JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Add like
Add dislike
Add to saved papers

Joint principal trend analysis for longitudinal high-dimensional data.

Biometrics 2018 June
We consider a research scenario motivated by integrating multiple sources of information for better knowledge discovery in diverse dynamic biological processes. Given two longitudinal high-dimensional datasets for a group of subjects, we want to extract shared latent trends and identify relevant features. To solve this problem, we present a new statistical method named as joint principal trend analysis (JPTA). We demonstrate the utility of JPTA through simulations and applications to gene expression data of the mammalian cell cycle and longitudinal transcriptional profiling data in response to influenza viral infections.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app