Predicting age from the transcriptome of human dermal fibroblasts.
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ABSTRACT:
SUBMITTER: Fleischer JG
PROVIDER: S-EPMC6300908 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
Publications
Predicting age from the transcriptome of human dermal fibroblasts.
Fleischer Jason G JG Schulte Roberta R Tsai Hsiao H HH Tyagi Swati S Ibarra Arkaitz A Shokhirev Maxim N MN Huang Ling L Hetzer Martin W MW Navlakha Saket S
Genome biology 20181220 1
Biomarkers of aging can be used to assess the health of individuals and to study aging and age-related diseases. We generate a large dataset of genome-wide RNA-seq profiles of human dermal fibroblasts from 133 people aged 1 to 94 years old to test whether signatures of aging are encoded within the transcriptome. We develop an ensemble machine learning method that predicts age to a median error of 4 years, outperforming previous methods used to predict age. The ensemble was further validated by t ...[more]
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