Hi,
I am during the training of the classifier on my MacBook. It has been running like 30 hours, and still no response. What should I do now?
(qiime2-amplicon-2023.9) yiggritewu@Yiggrites-MacBook-Air training-feature-classifiers % qiime feature-classifier extract-reads
--i-sequences 99_otus.qza
--p-f-primer CCTAYGGGRBGCASCAG
--p-r-primer GGACTACNNGGGTATCTAAT
--p-trunc-len 250
--p-min-length 100
--p-max-length 490
--o-reads ref-seqs.qza
Thanks
Hi @Yiggrite ,
The long runtime is unusually long, but not very surprising, because your primers contain many degenerate or ambiguous bases, and hence extract-reads needs to check for every possible combination across both primers. I am guessing that you must also have many sequences as well, so this is taking a long time to process. I suggest continuing to wait or try again with fewer ambiguous bases in your primer sequences if you can be more specific.
I have changed the title of this post to be more specific, as this is an issue with extract-reads... you have not reached the classifier training step yet (which will also take a while if you have many sequences, just as a warning).
Good luck!
Thank you very much for your reply.
I tied this command on both of Macbook and the Linux subsystem in Windows.
Just for this extract-reads step. Macbook has run it for 2 days but in WSL terminal only need half hour.
Maybe I should not use Macbook? not sure...
Hi,
I am running the extract-read command on the WSL terminal in windows, but the command was killed. I checked the memory info. Is this the reason?
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$ qiime feature-classifier extract-reads \
--i-sequences 2022.10.backbone.full-length.fna.qza
--p-f-primer CCTAYGGGRBGCASCAG
p-r-prim> --p-r-primer GGACTACNNGGGTATCTAAT
--p-trunc-len 250
--p-min-length 200
-max-len> --p-max-length 490
--o-reads ref-seqs.qza
Saved FeatureData[Sequence] to: ref-seqs.qza
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$ qiime feature-classifier fit-classifier-naive-bayes
--i-reference-reads ref-seqs.qza
--i-reference-taxonomy 2022.10.backbone.tax.qza
--o-classifier classifier.qza
Killed
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$ qiime feature-classifier fit-classifier-naive-bayes
--i-reference-reads ref-seqs.qza
--i-reference-taxonomy 2022.10.backbone.tax.qza
--o-classifier classifier.qza
Killed
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$ free -mh : command not found
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$ free -mh
total used free shared buff/cache available
Mem: 7.7Gi 1.1Gi 6.5Gi 1.0Mi 140Mi 6.4Gi
Swap: 2.0Gi 972Mi 1.0Gi
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$ vmstat -s
8069524 K total memory
1125624 K used memory
29428 K active memory
948220 K inactive memory
6791960 K free memory
7648 K buffer memory
144292 K swap cache
2097152 K total swap
995532 K used swap
1101620 K free swap
4138259 non-nice user cpu ticks
3902 nice user cpu ticks
348793 system cpu ticks
981189334 idle cpu ticks
149976 IO-wait cpu ticks
0 IRQ cpu ticks
12626 softirq cpu ticks
0 stolen cpu ticks
2084714 pages paged in
11151400 pages paged out
52595 pages swapped in
1066861 pages swapped out
5320163 interrupts
47183740 CPU context switches
1702679965 boot time
37849 forks
(qiime2) yiggrite@MWMJ07RHBF:~/qiime2/muxed-se-barcode-in-seq/training-feature-classifiers$
Thanks
Hi @Yiggrite ,
Running on different machines could give different results if you have different amounts of available RAM or other differences in the hardware. There should not be a specific issue with running this command on a mac.
Yes, most likely if this is a personal computer.
Good luck!
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