SimHap Beta 2.1 Release Notes - 21/03/2006

Since the release of SimHap Beta 2.0, several modifications to the program have been made. These modifications are outlined below. We recommend that you download the new version of SimHap and update the version of R you have installed, even if you were happy with the Beta 2.0 version.

Problems caused by missing genotype data in single SNP analysis
* A bug was recently reported with respect to how SimHap deals with missing data for single SNP analysis. This bug appeared to be a 	problem when data contained large amounts of missing genotype data, with results tending to the null hypothesis of no association 	due to a minor homozygote recoding error. This bug has been fixed.
* The Analysis of Variance test performed in single SNP analysis, used to test for an improvement in a model with genetic covariates against a model without genetic covariates, can be affected by missing genotype data. By default, individuals are omitted from analysis if they have missing data for the covariates included in a model. Individuals with missing genotype data may have complete phenotype data, and hence will be included in the model that does not adjust for SNPs, but will be excluded when SNPs are then added to the model. If this is the case, the ANOVA is attempting to be performed using models fitted to data sets of different sizes. If this is attempted, the ANOVA test will crash. To overcome this, for single SNP analysis we have replaced the ANOVA with a Likelihood Ratio Test (LRT) for Quantitative and Binary outcomes. We are still working on implementing an appropriate test for Richt-censored and Longitudinal outcomes. Caution should be taken when interpreting the results of the LRT, as this test is based on the assumptions that the data come from the parametric model under consideration and that the parameter satisfies the null hypothesis. For example, for quantitative outcomes, the LRT is not robust to departures from Normality, and can only safely be interpreted if Normality of the outcome variable is ensured. Keep in mind that the effect of the SNP on the outcome, adjusted for other covariates in the model, can be assessed by looking at the effect size and p-value of the SNP on the SimHap Results screen. 

We apologise for any inconvenience these problems may have caused the users.

Interface improvements
* The interface for data file browsing, at the Data Input stage of SimHap has been improved, particularly for Linux users, to facilitate easier file browsing and provide a consistent file browsing interface for all platforms.
* For haplotype analysis, once haplotype frequencies have been generated, these frequencies are displayed in the SimHap window with there standard errors. At the bottom of this window, the SNPs used to generate these haplotypes, and the order in which they were used is now reported.
* The user has the option to view individuals with their possible haplotype configurations and posterior probabilities. In SimHap Beta 2.0, individuals were referenced numerically as 1 to n. This table has been improved to use the actual individual IDs as supplied in the genotype and phenotype files (i.e. the IDs in the first column of both files).
* Some small interface additions have been made to enable more stable use of SimHap on Mac OS platforms.

We thankyou for your very useful feedback on SimHap Beta 2.0, and hope that you enjoy using SimHap Beta 2.1. Please ensure that you register your details with us so you may be promptly informed of future additions and improvements to SimHap.

Pamela McCaskie