- Gene function prediction from synthetic lethality networks via ranking on demand
Machine Learning and Computational Biology Research Group, Max Planck Institutes, Tubingen, Germany
Bioinformatics 26:912-8. 2010
..However, there is a lack of algorithms for predicting gene function from synthetic lethality interaction networks...
- FaST linear mixed models for genome-wide association studies
Microsoft Research, Los Angeles, California, USA
Nat Methods 8:833-5. 2011
..Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/)...
- A powerful and efficient set test for genetic markers that handles confounders
eScience Group, Microsoft Research, Los Angeles, CA 90024, USA
Bioinformatics 29:1526-33. 2013
..Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power...
- The benefits of selecting phenotype-specific variants for applications of mixed models in genomics
eScience Group, Microsoft Research, Los Angeles, CA 90024, United States
Sci Rep 3:1815. 2013
..For each application of the LMM, we review known effects and describe new effects showing how variable selection can be used to mitigate them...
- Further improvements to linear mixed models for genome-wide association studies
eScience Group, Microsoft Research, 1100 Glendon Avenue, Suite PH1, Los Angeles, CA, 90024, United States
Sci Rep 4:6874. 2014
..Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science. ..
- Greater power and computational efficiency for kernel-based association testing of sets of genetic variants
eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA
Bioinformatics 30:3206-14. 2014
..Thus we develop new computationally efficient methods...
- Epigenome-wide association studies without the need for cell-type composition
1 eScience Research Group, Microsoft Research, Los Angeles, California, USA 2 The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA 3 School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Nat Methods 11:309-11. 2014
..Corresponding software is available from http://www.microsoft.com/science/...
- An exhaustive epistatic SNP association analysis on expanded Wellcome Trust data
Microsoft Research, Los Angeles, CA, USA
Sci Rep 3:1099. 2013
..Our work suggests that carefully combining data from large repositories could reveal many new biological insights through increased power. As a community resource, all results have been made available through an interactive web server...
- Patterns of methylation heritability in a genome-wide analysis of four brain regions
eScience Group, Microsoft Research, 1100 Glendon Avenue, Suite PH1, Los Angeles, CA 90024, USA
Nucleic Acids Res 41:2095-104. 2013
..Finally, we show that the number of heritable loci depends on the window size parameter commonly used to identify candidate cis-acting single-nucleotide polymorphism variants...
- Quantifying the uncertainty in heritability
Nicholas A Furlotte
1 Microsoft Research, Los Angeles, CA, USA 2 Computer Science Department, University of California, Los Angeles, CA, USA
J Hum Genet 59:269-75. 2014
..Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large...