Can't load sce data #11

JihedC · 2019-11-26T16:35:04Z

Hi,
I am new to Ouija but quite excite about using it.
I have got my Seurat object transformed into a singleCellExperiment object. Unfortunately Ouija doesn't seem to see like this. I get this :

oui <- ouija(sample1.sce)
Error in t.default(x@assays[[single_cell_experiment_assay]]) : 
  argument is not a matrix

Am I doing something wrong?

The text was updated successfully, but these errors were encountered:

kieranrcampbell · 2019-11-29T09:39:14Z

Hi Jihed Did you get this working? I’m currently trying to debug but there are issues using Stan on MacOS Catalina that I’m looking into

…

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JihedC · 2019-11-29T10:53:35Z

Hi Kieran!
Thanks for your reply!
No I didn't manage to load the singlecellexperiment I created via Seurat. I tried to work around it by importing a matrix from my Seurat object.

expression <- as.matrix(sample@assays$RNA@data)
test <- expression[1:10,1:100]
transposed<-t(test)
test <- transposed +1
normalized_test <- log(test)

oui <- ouija(test)
plot_expression(oui)

But I have no clue if this is okay to do so. I have got this plot:

kieranrcampbell · 2019-11-29T14:55:47Z

Hmm looks like the sampler hasn't run at all. Let me debug over the next few days and see where I get. I suspect various dependencies have been updated that have broken the main package.

JihedC · 2019-11-29T15:02:48Z

ok thanks!
I have also tried to run your example with Singlecellexperiment:

library(ouija)
data(synth_gex)
single_cell_set <- SingleCellExperiment(assays = list(exprs = t(example_gex)))
ouija(single_cell_set)

Which also gives the same output :

Error in t.default(x@assays[[single_cell_experiment_assay]]) : 
  argument is not a matrix

kieranrcampbell · 2019-11-29T15:05:08Z

Ok that error should now be fixed in c77e652 -- can you reinstall from github and try again? Thanks

JihedC · 2019-11-29T15:05:31Z

Yep I'll have a look

JihedC · 2019-11-29T15:12:51Z

Ok that error should now be fixed in c77e652 -- can you reinstall from github and try again? Thanks

Nope I still get the same error message and the command :

data(synth_gex)

doesn't work anymore :(

kieranrcampbell · 2019-11-29T15:17:29Z

Okay at some point synth_gex became example_gex -- can you try that? I've updated doc in latest commit

JihedC · 2019-11-29T15:20:42Z

This is what I've got. Sorry it's in French, it means that the argument is not a matrix :(

> data(example_gex)
> single_cell_set <- SingleCellExperiment(assays = list(exprs = t(example_gex)))
> ouija(single_cell_set)
Error in t.default(x@assays[[single_cell_experiment_assay]]) : 
  l'argument n'est pas une matrice
>

kieranrcampbell · 2019-11-29T15:24:13Z

Ah the assay should be "logcounts" or the single_cell_experiment_assay changed to "logcounts" -- I've updated the vignette to reflect this, my fault for not changing sooner. Also it looks like you haven't reinstalled from github since I just changed the code to remove the line x@assays... -- could you reinstall using devtools::install_github and try again? Thanks

JihedC · 2019-11-29T15:25:55Z

I reinstalled earlier using this

devtools::install_github("kieranrcampbell/ouija")

I'll try again

JihedC · 2019-11-29T15:31:17Z

Ah the assay should be "logcounts" or the single_cell_experiment_assay changed to "logcounts" -- I've updated the vignette to reflect this, my fault for not changing sooner. Also it looks like you haven't reinstalled from github since I just changed the code to remove the line x@assays... -- could you reinstall using devtools::install_github and try again? Thanks

I am afraid I am not understanding what you mean. Which command should I use to load the ice assay?

By the way these are my session info (concerning the installation):

> sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS  10.14.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /anaconda3/envs/seurat/lib/R/lib/libRlapack.dylib

locale:
[1] fr_FR.UTF-8/fr_FR.UTF-8/fr_FR.UTF-8/C/fr_FR.UTF-8/fr_FR.UTF-8

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ouija_0.99.0                sctransform_0.2.0           rstan_2.19.2                ggplot2_3.2.1              
 [5] StanHeaders_2.19.0          Rcpp_1.0.3                  Seurat_3.1.1                knitr_1.26                 
 [9] SingleCellExperiment_1.4.1  SummarizedExperiment_1.12.0 DelayedArray_0.8.0          BiocParallel_1.16.6        
[13] matrixStats_0.55.0          Biobase_2.42.0              GenomicRanges_1.34.0        GenomeInfoDb_1.18.2        
[17] IRanges_2.16.0              S4Vectors_0.20.1            BiocGenerics_0.28.0

kieranrcampbell · 2019-11-29T15:35:15Z

single_cell_set <- SingleCellExperiment(assays = list(logcounts = t(example_gex)))
ouija(single_cell_set)

should work ?

I've also bumped the version number so if you get the same error as before (Error in t.default(x@assays[[single_cell_experiment_assay]]) ) can you reinstall and ensure version number is
0.99.1 ? Thanks

JihedC · 2019-11-29T15:43:03Z

I am sorry for bringing bad news to you today :(

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS  10.14.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /anaconda3/envs/seurat/lib/R/lib/libRlapack.dylib

locale:
[1] fr_FR.UTF-8/fr_FR.UTF-8/fr_FR.UTF-8/C/fr_FR.UTF-8/fr_FR.UTF-8

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ouija_0.99.1                sctransform_0.2.0           rstan_2.19.2                ggplot2_3.2.1              
 [5] StanHeaders_2.19.0          Rcpp_1.0.3                  Seurat_3.1.1                knitr_1.26                 
 [9] SingleCellExperiment_1.4.1  SummarizedExperiment_1.12.0 DelayedArray_0.8.0          BiocParallel_1.16.6        
[13] matrixStats_0.55.0          Biobase_2.42.0              GenomicRanges_1.34.0        GenomeInfoDb_1.18.2        
[17] IRanges_2.16.0              S4Vectors_0.20.1            BiocGenerics_0.28.0

But there is another error now :(

> ouija(single_cell_set)
Erreur : lazy-load database '/anaconda3/envs/seurat/lib/R/library/ouija/R/ouija.rdb' is corrupt
De plus : Warning message:
internal error -3 in R_decompress1

kieranrcampbell · 2019-11-29T15:45:18Z

No problem! Can you restart R (or terminate session in Rstudio) and try again? That usually resolves this error.

JihedC · 2019-11-29T16:38:52Z

Great it works!

I have one more question, if you can help me, it would be great!

I have managed to reproduce your example using the data(example_gex) but I still get the error when I load my own SCE object I have got from Seurat with as.SingleCellExperiment.
If I load my rds file in R and then run ouija I still get the error :

Error in t.default(assay(x, single_cell_experiment_assay)) : 
  l'argument n'est pas une matrice

This is what I tried with my own SCE object :

test <- readRDS(file = "SCE_thymo_cells_cycle_regressed.rds")
test_oui <- ouija(test)
Error in t.default(assay(x, single_cell_experiment_assay)) : 
  l'argument n'est pas une matrice

> str(test)
Formal class 'SingleCellExperiment' [package "SingleCellExperiment"] with 10 slots
  ..@ int_elementMetadata:Formal class 'DataFrame' [package "S4Vectors"] with 6 slots
  .. .. ..@ rownames       : NULL
  .. .. ..@ nrows          : int 17535
  .. .. ..@ listData       : Named list()
  .. .. ..@ elementType    : chr "ANY"
  .. .. ..@ elementMetadata: NULL
  .. .. ..@ metadata       : list()
  ..@ int_colData        :Formal class 'DataFrame' [package "S4Vectors"] with 6 slots
  .. .. ..@ rownames       : NULL
  .. .. ..@ nrows          : int 8981
  .. .. ..@ listData       : Named list()
  .. .. ..@ elementType    : chr "ANY"
  .. .. ..@ elementMetadata: NULL
  .. .. ..@ metadata       : list()
  ..@ int_metadata       :List of 3
  .. ..$ version          :Classes 'package_version', 'numeric_version'  hidden list of 1
  .. .. ..$ : int [1:3] 1 4 1
  .. ..$ spike_names      : chr(0) 
  .. ..$ size_factor_names: chr(0) 
  ..@ reducedDims        :Formal class 'SimpleList' [package "S4Vectors"] with 4 slots
  .. .. ..@ listData       :List of 3
  .. .. .. ..$ PCA : num [1:8981, 1:50] -11.04 -3.48 -10.32 -10.87 -4.52 ...
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:8981] "AAAAATTCTTAA" "GTAATTTAACGA" "TACAAGTTGATG" "TCAGCAATGACN" ...
  .. .. .. .. .. ..$ : chr [1:50] "PC_1" "PC_2" "PC_3" "PC_4" ...
  .. .. .. ..$ UMAP: num [1:8981, 1:2] -1.338 -2.712 2.348 -1.547 -0.965 ...
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:8981] "AAAAATTCTTAA" "GTAATTTAACGA" "TACAAGTTGATG" "TCAGCAATGACN" ...
  .. .. .. .. .. ..$ : chr [1:2] "UMAP_1" "UMAP_2"
  .. .. .. ..$ TSNE: num [1:8981, 1:2] 29.4 28.8 33.8 29.7 24.1 ...
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:8981] "AAAAATTCTTAA" "GTAATTTAACGA" "TACAAGTTGATG" "TCAGCAATGACN" ...
  .. .. .. .. .. ..$ : chr [1:2] "tSNE_1" "tSNE_2"
  .. .. ..@ elementType    : chr "ANY"
  .. .. ..@ elementMetadata: NULL
  .. .. ..@ metadata       : list()
  ..@ rowRanges          :Formal class 'CompressedGRangesList' [package "GenomicRanges"] with 5 slots
  .. .. ..@ unlistData     :Formal class 'GRanges' [package "GenomicRanges"] with 7 slots
  .. .. .. .. ..@ seqnames       :Formal class 'Rle' [package "S4Vectors"] with 4 slots
  .. .. .. .. .. .. ..@ values         : Factor w/ 0 levels: 
  .. .. .. .. .. .. ..@ lengths        : int(0) 
  .. .. .. .. .. .. ..@ elementMetadata: NULL
  .. .. .. .. .. .. ..@ metadata       : list()
  .. .. .. .. ..@ ranges         :Formal class 'IRanges' [package "IRanges"] with 6 slots
  .. .. .. .. .. .. ..@ start          : int(0) 
  .. .. .. .. .. .. ..@ width          : int(0) 
  .. .. .. .. .. .. ..@ NAMES          : NULL
  .. .. .. .. .. .. ..@ elementType    : chr "ANY"
  .. .. .. .. .. .. ..@ elementMetadata: NULL
  .. .. .. .. .. .. ..@ metadata       : list()
  .. .. .. .. ..@ strand         :Formal class 'Rle' [package "S4Vectors"] with 4 slots
  .. .. .. .. .. .. ..@ values         : Factor w/ 3 levels "+","-","*": 
  .. .. .. .. .. .. ..@ lengths        : int(0) 
  .. .. .. .. .. .. ..@ elementMetadata: NULL
  .. .. .. .. .. .. ..@ metadata       : list()
  .. .. .. .. ..@ seqinfo        :Formal class 'Seqinfo' [package "GenomeInfoDb"] with 4 slots
  .. .. .. .. .. .. ..@ seqnames   : chr(0) 
  .. .. .. .. .. .. ..@ seqlengths : int(0) 
  .. .. .. .. .. .. ..@ is_circular: logi(0) 
  .. .. .. .. .. .. ..@ genome     : chr(0) 
  .. .. .. .. ..@ elementMetadata:Formal class 'DataFrame' [package "S4Vectors"] with 6 slots
  .. .. .. .. .. .. ..@ rownames       : NULL
  .. .. .. .. .. .. ..@ nrows          : int 0
  .. .. .. .. .. .. ..@ listData       : Named list()
  .. .. .. .. .. .. ..@ elementType    : chr "ANY"
  .. .. .. .. .. .. ..@ elementMetadata: NULL
  .. .. .. .. .. .. ..@ metadata       : list()
  .. .. .. .. ..@ elementType    : chr "ANY"
  .. .. .. .. ..@ metadata       : list()
  .. .. ..@ elementMetadata:Formal class 'DataFrame' [package "S4Vectors"] with 6 slots
  .. .. .. .. ..@ rownames       : NULL
  .. .. .. .. ..@ nrows          : int 17535
  .. .. .. .. ..@ listData       :List of 5
  .. .. .. .. .. ..$ vst.mean                 : num [1:17535] 0.477 0.259 0.02 0.124 0.286 ...
  .. .. .. .. .. ..$ vst.variance             : num [1:17535] 0.6827 0.328 0.0224 0.1403 0.4018 ...
  .. .. .. .. .. ..$ vst.variance.expected    : num [1:17535] 0.697 0.3385 0.0242 0.1497 0.3788 ...
  .. .. .. .. .. ..$ vst.variance.standardized: num [1:17535] 0.979 0.969 0.924 0.937 1.061 ...
  .. .. .. .. .. ..$ vst.variable             : logi [1:17535] FALSE FALSE FALSE FALSE FALSE FALSE ...
  .. .. .. .. ..@ elementType    : chr "ANY"
  .. .. .. .. ..@ elementMetadata: NULL
  .. .. .. .. ..@ metadata       : list()
  .. .. ..@ elementType    : chr "GRanges"
  .. .. ..@ metadata       : list()
  .. .. ..@ partitioning   :Formal class 'PartitioningByEnd' [package "IRanges"] with 5 slots
  .. .. .. .. ..@ end            : int [1:17535] 0 0 0 0 0 0 0 0 0 0 ...
  .. .. .. .. ..@ NAMES          : chr [1:17535] "0610007P14Rik" "0610009B22Rik" "0610009L18Rik" "0610009O20Rik" ...
  .. .. .. .. ..@ elementType    : chr "ANY"
  .. .. .. .. ..@ elementMetadata: NULL
  .. .. .. .. ..@ metadata       : list()
  ..@ colData            :Formal class 'DataFrame' [package "S4Vectors"] with 6 slots
  .. .. ..@ rownames       : chr [1:8981] "AAAAATTCTTAA" "GTAATTTAACGA" "TACAAGTTGATG" "TCAGCAATGACN" ...
  .. .. ..@ nrows          : int 8981
  .. .. ..@ listData       :List of 14
  .. .. .. ..$ orig.ident      : Factor w/ 1 level "full_atlas": 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..$ nCount_RNA      : num [1:8981] 3825 1861 3117 9331 2494 ...
  .. .. .. ..$ nFeature_RNA    : int [1:8981] 1946 1177 1331 3505 1524 2830 2844 3404 1953 1447 ...
  .. .. .. ..$ percent.mt      : num [1:8981] 0 0 0 0 0 0 0 0 0 0 ...
  .. .. .. ..$ RNA_snn_res.0.5 : Factor w/ 8 levels "0","1","2","3",..: 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..$ seurat_clusters : Factor w/ 8 levels "0","1","2","3",..: 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..$ percent.rp      : num [1:8981] 9.961 12.52 0.738 8.606 8.621 ...
  .. .. .. ..$ RNA_snn_res.0.25: Factor w/ 7 levels "0","1","2","3",..: 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..$ S.Score         : num [1:8981] -0.01811 -0.11624 0.00729 0.08427 -0.04092 ...
  .. .. .. ..$ G2M.Score       : num [1:8981] 0.18012 -0.000609 0.048107 0.054149 -0.026457 ...
  .. .. .. ..$ Phase           : Factor w/ 3 levels "G1","G2M","S": 2 1 2 3 1 3 2 1 3 2 ...
  .. .. .. ..$ old.ident       : Factor w/ 7 levels "0","1","2","3",..: 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..$ label           : Factor w/ 7 levels "Tconv1","Tconv3",..: 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..$ ident           : Factor w/ 5 levels "Tconv1","Tconv3",..: 1 1 1 1 1 1 1 1 1 1 ...
  .. .. ..@ elementType    : chr "ANY"
  .. .. ..@ elementMetadata: NULL
  .. .. ..@ metadata       : list()
  ..@ assays             :Reference class 'ShallowSimpleListAssays' [package "SummarizedExperiment"] with 1 field
  .. ..$ data: NULL
  .. ..and 14 methods.
  ..@ NAMES              : NULL
  ..@ elementMetadata    :Formal class 'DataFrame' [package "S4Vectors"] with 6 slots
  .. .. ..@ rownames       : NULL
  .. .. ..@ nrows          : int 17535
  .. .. ..@ listData       : Named list()
  .. .. ..@ elementType    : chr "ANY"
  .. .. ..@ elementMetadata: NULL
  .. .. ..@ metadata       : list()
  ..@ metadata           : list()

Thanks in advance!

kieranrcampbell · 2019-11-29T16:44:45Z

Aha! So if you print assays(test) what does it show? Ouija looks for an assay called logcounts (though you can change this with the single_cell_experiment_assay argument to the ouija function), so by default the SingleCellExperiment you pass must have an assay called logcounts

JihedC · 2019-12-02T08:52:35Z

Sorry for not answering earlier.
assay(test) returns this :

I am not so familiar with SCE object but this looks like a count matrix. Is there a problem with the conversion with Seurat ? I don't see any log counts in this data frame (I am just may be missing it )

kieranrcampbell · 2019-12-02T09:04:51Z

Aha! So just double check that names(assays(test)) returns counts only?

If so, you should be able to call

library(scran)
library(scater)
test <- computeSumFactors(test) # this computes size factors for each cell
test <- normalize(test) # compute log normalized counts

and double check that name(assays(test)) now has a logcounts

JihedC · 2019-12-02T09:37:12Z

Hi Kieran!
Thanks for such a quick reply!

names(assays(test))
[1] "counts"    "logcounts"

The SCE contained already the log counts apparently.

I did run the command you suggested anyway and tried to use ouija like this:

library(ouija)
test_oui <- ouija(test, single_cell_experiment_assay = "logcounts")

Error in t.default(assay(x, single_cell_experiment_assay)) : l'argument n'est pas une matrice

But it still tells me that the argument is not a matrix :(

kieranrcampbell · 2019-12-02T09:38:32Z

Ohhh I think it's because it's saved as a sparse matrix....Ouija was written baack in the days when these weren't a thing. Does

logcounts(test) <- as.matrix(logcounts(test))

fix it?

JihedC · 2019-12-02T09:45:51Z

ah ok!
So I tried :

logcounts(test) <- as.matrix(logcounts(test))
test_oui <- ouija(test, single_cell_experiment_assay = "logcounts")

and I've got this :

Error in svd(x, nu = 0, nv = k) : infinite or missing values in 'x'

kieranrcampbell · 2019-12-02T09:51:59Z

What does summary(colSums(logcounts(test))) look like?

JihedC · 2019-12-02T09:52:42Z

summary(colSums(logcounts(test)))

Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   2041    2662    2916    2914    3161    3974

kieranrcampbell · 2019-12-02T09:54:25Z

Ok I'm stumped -- would you be able to saveRDS(test,...) and email it to me and I'll take a look?

JihedC · 2019-12-02T09:57:54Z

yes sure!
What is the issue with it ?

JihedC · 2019-12-02T10:05:49Z

I have sent it to you via dropbox on the gmail address I found on your cv (I don't want to display it here)

JihedC · 2019-12-02T11:14:55Z

I have tried to work around it a bit by extracting the log count matrix of my genes of interest and adding 0.000001. I have also selected randomly 500 cells among the almost 10000 cells I have in my matrix.
With this matrix the function ouija() worked but I am puzzled by the result I have got :

I don't understand why I am getting such a high values on the y-axis, on your example the values are between 0 and 1.5. Besides in terms of biology, the pseudo-time line should be reverted Bcl11b is a gene that I am expecting expressed "late" in the pseudo time.

kieranrcampbell · 2019-12-10T10:58:34Z

Hi @JihedC

Do you have a list of marker genes? I've had a look at the test object but it appears transcriptome wide

JihedC · 2019-12-10T13:34:02Z

Hi @kieranrcampbell ,
Here is the list of genes:

genes = c("Flt3", "Kit", "Spi1", "Gata3", "Runx1", "Tcf7", "Bcl11b", "Rag1", "Cd4", "Cd8b1", "Cd8a")

JihedC closed this as completed Nov 29, 2019

JihedC reopened this Nov 29, 2019

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Can't load sce data #11

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