한빛사논문
- 조회689
Jaehyun Park 1, Sharon M Lutz 2, Seungil Choi 3, Sanghun Lee 4, Sang-Cheol Park 5, Kangjin Kim 6, Hosik Choi 7, Hansoo Park 8,9, So Yeon Lee 10, Scott T Weiss 11, Soo-Jong Hong 10, Bong-Soo Kim 12,*, Sungho Won 1,5,6,13,*
1Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, Seoul, Korea.
2Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
3Department of Statistics, College of Natural Sciences, Seoul National University, Seoul, Korea.
4Department of Medical Consilience, Graduate School, Dankook University, Yongin-Si, Korea.
5Seoul National University Institute of Health and Environment, Seoul, Korea.
6Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, Korea.
7Graduate School, Department of Urban Big Data Convergence, University of Seoul, Seoul, Korea.
8Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea.
9Genome & Company, Seoungnam-si, Korea.
10Department of Pediatrics, Childhood Asthma Atopy Center, Environmental Health Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
11Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
12Department of Life Science, Multidisciplinary Genome Institute, Hallym University, Chuncheon, Korea.
13RexSoft Corps, Seoul, Korea
Abstract
To the Editor,
In recent years, omics data for studies on atopic dermatitis (AD) have become more available. Most studies, however, have focused on a single type of omics data, owing to which, interplays between biological aspects may be missed or spurious correlations may be concluded. Here, using genetic and microbial profiles obtained from Cohort for Childhood Origin of Asthma and Allergic Diseases (COCOA) study,1 we built a prediction model of AD in 6-month-old infants using three omics datasets: microarray transcriptome data for host gene expression, and 16S rRNA microbiome and metagenome shotgun data for compositional and functional characteristics of the intestinal microbiota, respectively. Performance was evaluated using area under the curve (AUC) values corresponding to receiver operating characteristic (ROC) curves, and the relative importance of each omics data was investigated using McFadden's R-square.2
논문정보
- LETTER TO THE EDITOR
- 2021년 08월 (BRIC 등록일 2021-08-19)
- 국내(교신)+국외 연구진
- 의약학 > 유전 및 유전체의학
댓글 작성 로그인
팝업 닫기관련 링크
관련분야 연구자보기
소속기관 논문보기
관련분야 논문보기
해당논문 저자보기
