Error in if (any(which.row)) { : missing value where TRUE/FALSE needed about bayesprism

[tinyi]

Hi Tianqi,

It turned out that the error was caused by having too few genes (N=63), and some bulk samples have zero expression over all selected genes. Unless there is a strong reason, I would recommend substantially increase the number of genes. Otherwise you may simply manually filter out bulk samples with sufficient number of total reads over your selected genes.

Best,

Tinyi

[tinyi]

Hi Tianqi, It seems a bit odd. If error is not reproducible, I would suspect it might be a memory issue, in which case you may try using fewer threads. Also the number of overlapping genes between your bulk data and reference is less than 100, which may need to double check. If error persists, you may send me your prism object, I am happy to help you troubleshoot. Best, Tinyi

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On Mon, Jul 18, 2022 at 10:43 PM Tianqi MA ***@***.***> wrote: Hi, BayesPrism team I've played this package for a while and it performes very stable. But today I encountered an error like this: recommend to have sufficient number of cells in each cell state Number of outlier genes filtered from mixture = 44 Aligning reference and mixture... Nornalizing reference... Warning message: In new.prism(reference = sc.dat.filtered.pc, mixture = bk.dat, input.type = "count.matrix", : Warning: very few gene from reference and mixture match! Please double check your gene names. Run Gibbs sampling... Current time: 2022-07-19 02:02:40 Estimated time to complete: 2mins Estimated finishing time: 2022-07-19 02:04:01 Start run... R Version: R version 4.1.2 (2021-11-01) snowfall 1.84-6.1 initialized (using snow 0.4-4): parallel execution on 50 CPUs. Stopping cluster Update the reference matrix ... Error in if (any(which.row)) { : missing value where TRUE/FALSE needed Calls: run.prism -> updateReference -> get.MLE.psi_mal -> norm.to.one In addition: Warning message: In searchCommandline(parallel, cpus = cpus, type = type, socketHosts = socketHosts, : Unknown option on commandline: --file Execution halted It's kind of weird because the the query data (83 samples) is always the same in the past few succeed trials. The only difference is that the number of genes in it is reduced from 2000 to 901 like this > dim(bk.dat) [1] 83 901 Besides, if I subset some of the 83 samples and add part/all them up to make a artifical dataset like this. data$testA1 = with(data, CR190516 + CR190517 + CR190518 + CR190522 + CR190523) ; data$testA2 = with(data, CR190516 + CR190517 + CR190518 ) ; data$testA3 = with(data, CR190518 + CR190522 + CR190523) ; data$testA4 = with(data, CR190516 ); data$testA5 = with(data, CR190517 ); data$testA6 = with(data, CR190518 ); data$testA7 = with(data, CR190522 ); data$testA8 = with(data, CR190523 ); testSamples=colnames(data)[grepl("test", colnames(data))] test = data[,testSamples] rownames(test) = rownames(data) ; testData=t(test) ; bk.dat <- testData No errors showed up. Is the error coming from some of my samples? — Reply to this email directly, view it on GitHub <#4>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHSZ2LM6FALHNQYHQBFLVUYI4TANCNFSM536L76MA> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[Tianqi-Ma]

Thank you for replying. I will try it later and let you know what's going on.

BTW, I found the performance can be improved dramatically (at least in my case) when building query matrix using 975 genes (the genes I used in the failed trial above) from https://www.deepcap.org/download. Perhaps you can have a test using this gene list and incooperate it into existed pipeline if it has a universal improvement (only for suggestion, of course).

[Tianqi-Ma]

I found this issue is some kind of sample-specific, but I didn't figure it out in detail. Please leave an email address so that I can send you my prism object. Thank you very much for your help.

[tinyi]

Hi Tianqi, Thank you for your suggestion. I took a brief look at those 975 genes. It seems that those genes are used to define cancer types, rather than cell types? Usually marker genes that define cell types would increase the accuracy for all deconvolution algorithms. Also the size of genes 975 seems to be slightly small IMO. I was curious about the setup of your problem and the way performance was tested. You may save your data as an rdata file and send it to ***@***.*** I am happy to look into it. Best, Tinyi

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On Wed, Jul 20, 2022 at 3:28 AM Tianqi MA ***@***.***> wrote: I found this issue is some kind of sample-specific, but I didn't figure it out in detail. Please left an email address so that I can send you my prism object. Thank you very much for your help. — Reply to this email directly, view it on GitHub <#4 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHSZA7QXGHH6A235UAQLVU6TCDANCNFSM536L76MA> . You are receiving this because you commented.Message ID: ***@***.***>

[Tianqi-Ma]

Hi, Tinyi

Yes, in my case , I was trying to deconvolute tumor cells in blood sample. BTW, I can't see the email address.

[tinyi]

Looks like github automatically hides the email. Use tc532 at cornell.com

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On Thu, Jul 21, 2022 at 10:29 PM Tianqi MA ***@***.***> wrote: Hi, Tinyi Yes, in my case , I was trying to deconvolute tumor cells in blood sample. BTW, I can't see the email address. — Reply to this email directly, view it on GitHub <#4 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHS7MJMNMDPXMM5FPWQTVVIBR3ANCNFSM536L76MA> . You are receiving this because you commented.Message ID: ***@***.***>

[Tianqi-Ma]

Cannot find tc532 at cornell.com. Did you receive the emial or is there a missing suffix?

[tinyi]

Sorry. should be cornell.edu

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On Thu, Jul 21, 2022 at 10:51 PM Tianqi MA ***@***.***> wrote: Cannot find tc532 at cornell.com. Is there a missing suffix? — Reply to this email directly, view it on GitHub <#4 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHS253HX574VOGZ4KP63VVIEBDANCNFSM536L76MA> . You are receiving this because you commented.Message ID: ***@***.***>

[Tianqi-Ma]

Ahhhhh, I was suspecting so as well. Anyway, thanks so much for your patience.

Hope you have a good day!