Closed MonicaSteffi closed 3 years ago
Hi monica what a great dataset. Not all functions in aldex have multicore support.
I would suggest with a dataset where there are as many samples as features to reduce the number of montecarlo replicates to 8 or 16 as you actually are capturing a lot of the variance with the biosamples. so you could try mc.samples=16 to reduce run time.
I will work on including a multicore environment for all functions
Thank you.
Hi Monica, The bad news: in looking through the code a bit more, it seems that most functions that can be run in parallel are set up to use multicore. The real issue is that the bottlenecks in the code are not those that are trivial to parallelize. The good news: there are a number of bottlenecks that I think I can address. Thanks for making me look through the code again, I think I can do some speed enhancements
Hi Monica, The bad news: in looking through the code a bit more, it seems that most functions that can be run in parallel are set up to use multicore. The real issue is that the bottlenecks in the code are not those that are trivial to parallelize. The good news: there are a number of bottlenecks that I think I can address. Thanks for making me look through the code again, I think I can do some speed enhancements
Hi @ggloor
Thank you so much.
Somehow I managed to run aldex2 for my dataset. First I run aldex.clr() module followed by ttest() module. However, Now I am facing different problem. I got only NaN for the wi test. But got the value for we test.
we.ep | we.eBH | wi.ep | wi.eBH |
PWY-7013 | 7.47E-01 | 7.50E-01 | NaN | NaN
PWY-5971 | 6.91E-01 | 6.95E-01 | NaN | NaN
PWY-6630 | 6.21E-01 | 6.26E-01 | NaN | NaN
PWY-5531 | 6.15E-01 | 6.19E-01 | NaN | NaN
PWY-7159 | 3.87E-01 | 3.91E-01 | NaN | NaN
PWY-7090 | 2.85E-01 | 2.89E-01 | NaN | NaN
I have attached my output rds. How do I trace the error? https://www.dropbox.com/s/v2lo6b0g84q8odq/Region_South_North_KOabun_in_filt_aldex_1.rds?dl=0
Str of my data:
data.frame': 4000 obs. of 4527 variables:
$ run5.326. : num 6623.02 2.05 0 33.59 3836.14 ...
$ run5.327. : num 7293.73 1.41 0 19.89 4295.43 ...
$ run5.328. : num 6929.47 2.69 0 0 3538.15 ...
$ run5.329. : num 6311.76 1.12 0 0 3208.59 ...
$ run5.330. : num 6533.48 1.94 0 0 4170.34 ...
I executed the following command
Region_clr<- aldex.clr(round(Region_pathabun_in), conds, denom="all", verbose=TRUE, useMC = TRUE )
Region_aldex<-aldex.ttest(Region_clr, paired.test = FALSE, hist.plot = FALSE, verbose = TRUE)
Dear All, I have a picrust output for a huge dataset. It has with 4000 KO and 4570 samples. I would like to run differential abundance testing on top of that. Since it will take a lots of time, I would like to do it on multicore. I would like to run it slurm.
This is my slurm code:
I know there is a option useMC=TRUE in aldex to enable the multicore. In my R_script, I gave the following command.
Region_pathabun <- aldex(round(Region_path), conds, effect=TRUE, useMC=TRUE)
But it was still running on single core. How do I specificity number of cores in aldex function?