FAQ

1. How do I execute Java in my machine?

   1. For Windows users:

      1. Click a Windows start button (or press a Windows key between Ctrl and Alt)

      2. Windows XP: Click “Run…” and type “cmd”. This will pop up the console

      3. Windows 7: Type “cmd” in the “Search Programs and Files” box. This will pop up the console

      4. Type “java” on the console. If you see an error message saying that Java is not found or Java is not recognized, you need to install Java on your machine. Please visit Download & Instructions to find how to install Java.

   2. For Mac users:

      1. Click “Finder”

      2. Click “Applications” -> “Utilities” -> “Terminal”. This will pop up the console

      3. Type “java” on the console. Java should be pre-installed on your machine. If you want to update to the latest version of Java, please visit Download & Instructions to find how to install Java.

2. When I type “java -jar RWAS.jar -h”, I see the following message:
   Exception in thread “main” java.lang.NoClassDefFoundError: orgapachecommonsmathdistribution/NormalDistribution

   1. This may happen when there is no “lib” directory in the same directory as RWAS.jar and LRT.jar. Please make sure you have “lib” directory.

3. Which method should I run on my dataset? RWAS or LRT?

   1. My suggestion is to run both :) RWAS and LRT take very different approaches in finding associations of groups of rare variants, and they may give different results on the same dataset. In regards to the statistical power of two methods, we show in our paper that LRT is more powerful than RWAS. However, LRT is also a computationally more expensive method. If you want to analyze many genes ( 20000) without high computing power, we suggest analyzing your dataset with RWAS. If you have a computer cluster with many nodes, we suggest both LRT and RWAS.

4. What's the running time of RWAS and LRT?

   1. Here are some rough estimates of runtime of our methods. The estimates are based on 1000 case and 1000 control individuals and 50 variants (one gene) running on a 2.26 GHz Macbook.
      · RWAS without a permutation test: less than a minute
      · RWAS with 1 million permutations: 10 minutes
      · LRT with 10 million permutations: 5 minutes
      

   2. The running time of RWAS with a permutation test scales linearly with the number of individuals, the number of variants and the number of permutations.

   3. The running time of LRT scales linearly with the number of variants and the number of permutations.

5. How can I speed up the analysis?

   1. Here's a simple tip to speed up your analysis when you analyze many genes simultaneously with a computer cluster.

      1. Convert your input file to Multiple Genes File Format

      2. Use -s and -e options to split the computing load to multiple nodes. For example,
         · Let's say you have 100 nodes in your cluster. You want to analyze 20,000 genes.
         · Each node should analyze 20,000 / 100 = 200 genes.
         · When submitting jobs, the first job should be submitted with a option -s 0 -e 200 assuming that the starting index of gene ID is 0
         · The second job should have a option -s 200 -e 400, and so on.

6. When I run RWAS or LRT with a big input file, I see the following message:
   Exception in thread “main” java.lang.OutOfMemoryError: Java heap space

   1. This error may occur if there is not enough heap space for Java. Please increase the heap space by including the parameter -Xmx. For instance, if you want to increase it to 1 GB, then please use the following command.
      java -Xmx1024m -jar LRT.jar -n ...

Please contact Jae Hoon Sul at jhsul at cs dot ucla dot edu if you have more questions or suggestions.