December 15, 2012

Genotype imputation via matrix completion (Chi et al. 2012)

Link to Mendel.

Genome Res doi: 10.1101/gr.145821.112

Genotype imputation via matrix completion

Eric C. Chi et al.

Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in Matlab and tested on real data from HapMap3, simulated pedigree data, and simulated low-coverage sequencing data derived from the 1000 Genomes Project. Compared to leading imputation programs, matrix completion as embodied in our program Mendel-Impute achieves comparable imputation accuracy while reducing run times significantly. Implementation in a lower-level language such as Fortran or C is apt to further improve computational efficiency.


1 comment:

Rui said...

Main thing about MENDEL-IMPUTE seems to be a very significant reduction in run times with very decent accuracy.

But "MaCH can obtain better accuracies by increasing the size of the latent state space and increasing the number of MCMC rounds."

Essentially, they observe a trade beteween a minor drop off in performance for big reductions in computation time.

"Compared to BEAGLE and IMPUTE2, Mendel-Impute suffers marginal decline in association testing and retains a substantial edge in computation time."

Also, "Mendel-Impute may at times produce more hits than the other methods and possibly more false positives"