Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,616 bioRxiv papers from 308,268 authors.

Unsupervized Quantification of Demographic Structure for Single-copy Alignments

By AB Rohrlach, Nigel Bean, Gary Glonek, Barbara Holland, Ray Tobler, Jonathan Tuke, Alan Cooper

Posted 04 Jun 2018
bioRxiv DOI: 10.1101/338442

Principal components analysis (PCA) has been one of the most widely used exploration tools in genomic data analysis since its introduction in 1978 (Menozzi et al. 1978). PCA allows similarities between individuals to be efficiently calculated and visualized, optimally in two dimensions. While PCA is well suited to analyses concerned with autosomal DNA, no analogue for PCA exists for the analysis and visualization of non-autosomal DNA. In this paper we introduce a statistically valid method for the analysis of single-copy sequence data. We then show that tests for relationships between genetic information and qualitative and quantitative characteristics can be implemented in a rigorous statistical framework. We motivate the use of our method with examples from empirical data.

Download data

  • Downloaded 279 times
  • Download rankings, all-time:
    • Site-wide: 41,290 out of 70,610
    • In bioinformatics: 4,867 out of 6,912
  • Year to date:
    • Site-wide: 46,571 out of 70,610
  • Since beginning of last month:
    • Site-wide: 55,346 out of 70,610

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News