I am running the Lotus2 tool with multiple fastq files.
When I include the whole dataset (27 fastq files) the job fails with the error message,
‘This job was terminated because it used more memory than it was allocated’
More than 90% of my 100gb data storage was available when I ran this so I assume that the above error refers to working memory.
I have since successfully run the Lotus2 tool using various subsets of the data (i.e. 8 fastq files rather than 27), however this will not be appropriate for my analysis as the OTUs generated will not be comparable across datasets.
It seems possible from other forum posts that either some input is currently incorrectly specified,
or that I indeed need to run my job on a server with higher working memory.
Please, report the failed job to the server admins as following: click at any output from the failed job, click at Error icon, the one looking like lady bird beetle, in the middle window provide a brief description (optional) and hit Report. Error reports give the server admins access to job setup and input data.
The quota (storage in your Galaxy account) is not related to memory used for data analysis. Often, memory allocation in Galaxy correlates with size of input data, buy rules created by the server admins. In meantime, can you reduce size of the data? Does it work for smaller number of samples? Also, check LotiS2 paper for recommendation for memory requirements:
Example: In its fastest configuration (using “UPARSE” option in clustering and “RDP” to assign taxonomy), the gut and soil 16S rRNA datasets can be processed with LotuS2 in under 20 min and 12 min, respectively, using < 10 GB of memory and 4 CPU cores.