LDPAC is a method for detecting spurious associations using p-values.
The strength of the method is its simplicity; it requires no other information
We provide both the Web server
where user can upload p-values,
and the Software binary.
Our method uses internally stored HapMap Phase III data to retrieve LD information.
- Quick check: just drop 100 p-values around a suspicious association into our web server. You can instantly check if the association is spurious.
- Genome-wide check: since LDPAC is so fast, you can put whole genome p-values into one file and check spurious associations in hours of time.
- Resque: our method can detect possibly true associations from discarded associations by QC, if QC was too harsh.
HOW IT WORKS
The intuition is that if the association is caused
by a true genetic effect, neighboring markers in LD should show
comparably significant p-values (Figure A). If not, it may be evidence of
spurious association (Figure B). Previous studies have applied the same
idea but only manually without a formal statistical framework.
Our method LDPAC provides a systematic framework
to quantitatively measure the evidence of spurious associations.
We take WTCCC CAD chr 9 data
where a confirmed association exists.
We put 5 spurious associations back into the data
which were originally excluded by QC in WTCCC study.
Figure shows that our method effectively detects 3
out of 5 spurious associations (red dots)
using only p-values.
The true association is correctly predicted as true (blue dots).
B.H. and E.E. are supported by National Science Foundation grants 0513612, 0731455, 0729049 and 0916676, and NIH grants K25-HL080079 and U01-DA024417. B.H. is supported by the Samsung Scholar- ship. This research was supported in part by the University of California, Los Angeles subcontract of contract N01-ES-45530 from the National Toxicology Program and National Institute of Environmental Health Sciences to Perlegen Sciences.