Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 73,834 bioRxiv papers from 321,396 authors.

KS-Burden: Assessing distributional differences of rare variants in dichotomous traits

By Robert Milan Porsch, Timothy Mak, Clara Tang, Pak C Sham

Posted 13 Jul 2018
bioRxiv DOI: 10.1101/368696

A number of rare variant tests have been developed to explore the effect of low frequency genetic variations on complex phenotypes. However, an often neglected aspect in these tests is the position of genetic variations. Here we are proposing a way to assess the differences in spatial organization of rare variants by assessing their distributional differences between affected and unaffected subjects. To do so, we have formulated an adaptation of the well know Kolmogorov-Smirnov (KS) test, combining both KS and a simple gene burden approach, called KS-Burden. The performance of our test was evaluated under a comprehensive simulations framework using real data and various scenarios. Our results show that the KS-Burden test is able to outperform the commonly used SKAT-O test, as well as others, in the presents of clusters of causal variants within a genomic region. Furthermore, our test is able to maintain competitive statistical power in scenarios unfavorable to its original assumptions. Hence, the KS-Burden test is a valuable alternative to existing tests and provides better statistical power in the presents of causal clusters within a gene.

Download data

  • Downloaded 240 times
  • Download rankings, all-time:
    • Site-wide: 49,259 out of 73,834
    • In bioinformatics: 5,515 out of 7,182
  • Year to date:
    • Site-wide: 71,959 out of 73,834
  • Since beginning of last month:
    • Site-wide: 71,959 out of 73,834

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


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