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R toolkit for single cell genomics
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VlnPlot fails if one of the categories have too many NAs #8305

Open vertesy opened 10 months ago

vertesy commented 10 months ago

I use VlnPlot to for a feature that has NA-s. All datasets have NA-s in features, but it fails on the last one. 

Error in if (all(data[, feature] == data[, feature][1])) { : 
  missing value where TRUE/FALSE needed
In addition: Warning message:
Removing 1782 cells missing data for vars requested

I reproduced the issue in a fresh session. You can see that VlnPlot succeeds at 55% NA values [[2]] but fails at 80% NA [[4]]. Sorry for no reprex. Don't need to fix it just wanted to report it. (Workaround na_replace in wrapper)

%NA-s in features per split.by :

lapply(ls.obj, function(obj) {
  obj@meta.data %>%
    group_by(my_splitby) %>%
    summarise(PercentageNA = sum(is.na(my_feature / n() * 100)
})

$obj1
# A tibble: 4 × 2
  Genotype.orig      PercentageNA
  <chr>                     <dbl>
1 GT1                         7.77
2 GT2                        3.14
3 doubletsc               3.5 
4 unassignedsc         4   

$obj2
# A tibble: 5 × 2
  Genotype.orig      PercentageNA
  <chr>                     <dbl>
1 GT1                         56.0
2 GT2                        42.3
3 GT3                        46.4
4 doubletsc               50  
5 unassignedsc         41.2

$obj3
# A tibble: 4 × 2
  Genotype.orig      PercentageNA
  <chr>                     <dbl>
1 GT1                       15.0 
2 GT2                       4.42
3 doubletsc             10   
4 unassignedsc        5   

$obj4
# A tibble: 4 × 2
  Genotype.orig      PercentageNA
  <chr>                     <dbl>
1 GT1                        86.3
2 GT2                       35.9
3 doubletsc              23.1
4 unassignedsc        67.7

session_info() ─ Session info ────────────────────────────────────────────────── setting value version R version 4.3.0 (2023-04-21) os CentOS Linux 7 (Core) system x86_64, linux-gnu ui RStudio language (EN) collate en_US.UTF-8 ctype en_US.UTF-8 tz Europe/Vienna date 2024-01-11 rstudio 2023.09.1+494.pro2 Desert Sunflower (server) pandoc 3.1.1 @ /software/system/rstudio/rstudio-server-2023.09.1/bin/quarto/bin/tools/ (via rmarkdown)

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[1] /users/abel.vertesy/R/x86_64-pc-linux-gnu-library/4.3 [2] /software/f2022/software/r-bundle-bioconductor/3.17-foss-2022b-r-4.3.0 [3] /software/f2022/software/arrow-r/12.0.0-foss-2022b-r-4.3.0 [4] /software/f2022/software/r/4.3.0-foss-2022b/lib64/R/library

V ── Loaded and on-disk version mismatch. P ── Loaded and on-disk path mismatch.

vertesy commented 10 months ago

I did not trace it down, but it can be that its not the %NA but the absolute number of non-NA values per category that matter.

>     (NrCellsByGenotype <- lapply(ls.Seurat, function(obj) {
+       obj@meta.data %>%
+         group_by(my_splitby) %>%
+         summarise(nr.cells = length(my_feature))
+     }))

$sc06.692
# A tibble: 4 × 2
  Genotype.orig      nr.cells
  <chr>                 <int>
1 GT1                    2046
2 GT2                     4901
3 doubletsc               200
4 unassigned                25

$sc06.693
# A tibble: 5 × 2
  Genotype.orig      nr.cells
  <chr>                 <int>
1 GT1                     243
2 GT2                     2912
3 GT3                179
4 doubletsc                26
5 unassigned                17

$sc08.325
# A tibble: 4 × 2
  Genotype.orig      nr.cells
  <chr>                 <int>
1 GT1                     381
2 GT2                     4978
3 doubletsc                20
4 unassigned                20

$sc08.327
# A tibble: 4 × 2
  Genotype.orig      nr.cells
  <chr>                 <int>
1 GT1                     431
2 TSC2.p5                3268
3 doubletsc                13
4 unassigned               344
zskylarli commented 10 months ago

Hi - thank you for reporting this! We will look into this ASAP since this seems to be an overlooked edge case.