Hi, I am running Qiime2 version 2019.4 as a Miniconda3 environment on an Ubuntu Desktop app version 18.04 on a Windows 10 system.
I have been trying to make a phylogenetic tree from a merged Feature[Sequence] table I made.
I had Ion Torrent 16S sequencing data from multiple runs with MrDNA. I first input .fna and .qual files into split_libraries.py on Qiime1 and individually imported the resulting seqs.fna files into Qiime2. I dereplicated with vsearch dereplicate-sequences to get individual rep-seqs.qza files. Next I took those and did qiime vsearch cluster-features-open-reference with the Silva 132 release 97% .qza to get rep-seqs-or-97.qza files. Then I used qiime feature-table merge-seqs to merge the rep-seqs-or-97.qza files. Out of this, I got a merged-rep-seqs.qza, and everything was fine up until this point. The merged-rep-seqs.qza is what I have been trying to use for generating the tree.
I enter this:
(qiime2-2019.4) dkrachel@DESKTOP-LPD2VHA:~/qiime2_passaic-comparison$ qiime phylogeny align-to-tree-mafft-fasttree --i-sequences merged-rep-seqs.qza --o-alignment aligned-merged-rep-seqs.qza --o-masked-alignment masked-aligned-rep-seqs.qza --o-tree unrooted-tree.qza --o-rooted-tree rooted-tree.qza
and the app never returns anything. It just blinks for a couple hours like it is still working and then the app window goes black.
When I re-ran the same command in the wrong directory:
(qiime2-2019.4) dkrachel@DESKTOP-LPD2VHA:~$ qiime phylogeny align-to-tree-mafft-fasttree --i-sequences merged-rep-seqs.qza --o-alignment aligned-merged-rep-seqs.qza --o-masked-alignment masked-aligned-rep-seqs.qza --o-tree unrooted-tree.qza --o-rooted-tree rooted-tree.qza
I got this:
(1/1) Invalid value for ââi-sequencesâ: âmerged-rep-seqs.qzaâ is not a QIIME
2 Artifact (.qza)
I can see that the .qza file Iâm using should be the correct QIIME2 artifact:
qiime tools peek merged-rep-seqs.qza
UUID: 6ee57535-32f5-4f09-bb95-16295325faaf
Type: FeatureData[Sequence]
Data format: DNASequencesDirectoryFormat
Iâve looked up the Ubuntu Desktop app and it says that it has 4 GB system memory. Is this not enough? I know for Qiime1, I allocated 4 GB memory and that was enough to go through an entire similar workflow. Iâm wondering if this is a memory issue or something wrong with the file types, or if I missed something?
Still, it also can be a memory issue. If you are able to run successfully the same with smaller data set, and your current is bigger, I think, you donât have enough of RAM
I tried your suggestion and merged only two instead of the four rep-seqs-or-97.qza files I have, then tried to make the tree with that. Iâm still having the same problem. (Itâs been 30 minutes, but I donât expect it will finish.) I have data from only six samples on four different runs. One run has three samples. If it wasnât for that one run with multiple samples, I can make a manifest file and import that way. Dada2 doesnât take the demultiplexed .fasta files I can make in Qiime1 for the multi-sample run, so I had to import everything as .fasta and use clustering. I thought I would be able to process 6 samples on my computer without a problemâŚ?
I'm sorry, I guess it is not Ubuntu Desktop, it is just "Windows Ubuntu". It just looks like a terminal window. I don't know how to see CPU history, but I can see Memory and Swap. I included the Task manager from Windows while it is stuck running this command in the Ubuntu app. Is that helpful?
Sounds like you are running Ubuntu directly through windows using WSL, instead of a VirtualBox or other VM. Iâm not super familiar with Windows Subsystem for Linux (WSL), but this is a really great place to start!
Both those windows show 82% through 87% usage of RAM. You mentioned that your computer has 16 GB of RAM, but it looks like those GB are not getting seen by your PC.
This is a real mystery! Letâs see what the Qiime devs recommend!
Good! That means it is running! I think things are working fine, you just arenât letting them run long enough to finish (this command can take a very long time). If you want to see live output, run the command with the --verbose flag. You might also want to run with multiple threads, depending on the capacity of your computation environment.
It worked! It took 5 hours to run. I guess I just needed to be patient and adjust my sleep settings. I think I will be switching to a computing cluster soon.