Add like
Add dislike
Add to saved papers

Diversity Analysis in Viral Metagenomes.

Viruses are the most abundant and diverse biological entity in the earth. Nowadays, there are several viral metagenomes from different ecological niches which have been used to characterize new viral particles and to determine their diversity. However, viral metagenomic data have the disadvantage to be high-dimensional compositional and sparse. This type of data renders many of the conventional multivariate statistical analyses inoperative. Fortunately, different libraries and statistical packages have been developed to deal with this problem and perform the different ecological and statistical analyses. In the present chapter, it is analyzed simulated viral metagenomes, based on real human gut-associated viral metagenomes, using different R and python packages. The example presented here includes the estimation and comparison of different indexes of diversity, evenness, and richness; perform different ordination and statistical analysis using different dissimilarity metrics; determine the optimal cluster configuration and perform biomarker discovery. The scripts and the simulated datasets are in https://github.com/jorgevazcast/Viromic-diversity.

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