical Device Monitoring | |
| DOI | https://doi.org/10.1051/bioconf/20235903011 | |
| Published online | 08 May 2023 | |
Statistical detecting of genes associated with PIK3C2B on lung disease
School of Mathematical Sciences, Heilongjiang University, Harbin 150080, China
*a Corresponding authors’ e-mails: 2022012@hlju.edu.cn
b yzhou@aliyun.com
Statistical gene detection plays an important role in biostatistics and bioinformatics. So far, many gene loci associated with human complex disease have been found by statistical methods. However, it is difficult to find all the mutation genes that are associated with a certain disease. Researchers need to detect more associated genes aiming at a disease so that human will conquer the disease one day. In this paper, we considered a real and big data set and study the detection problem of genes associated with the PIK3C2B gene on lung disease. 168 significant genes associated with the PIK3C2B gene were detected at nominal significance level 0.001 by using statistical multiple testing method. The detected genes will provide some reference to further study the function of the PIK3C2B gene to lung disease for biologists and medical scientists.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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