Unused argument error when running example code

[vishalmshah]

Hi! I have been attempting to run eskrate with your example data, but I am running into some issues. Most notably, when running the exact code from the readme, I get this error when running the estimateKinetics() function:

Error in estimateKinetics(observedData = observed.data, threadN = 2) : unused argument (observedData = observed.data)

In order to solve this, I have also edited two functions from your code. However, these functions output ridiculous transcription rates, so I am unsure if these are correct.

Here is the code that I am running (straight from the readme):

#devtools::install_github("rajewsky-lab/Eskrate")  

library(tibble)
library(dplyr)
library(magrittr)
library(tidyr)
library(ggplot2)
library(cowplot)
library(Rmpfr)
library(gam)
library(mgcv)
library(foreach)
library(doParallel)
library(Eskrate)

library(Seurat)
library(SeuratData)
library(SeuratDisk)

setwd('/projectnb/velocity/vishalms/')


### cell meta data
cells_info <- readRDS("/data/cells_info.rds")

### gene expression matrix
raw_labeled_mature <- readRDS("./Eskrate/data/raw_counts_labeled_mature.rds")
raw_unlabeled_mature <- readRDS("./Eskrate/data/raw_counts_unlabeled_mature.rds")
raw_labeled_precursor <- readRDS( "./Eskrate/data/raw_counts_labeled_precursor.rds")
raw_unlabeled_precursor <- readRDS("./Eskrate/data/raw_counts_unlabeled_precursor.rds")

observed.data <- 
  getInput(rawCountsLabeledMature = raw_labeled_mature,
           rawCountsUnlabeledMature = raw_unlabeled_mature,
           rawCountsLabeledPrecursor = raw_labeled_precursor,
           rawCountsUnlabeledPrecursor = raw_unlabeled_precursor,
           cells = cells_info,
           labelingTime = 15)

### select two genes (ZNF711, KIF14) for demo
observed.data %<>% 
  filter(gene %in% c("ZNF711", "KIF14")) %>%
  droplevels

data_rates <- 
  estimateKinetics(observedData = observed.data, 
                   threadN = 2)

data_predicted <- 
  getPredictions(dataRates = data_rates, 
                 threadN=2)

p1 <-
  plotMtotalAlphaGamma(df.prediction = predicted.data,   
                       gene.to.plot = "ZNF711",
                       color.alpha = "#D95F02",
                       color.gamma = "#1B9E77",
                       color.expression = "#666666",
                       show.phase.boundaries = FALSE,
                       line.size = 1,
                       font.size = 16)

p2 <-
  plotMtotalAlphaGamma(df.prediction = predicted.data,   
                       gene.to.plot = "KIF14",
                       color.alpha = "#D95F02",
                       color.gamma = "#1B9E77",
                       color.expression = "#666666",
                       show.phase.boundaries = FALSE,
                       line.size = 1,
                       font.size = 16)

plot_grid(p1, p2, ncol=2)

Here is my sessionInfo():

sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: AlmaLinux 8.10 (Cerulean Leopard)

Matrix products: default
BLAS:   /share/pkg.7/r/4.1.2/install/lib64/R/lib/libRblas.so
LAPACK: /share/pkg.7/r/4.1.2/install/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] SeuratDisk_0.0.0.9020 SeuratData_0.2.2      SeuratObject_4.0.4    Seurat_4.1.0          Eskrate_0.1.0        
 [6] doParallel_1.0.16     iterators_1.0.13      mgcv_1.8-38           nlme_3.1-155          gam_1.20             
[11] foreach_1.5.1         Rmpfr_0.8-7           gmp_0.6-2.1           cowplot_1.1.1         ggplot2_3.4.2        
[16] tidyr_1.3.0           magrittr_2.0.3        dplyr_1.1.2           tibble_3.2.1         

loaded via a namespace (and not attached):
 [1] Rtsne_0.16            colorspace_2.1-0      deldir_1.0-9          ellipsis_0.3.2        ggridges_0.5.3       
 [6] rstudioapi_0.13       spatstat.data_3.0-0   leiden_0.3.9          listenv_0.9.0         bit64_4.0.5          
[11] ggrepel_0.9.3         fansi_1.0.4           codetools_0.2-18      polyclip_1.10-0       jsonlite_1.8.5       
[16] ica_1.0-2             cluster_2.1.2         png_0.1-8             uwot_0.1.14           shiny_1.7.1          
[21] sctransform_0.3.3     spatstat.sparse_3.0-0 compiler_4.1.2        httr_1.4.6            Matrix_1.4-1         
[26] fastmap_1.1.1         lazyeval_0.2.2        cli_3.6.1             later_1.3.1           htmltools_0.5.5      
[31] tools_4.1.2           igraph_1.5.0          gtable_0.3.3          glue_1.6.2            RANN_2.6.1           
[36] reshape2_1.4.4        rappdirs_0.3.3        Rcpp_1.0.10           scattermore_0.7       vctrs_0.6.3          
[41] lmtest_0.9-39         stringr_1.5.0         globals_0.16.2        mime_0.12             miniUI_0.1.1.1       
[46] lifecycle_1.0.3       irlba_2.3.5.1         goftest_1.2-3         future_1.32.0         MASS_7.3-55          
[51] zoo_1.8-10            scales_1.2.1          spatstat.core_2.3-2   promises_1.2.0.1      spatstat.utils_3.0-1 
[56] RColorBrewer_1.1-3    reticulate_1.30       pbapply_1.5-0         gridExtra_2.3         rpart_4.1.16         
[61] stringi_1.7.12        rlang_1.1.1           pkgconfig_2.0.3       matrixStats_1.0.0     lattice_0.20-45      
[66] ROCR_1.0-11           purrr_1.0.1           tensor_1.5            patchwork_1.1.1       htmlwidgets_1.6.2    
[71] bit_4.0.4             tidyselect_1.2.0      parallelly_1.36.0     RcppAnnoy_0.0.20      plyr_1.8.8           
[76] R6_2.5.1              generics_0.1.3        DBI_1.1.2             pillar_1.9.0          withr_2.5.0          
[81] fitdistrplus_1.1-6    survival_3.2-13       abind_1.4-7           future.apply_1.11.0   hdf5r_1.3.5          
[86] crayon_1.4.2          KernSmooth_2.23-20    utf8_1.2.3            spatstat.geom_3.0-3   plotly_4.10.2        
[91] grid_4.1.2            data.table_1.14.8     digest_0.6.31         xtable_1.8-6          httpuv_1.6.5         
[96] munsell_0.5.0         viridisLite_0.4.2     Revelio_0.1.0