CRAN Package Check Results for Package PRECAST

Last updated on 2025-12-14 00:50:32 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.7 138.60 531.33 669.93 OK
r-devel-linux-x86_64-debian-gcc 1.7 92.00 374.22 466.22 ERROR
r-devel-linux-x86_64-fedora-clang 1.7 281.00 868.96 1149.96 ERROR
r-devel-linux-x86_64-fedora-gcc 1.7 205.00 451.32 656.32 ERROR
r-devel-windows-x86_64 1.7 160.00 472.00 632.00 OK
r-patched-linux-x86_64 1.7 142.68 507.54 650.22 OK
r-release-linux-x86_64 1.7 140.75 496.59 637.34 ERROR
r-release-macos-arm64 1.7 OK
r-release-macos-x86_64 1.7 89.00 271.00 360.00 OK
r-release-windows-x86_64 1.7 156.00 469.00 625.00 OK
r-oldrel-macos-arm64 1.7 NOTE
r-oldrel-macos-x86_64 1.7 91.00 305.00 396.00 NOTE
r-oldrel-windows-x86_64 1.7 183.00 626.00 809.00 OK

Check Details

Version: 1.7
Check: examples
Result: ERROR Running examples in ‘PRECAST-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: CreatePRECASTObject > ### Title: Create the PRECAST object with preprocessing step. > ### Aliases: CreatePRECASTObject > > ### ** Examples > > data(PRECASTObj) > library(Seurat) Loading required package: SeuratObject Loading required package: sp Attaching package: ‘SeuratObject’ The following objects are masked from ‘package:base’: intersect, t > seuList <- PRECASTObj@seulist > ## Check the input of seuList for create PRECAST object. > ## Check the default assay for each data batch > lapply(seuList, DefaultAssay) [[1]] [1] "RNA" [[2]] [1] "RNA" > ## Check the spatial coordinates in the meta data named "row" and "col". > head(seuList[[1]]@meta.data) orig.ident nCount_RNA nFeature_RNA row col true_cluster cell1_1 cell1 10004 55 1 1 2 cell1_2 cell1 12614 54 2 1 2 cell1_3 cell1 18233 57 3 1 2 cell1_4 cell1 1726 50 4 1 7 cell1_5 cell1 3451 53 5 1 7 cell1_6 cell1 134457 60 6 1 6 > ## Then create PRECAST object using this seuList. > ## For convenience, we show the user-specified genes' list for creating PRECAST object. > ## Users can use SVGs from SPARK-X or HVGs. > PRECASTObj2 <- CreatePRECASTObject(seuList, + customGenelist= row.names(seuList[[1]]), verbose=FALSE) Error in FUN(X[[i]], ...) : filter_gene: Seuat object must provide slots count or data in assay! Calls: CreatePRECASTObject -> <Anonymous> -> lapply -> FUN Execution halted Flavors: r-devel-linux-x86_64-debian-gcc, r-release-linux-x86_64

Version: 1.7
Check: examples
Result: ERROR Running examples in ‘PRECAST-Ex.R’ failed The error most likely occurred in: > ### Name: CreatePRECASTObject > ### Title: Create the PRECAST object with preprocessing step. > ### Aliases: CreatePRECASTObject > > ### ** Examples > > data(PRECASTObj) > library(Seurat) Loading required package: SeuratObject Loading required package: sp Attaching package: ‘SeuratObject’ The following objects are masked from ‘package:base’: intersect, t > seuList <- PRECASTObj@seulist > ## Check the input of seuList for create PRECAST object. > ## Check the default assay for each data batch > lapply(seuList, DefaultAssay) [[1]] [1] "RNA" [[2]] [1] "RNA" > ## Check the spatial coordinates in the meta data named "row" and "col". > head(seuList[[1]]@meta.data) orig.ident nCount_RNA nFeature_RNA row col true_cluster cell1_1 cell1 10004 55 1 1 2 cell1_2 cell1 12614 54 2 1 2 cell1_3 cell1 18233 57 3 1 2 cell1_4 cell1 1726 50 4 1 7 cell1_5 cell1 3451 53 5 1 7 cell1_6 cell1 134457 60 6 1 6 > ## Then create PRECAST object using this seuList. > ## For convenience, we show the user-specified genes' list for creating PRECAST object. > ## Users can use SVGs from SPARK-X or HVGs. > PRECASTObj2 <- CreatePRECASTObject(seuList, + customGenelist= row.names(seuList[[1]]), verbose=FALSE) Error in FUN(X[[i]], ...) : filter_gene: Seuat object must provide slots count or data in assay! Calls: CreatePRECASTObject -> <Anonymous> -> lapply -> FUN Execution halted Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 1.7
Check: installed package size
Result: NOTE installed size is 11.8Mb sub-directories of 1Mb or more: data 2.2Mb libs 8.8Mb Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64