Difference between revisions of "Rare variant tests"
Line 168: | Line 168: | ||
| Sequence dissimilarity* || Schork et al. 2008, Wessel et al. 2006 || || | | Sequence dissimilarity* || Schork et al. 2008, Wessel et al. 2006 || || | ||
|- | |- | ||
− | | Ridge regression * || Malo et al. 2008 || || | + | | Ridge regression * || [http://www.cell.com/AJHG/abstract/S0002-9297(08)00091-8 Malo et al. 2008] || || |
|} | |} |
Revision as of 11:07, 7 March 2012
Summary of discussion from ESP rare variant working group
The rare variant working group within ESP has discussed the issue of rare variant tests on several conference calls. The end result is that we recommend selecting one test from each of these three categories;
1. Aggregate tests (typically with 1% threshold, nonsynonymous SNPs only, with meta-analysis across different ethnic groups)
2. Tests that allow for risk and/or protective variants (again, probably 1% threshold, nonsynonymous SNPs only, with meta-analysis across different ethnic groups)
3. Weighted tests that allow incorporation of more common variants (possibly apply 5% threshold?, nonsynonymous only, etc.)
A brief summary of the RV discussion;
- Permutations (where we permute phenotype while maintaining ethnic group) will likely be required to get empirical p-values. These RV tests typically provide conservative p-values (deflated QQ plot), but not always. Thus, a computationally intensive test will not be practical for performing large numbers of permutations (at least 1000).
- Using too many tests will decrease the power overall because of correction for family-wise error.
- Although we'd like to evaluate power and type I error rates of these tests under a variety of genetic models, the reality is that we have so few known positive examples it would be difficult to assess them all in a fair way at this time. Instead, we expect to re-convene this discussion group at a later date once some true positive associations are identified.
- Shamil Sunyaev is performing a bake-off with some of these tests, and we look forward to seeing his results in the future.
- PLINKSeq is on its way, but is likely a month away from release (end Feb 2011)
Summary of rare variant tests for sequence data
Compiled by Cristen Willer and Suzanne Leal for the ESP Feb 1, 2011
* indicates applicability to quantitative data
1) Aggregate tests using a cut off e.g. 1 % analyzing nonsynonymous variants to detect detrimental variants
Test Name | Reference | Software | Notes |
---|---|---|---|
CMC/T1 test* | Li & Leal, 2008 | Will be implemented in PlinkSeq | |
KBAC | Liu & Leal, 2010 | Will be implemented in PlinkSeq | |
VT* | Price et al., 2010 | http://genetics.bwh.harvard.edu/rare_variants/ | |
WSS | Madsen & Browning, 2009 | with 1% cutoff, Will be implemented in PlinkSeq | |
CMAT | Zawistowski et al. 2010 | ||
ANRV/GRANVIL* | Morris & Zeggini | ||
RARECOVER | Bhati et al. 2010 | ||
CCRaVAT and QuTie* | Lawrence et al. 2010 | http://www.sanger.ac.uk/resources/software/rarevariant/ | |
RVE (rare variant exclusive) | Cohen & Hobbs | underpowered, Will be implemented in PlinkSeq |
2) Aggregate tests for protective and detrimental variants (recommend 1% cutoff)
Test Name | Reference | Software | Notes |
---|---|---|---|
C-alpha | [Neale et al., submitted] | Will be implemented in PlinkSeq | |
Ionita-Laza & Lange | Ionita-Laza & Lange, 2011 | ||
DASH* | Han & Pan | Computational burden | |
SKAT* | Wu et al., 2010 | http://www.hsph.harvard.edu/~xlin/software.html | For some kernel choices, need to code 0=major homozygote, 1=het, 2-minor homozygote |
WHaIT | Li et al. 2010 | http://www.sph.umich.edu/csg/yli/whait/ | |
EMMPAT* | King et al. 2010 | http://home.uchicago.edu/~crk8e/papersup.html |
3) Analyzing common and rare variants together (could down-weight or threshold common variants)
Test Name | Reference | Software | Notes |
---|---|---|---|
WSS | Madsen & Browning, 2009 | with 1% or 5% cutoff, Will be implemented in PlinkSeq | |
RARECOVER | Bhati et al. 2010 | ||
Step-Up Collapsing* | Hoffman et al. 2010 | Will be implemented in PlinkSeq | |
CMC/T5 test* | Li & Leal, 2008 | Will be implemented in PlinkSeq | |
MENDEL* | Zhou et al. 2011 | http://www.genetics.ucla.edu/software/download?package=1 |
4.) Analyze higher frequency rare variants >1% individually
Use same regression frame work which has been used for common variants* Use meta analysis to combine results from sequence data and imputed genotypes to increase power*
Additional tests
Test Name | Reference | Software | Notes |
---|---|---|---|
Logic regression* | Kooperberg et al. 2001 | ||
Sequence diversity | Anderson et al. 2006 | ||
Sequence dissimilarity* | Schork et al. 2008, Wessel et al. 2006 | ||
Ridge regression * | Malo et al. 2008 |