I m getting the following error when trying to run MEGANizer, do you have any suggestions?
Version MEGAN Community Edition (version 6.20.19, built 5 Jan 2021)
Author(s) Daniel H. Huson
Copyright © 2020 Daniel H. Huson. This program comes with ABSOLUTELY NO WARRANTY.
Functional classifications to use: EC, EGGNOG, GTDB, INTERPRO2GO, SEED
Loading ncbi.map: 2,259,889
Loading ncbi.tre: 2,259,893
Loading ec.map: 8,081
Loading ec.tre: 8,085
Loading eggnog.map: 30,875
Loading eggnog.tre: 30,986
Loading gtdb.map: 240,103
Loading gtdb.tre: 240,107
Loading interpro2go.map: 12,738
Loading interpro2go.tre: 28,689
Loading seed.map: 978
Loading seed.tre: 979
In DAA file: BF4.daa
Output file: BF4.rma
Classifications: Taxonomy, SEED, EGGNOG, GTDB, EC, INTERPRO2GO
Generating RMA6 file Parsing matches
Annotating RMA6 file using FAST mode (accession database and first accession per line)
Parsing file BF4.daa
Parsing file: BF4.daa
10% 20% 30% Exception in thread “pool-2-thread-1” java.lang.OutOfMemoryError: Java heap space
at java.base/java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:1650)
at java.base/java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1182)
at java.base/java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:899)
at java.base/java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1056)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1116)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:630)
at java.base/java.lang.Thread.run(Thread.java:832)
Meganization requires and lot of memory und so you need to increase the amount of memory assigned to MEGAN, e.g. by editing the file MEGAN.vmoptions, or by reinstalling the software and setting the memory to a higher value during the installation process.
I would recommend at least 16G, but more is better (the program will run faster).