Error in rmultinom

[xzhouaw]

Thanks for the useful deconvolution tool. I am trying to use TED to deconvolute bulk RNA-seq data from tissues. And I used raw reads for scRNA-seq and expected counts generated from RSEM for bulk RNA-seq as input to run TED. However, I got the error as the following:

[1] "removing non-numeric genes..."
[1] "removing outlier genes..."
Number of outlier genes filtered= 7 
[1] "aligning reference and mixture..."
[1] "No tumor reference is speficied. Reference profiles are treated equally."
[1] "run first sampling"
current sample ID:1  Error in rmultinom(n = 1, size = X.i[g], prob = prob.mat[, g]) : 
  invalid second argument 'size'
Calls: run.Ted ... draw.sample.gibbs -> mclapply -> lapply -> FUN -> sample.n -> rmultinom
Execution halted

Here is my code :
library(TED)

ref.dat <- read.csv("scRNA-counts-for.t-for.csv", header=TRUE, row.names=1, sep="\t")
X <- read.csv("placenta_genename-count.uniq.t.for.csv", header=TRUE, row.names=1, sep="\t")
cell.type <- read.csv("scRNA-celltype-for.csv", header=FALSE, sep="\t")
cell.type.labels <- cell.type[[1]]
run.Ted(ref.dat, X, cell.type.labels, input.type="scRNA", pdf.name="trail.pdf")

Is there any suggestion about this error?
Thanks~

[tinyi]

Could you print the head(rownames(ref.dat)), head(colnames(ref.dat)), head(rownames(X)), head(colnames(X)) ? I suspect that it might be caused by an unmatched input data format. Thanks.

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On Sun, Aug 22, 2021 at 1:41 PM xzhouaw ***@***.***> wrote: Thanks for the useful deconvolution tool. I am trying to use TED to deconvolute bulk RNA-seq data from tissues. And I used raw reads for scRNA-seq and expected counts generated from RSEM for bulk RNA-seq as input to run TED. However, I got the error as the following: [1] "removing non-numeric genes..." [1] "removing outlier genes..." Number of outlier genes filtered= 7 [1] "aligning reference and mixture..." [1] "No tumor reference is speficied. Reference profiles are treated equally." [1] "run first sampling" current sample ID:1 Error in rmultinom(n = 1, size = X.i[g], prob = prob.mat[, g]) : invalid second argument 'size' Calls: run.Ted ... draw.sample.gibbs -> mclapply -> lapply -> FUN -> sample.n -> rmultinom Execution halted Here is my code : library(TED) ref.dat <- read.csv("scRNA-counts-for.t-for.csv", header=TRUE, row.names=1, sep="\t") X <- read.csv("placenta_genename-count.uniq.t.for.csv", header=TRUE, row.names=1, sep="\t") cell.type <- read.csv("scRNA-celltype-for.csv", header=FALSE, sep="\t") cell.type.labels <- cell.type[[1]] run.Ted(ref.dat, X, cell.type.labels, input.type="scRNA", pdf.name="trail.pdf") Is there any suggestion about this error? Thanks~ — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#13>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHSYXPZFAPVSLVUSXSHLT6EZFJANCNFSM5CTFCUYA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&utm_campaign=notification-email> .

[xzhouaw]

Thanks for your fast reply. Here is the result:

> head(rownames(X))
[1] "X20210128.RNA.Cov1"  "X20210128.RNA.Cov2"  "X20210128.RNA.Cov3" 
[4] "X20210128.RNA.Ctrl1" "X20210128.RNA.Ctrl2" "X20210128.RNA.Ctrl3"
> head(colnames(X))
[1] "A1BG"     "A1BG.AS1" "A1CF"     "A2M"      "A2M.AS1"  "A2ML1"  
> head(rownames(ref.dat))
[1] "Ctrl2_AAACCCAAGAGGTGCT.1" "Ctrl2_AAACCCAGTGAACGGT.1"
[3] "Ctrl2_AAACGAAAGCACACAG.1" "Ctrl2_AAACGAAAGGGTGGGA.1"
[5] "Ctrl2_AAACGAAGTATCCCAA.1" "Ctrl2_AAACGCTAGGGCTTCC.1"
> head(colnames(ref.dat))
[1] "AL627309.1" "AL627309.3" "AL627309.5" "AL627309.4" "AP006222.2"
[6] "AL732372.1"

[tinyi]

I suspect that it was caused by the issue that your input was dataframe rather than matrix type. Try converting them to matrix using as.matrix.

…

On Sun, Aug 22, 2021 at 11:54 PM xzhouaw ***@***.***> wrote: Thanks for your fast reply. Here is the result: > head(rownames(X)) [1] "X20210128.RNA.Cov1" "X20210128.RNA.Cov2" "X20210128.RNA.Cov3" [4] "X20210128.RNA.Ctrl1" "X20210128.RNA.Ctrl2" "X20210128.RNA.Ctrl3" > head(colnames(X)) [1] "A1BG" "A1BG.AS1" "A1CF" "A2M" "A2M.AS1" "A2ML1" > head(rownames(ref.dat)) [1] "Ctrl2_AAACCCAAGAGGTGCT.1" "Ctrl2_AAACCCAGTGAACGGT.1" [3] "Ctrl2_AAACGAAAGCACACAG.1" "Ctrl2_AAACGAAAGGGTGGGA.1" [5] "Ctrl2_AAACGAAGTATCCCAA.1" "Ctrl2_AAACGCTAGGGCTTCC.1" > head(colnames(ref.dat)) [1] "AL627309.1" "AL627309.3" "AL627309.5" "AL627309.4" "AP006222.2" [6] "AL732372.1" — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#13 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHS26M7J3FIOMKMYNW43T6HBA3ANCNFSM5CTFCUYA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&utm_campaign=notification-email> .

[xzhouaw]

Thanks! I used the following code to convert them to matrix and then the problem disappeared.

ref.dat <- data.matrix(read.csv("scRNA-counts-for.t-for.csv", header=TRUE, row.names=1, sep="\t"))
X <- data.matrix(read.csv("placenta_genename-count.uniq.t.for.csv", header=TRUE, row.names=1, sep="\t"))

I am pretty new to R language, so after I got the result, I am not sure how to extract the cell proportion of each sample and the gene expression to a new file now. I used the followed code, but it reminded "Error: object 'res' not found".

fraction_1 <- res$first.gibbs.res$gibbs.theta
write.csv(fraction_1, "initial_fraction.csv")
fraction_2 <- res$first.gibbs.res$theta.merged
write.csv(fraction_2, "summed_fraction.csv")
expression_1 <- res$first.gibbs.res$Znkg
write.csv(expression_1, "initial_expression.csv")
expression_2 <- res$first.gibbs.res$Znkg.merged
write.csv(expression_2, "summed_expression.csv")

By the way, this is the part of the result, is it the proportion of each cell types of different sample? Do I understand properly?

$res$first.gibbs.res$theta.merged
                                   Fibroblast           ST    Vascular
X20210128.RNA.Cov1                0.084226439 2.010806e-06 0.102461011
X20210128.RNA.Cov2                0.043057241 1.005924e-06 0.169533072
X20210128.RNA.Cov3                0.338976195 7.365366e-07 0.210604896
X20210128.RNA.Ctrl1               0.067247233 1.069072e-06 0.350462530
X20210128.RNA.Ctrl2               0.120580135 4.189616e-01 0.021133022
X20210128.RNA.Ctrl3               0.188919622 2.135598e-01 0.159996034
X20210413.RNA.seq.covid4.placenta 0.170492060 9.523773e-02 0.161865213
X20210413.RNA.seq.covid5.placenta 0.114260971 6.995568e-07 0.183139142
X20210413.RNA.seq.covid6.placenta 0.042868862 1.484226e-06 0.183065919
X20210413.RNA.seq.covid7.placenta 0.196240879 2.272424e-06 0.294446013
X20210413.RNA.seq.ctrl4.placenta  0.241235347 5.646776e-07 0.200068194
X20210413.RNA.seq.ctrl5.placenta  0.071789509 5.505970e-01 0.048570371
X20210413.RNA.seq.ctrl6.placenta  0.005887166 5.274084e-01 0.001347521

Sorry for my questions, Thanks for your reply.

[tinyi]

please see the vignette.pdf for details. please let me know if there are any questions.

…

On Wed, Aug 25, 2021 at 12:11 AM xzhouaw ***@***.***> wrote: Thanks! I used the following code to convert them to matrix and then the problem disappeared. ref.dat <- data.matrix(read.csv("scRNA-counts-for.t-for.csv", header=TRUE, row.names=1, sep="\t")) X <- data.matrix(read.csv("placenta_genename-count.uniq.t.for.csv", header=TRUE, row.names=1, sep="\t")) I am pretty new to R language, so after I got the result, I am not sure how to extract the cell proportion of each sample and the gene expression to a new file now. I used the followed code, but it reminded "Error: object 'res' not found". fraction_1 <- res$first.gibbs.res$gibbs.theta write.csv(fraction_1, "initial_fraction.csv") fraction_2 <- res$first.gibbs.res$theta.merged write.csv(fraction_2, "summed_fraction.csv") expression_1 <- res$first.gibbs.res$Znkg write.csv(expression_1, "initial_expression.csv") expression_2 <- res$first.gibbs.res$Znkg.merged write.csv(expression_2, "summed_expression.csv") By the way, this is the part of the result, is it the proportion of each cell types of different sample? Do I understand properly? $res$first.gibbs.res$theta.merged Fibroblast ST Vascular X20210128.RNA.Cov1 0.084226439 2.010806e-06 0.102461011 X20210128.RNA.Cov2 0.043057241 1.005924e-06 0.169533072 X20210128.RNA.Cov3 0.338976195 7.365366e-07 0.210604896 X20210128.RNA.Ctrl1 0.067247233 1.069072e-06 0.350462530 X20210128.RNA.Ctrl2 0.120580135 4.189616e-01 0.021133022 X20210128.RNA.Ctrl3 0.188919622 2.135598e-01 0.159996034 X20210413.RNA.seq.covid4.placenta 0.170492060 9.523773e-02 0.161865213 X20210413.RNA.seq.covid5.placenta 0.114260971 6.995568e-07 0.183139142 X20210413.RNA.seq.covid6.placenta 0.042868862 1.484226e-06 0.183065919 X20210413.RNA.seq.covid7.placenta 0.196240879 2.272424e-06 0.294446013 X20210413.RNA.seq.ctrl4.placenta 0.241235347 5.646776e-07 0.200068194 X20210413.RNA.seq.ctrl5.placenta 0.071789509 5.505970e-01 0.048570371 X20210413.RNA.seq.ctrl6.placenta 0.005887166 5.274084e-01 0.001347521 Sorry for my questions, Thanks for your reply. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#13 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHS2CKPA223EV6T645DTT6RUNLANCNFSM5CTFCUYA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&utm_campaign=notification-email> .