RT Journal Article
SR Electronic
T1 Application of t-SNE to Human Genetic Data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 114884
DO 10.1101/114884
A1 Wentian Li
A1 Jane E Cerise
A1 Yaning Yang
A1 Henry Han
YR 2017
UL http://biorxiv.org/content/early/2017/03/08/114884.abstract
AB The t-SNE (t-distributed stochastic neighbor embedding) is a new dimension reduction and visualization technique for high-dimensional data. t-SNE is rarely applied to human genetic data, even though it is commonly used in other data-intensive biological fields, such as single-cell genomics. We explore the applicability of t-SNE to human genetic data and make these observations: (i) similar to previously used dimension reduction techniques such as principal component analysis (PCA), t-SNE is able to separate samples from different continents; (ii) unlike PCA, t-SNE is more robust with respect to the presence of outliers; (iii) t-SNE is able to display both continental and sub-continental patterns in a single plot. We conclude that the ability for t-SNE to reveal population stratification at different scales could be useful for human genetic association studies.