TASSEL Frequently Asked Questions
1. What if I have problems with Tassel?
We are interested in improving TASSEL to make it a very reliable. Tassel is an open source software project hosted on SourceForge and has a bug tracking list where you can notify the developer community of problems. In order for a bug to be fixed, we must be able to replicate the problem. Thus, it is important to document the steps that were taken that culminated in the error. If the data you are working with is not sensitive, please include the files which were used in the faulty procedure. You may also email the files to one of the software developers.
2. How do I change the amount of memory used? What do I do when the “Exception java.lang.OutOfMemoryError” occurs?
If you are working with very large data sets or are running memory intensive procedures, there may be occasions when Tassel runs out of memory. For most routine usage, however, Tassel memory is sufficient. By default, Tassel is allocated up to 512 Mb of memory space on your computer. If more is available on your computer, you can increase the amount allocated by downloading the stand-alone version of TASSEL and starting it from the command line. Modify the start_tassel.bat or start_tassel.pl scripts to change the amount of memory available. -Xms specifies the starting memory. -Xmx specifies the maximum memory available.
3. Why do I need to exclude one covariate from my population structure before running GLM or MLM?
Since the covariates of a population structure sum to one, any one of the covariates need to be removed, in order for GLM and MLM to execute correctly.
4. Why do I get results from Tassel or SAS but not the other?
While both SAS and Tassel have criteria for convergence and maximum number of iteration, these may not necessarily be the same for each software package. This explains why you may get converged data from one but not the other.
5. What should I substitute for missing values in TASSEL?
For trait data and population structure, use “-999” for missing values. For SNP data, use “N”. Kinship does not allow for missing values.
6. If I have kinship data, is population structure still needed when using the MLM? Or is only kinship, trait, and genotype data needed?
Both the population structure (Q) and Kinship (K) matrices should be included when running the MLM. If desired, you could compare the results of Q+K with that of the K-only model as well. When a marker is significant using the GLM but not when using the K matrix in MLM, this indicates that the association found under the GLM can also be explained by the relationships described by the K matrix. When you include both the Q and K matrices in your MLM, you have decided not to accept any marker-trait associations that can also be explained by either primary population structure (Q) or the general genetic background (K).
7. Is it possible to change data names in the Data Tree?
Yes. Click on the desired data name in the Data Tree, wait for one second, and then click it again or immediately hit the F2 key. Rename the dataset and then hit Enter to save the change.
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