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The binning of data based on feature means is incorrect in FindVariableFeatures. The binning produced will always place the feature with the minimum mean in the first bin and only that feature. The remaining n - 1 features will then be distributed across the remaining bins. This results in that bin not having a valid dispersion value, resulting in a scaled dispersion value of NA, and of course all of the other bins are compromised as there are features that should be in bin 1 scattered about.
The fix for this is quite simple. The code in preprocessing.R should be:
I have included a simple example to demonstrate this issue using SeuratData:
# Here is example demonstrating issue
data("pbmc3k")
variable_features<- FindVariableFeatures(pbmc_small, selection.method="mvp", mean.cutoff= c(-Inf, Inf), dispersion.cutoff= c(-Inf, Inf), binning.method="equal_frequency")
summary(variable_features@assays$RNA@meta.features$mvp.dispersion.scaled)
# Output from summary:# Min. 1st Qu. Median Mean 3rd Qu. Max. NA's #-1.7211 -0.7458 -0.1070 0.0000 0.5901 2.8493 1
Session Info:
> sessioninfo()
Error in sessioninfo() : could not find function "sessioninfo"
> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
The binning of data based on feature means is incorrect in FindVariableFeatures. The binning produced will always place the feature with the minimum mean in the first bin and only that feature. The remaining n - 1 features will then be distributed across the remaining bins. This results in that bin not having a valid dispersion value, resulting in a scaled dispersion value of NA, and of course all of the other bins are compromised as there are features that should be in bin 1 scattered about.
The fix for this is quite simple. The code in preprocessing.R should be:
I have included a simple example to demonstrate this issue using SeuratData:
Session Info:
> sessioninfo()
Error in sessioninfo() : could not find function "sessioninfo"
> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] pbmc3k.SeuratData_3.1.4 SeuratData_0.2.1 devtools_2.4.2 usethis_2.0.1
[5] matrixStats_0.59.0 dplyr_1.0.6 SeuratObject_4.0.1 Seurat_4.0.2
loaded via a namespace (and not attached):
[1] Rtsne_0.15 colorspace_2.0-1 deldir_0.2-10 ellipsis_0.3.2
[5] ggridges_0.5.3 rprojroot_2.0.2 fs_1.5.0 rstudioapi_0.13
[9] spatstat.data_2.1-0 leiden_0.3.8 listenv_0.8.0 remotes_2.4.0
[13] ggrepel_0.9.1 fansi_0.5.0 codetools_0.2-18 splines_4.1.0
[17] cachem_1.0.5 polyclip_1.10-0 pkgload_1.2.1 jsonlite_1.7.2
[21] ica_1.0-2 cluster_2.1.2 png_0.1-7 uwot_0.1.10
[25] shiny_1.6.0 sctransform_0.3.2 spatstat.sparse_2.0-0 compiler_4.1.0
[29] httr_1.4.2 Matrix_1.3-3 fastmap_1.1.0 lazyeval_0.2.2
[33] cli_2.5.0 later_1.2.0 htmltools_0.5.1.1 prettyunits_1.1.1
[37] tools_4.1.0 igraph_1.2.6 gtable_0.3.0 glue_1.4.2
[41] RANN_2.6.1 reshape2_1.4.4 rappdirs_0.3.3 Rcpp_1.0.6
[45] scattermore_0.7 vctrs_0.3.8 nlme_3.1-152 lmtest_0.9-38
[49] stringr_1.4.0 globals_0.14.0 ps_1.6.0 testthat_3.0.3
[53] mime_0.10 miniUI_0.1.1.1 lifecycle_1.0.0 irlba_2.3.3
[57] goftest_1.2-2 future_1.21.0 MASS_7.3-54 zoo_1.8-9
[61] scales_1.1.1 spatstat.core_2.1-2 promises_1.2.0.1 spatstat.utils_2.1-0
[65] parallel_4.1.0 RColorBrewer_1.1-2 curl_4.3.2 memoise_2.0.0
[69] reticulate_1.20 pbapply_1.4-3 gridExtra_2.3 ggplot2_3.3.3
[73] rpart_4.1-15 stringi_1.6.1 desc_1.3.0 pkgbuild_1.2.0
[77] rlang_0.4.11 pkgconfig_2.0.3 lattice_0.20-44 ROCR_1.0-11
[81] purrr_0.3.4 tensor_1.5 patchwork_1.1.1 htmlwidgets_1.5.3
[85] cowplot_1.1.1 tidyselect_1.1.1 processx_3.5.2 parallelly_1.26.0
[89] RcppAnnoy_0.0.18 plyr_1.8.6 magrittr_2.0.1 R6_2.5.0
[93] generics_0.1.0 pillar_1.6.1 withr_2.4.2 mgcv_1.8-35
[97] fitdistrplus_1.1-5 survival_3.2-11 abind_1.4-5 tibble_3.1.2
[101] future.apply_1.7.0 crayon_1.4.1 KernSmooth_2.23-20 utf8_1.2.1
[105] spatstat.geom_2.1-0 plotly_4.9.4 grid_4.1.0 data.table_1.14.0
[109] callr_3.7.0 digest_0.6.27 xtable_1.8-4 tidyr_1.1.3
[113] httpuv_1.6.1 munsell_0.5.0 viridisLite_0.4.0 sessioninfo_1.1.1
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