jefworks-lab / meringue Goto Github PK

Installation failed using
remotes::install_github('JEFworks-Lab/MERINGUE', build_vignettes = TRUE)

Error: Failed to install 'MERINGUE' from GitHub:
System command 'Rcmd.exe' failed, exit status: 1, stdout + stderr (last 10 lines):
E> C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5[ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5]+0x293): undefined reference to dgemm_' E> C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_[_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_]+0x627): undefined reference to dgemv_'
E> C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$_ZN4arma10glue_times5applyIdLb0

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 LC_MONETARY=English_United States.1252 LC_NUMERIC=C LC_TIME=English_United States.1252

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

loaded via a namespace (and not attached):
[1] processx_3.5.2 compiler_4.1.0 R6_2.5.0 rprojroot_2.0.2 cli_2.5.0 prettyunits_1.1.1 tools_4.1.0 withr_2.4.2 rstudioapi_0.13 curl_4.3.1 crayon_1.4.1
[12] remotes_2.4.0 callr_3.7.0 ps_1.6.0 pkgbuild_1.2.0

Hello!

I've been trying to install Meringue but am coming across this error:

Any help would be appreciated. Thanks in advance!

Hi Jean and team,

Thanks for making this cool work available! I am working through your spatially-informed clustering tutorial, and I am not getting the expected results when I run the clustering, but everything before this step matches your tutorial outputs.

W <- getSpatialNeighbors(pos, filterDist = 2)
plotNetwork(pos, W)
com2 <- getSpatiallyInformedClusters(pcs, W=W, k=50)
table(com2)
plotEmbedding(pos, groups=com2, main='Spatially Aware Transcriptional Clusters', xlab='Spatial X', ylab='Spatial Y')

I am just copying and pasting code exactly from your tutorial.

If I reduce the k from 50 to 14, I can get 3 clusters but they are not spatially distinct

Below is my session info. Thanks for any help!! Best- Orr

> sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

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

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

other attached packages:
[1] uwot_0.1.10  Matrix_1.3-4 MERINGUE_1.0

loaded via a namespace (and not attached):
 [1] mclust_5.4.7          ggrepel_0.9.1         Rcpp_1.0.7            riverplot_0.10       
 [5] lattice_0.20-45       ica_1.0-2             tidyr_1.1.4           FNN_1.1.3            
 [9] assertthat_0.2.1      digest_0.6.28         foreach_1.5.1         utf8_1.2.2           
[13] R6_2.5.1              plyr_1.8.6            magic_1.5-9           dynamicTreeCut_1.63-1
[17] evaluate_0.14         httr_1.4.2            ggplot2_3.3.5         pillar_1.6.3         
[21] rlang_0.4.12          irlba_2.3.3           hdf5r_1.3.4           rmarkdown_2.11       
[25] splines_4.0.3         Rtsne_0.15            rliger_1.0.0          igraph_1.2.7         
[29] bit_4.0.4             munsell_0.5.0         tinytex_0.34          compiler_4.0.3       
[33] xfun_0.26             pkgconfig_2.0.3       mgcv_1.8-37           htmltools_0.5.2      
[37] tidyselect_1.1.1      tibble_3.1.5          RANN_2.6.1            codetools_0.2-18     
[41] fansi_0.5.0           crayon_1.4.1          dplyr_1.0.7           grid_4.0.3           
[45] nlme_3.1-153          gtable_0.3.0          lifecycle_1.0.1       DBI_1.1.1            
[49] magrittr_2.0.1        scales_1.1.1          remotes_2.4.1         sp_1.4-5             
[53] doParallel_1.0.16     akima_0.6-2.2         geometry_0.4.5        ellipsis_0.3.2       
[57] generics_0.1.0        vctrs_0.3.8           cowplot_1.1.1         RColorBrewer_1.1-2   
[61] iterators_1.0.13      tools_4.0.3           bit64_4.0.5           glue_1.4.2           
[65] purrr_0.3.4           abind_1.4-5           parallel_4.0.3        fastmap_1.1.0        
[69] yaml_2.2.1            colorspace_2.0-2      knitr_1.36            patchwork_1.1.1      

Hello Jean & team,

I have 10x Visium Spatially resolved RNA seq dataset analyzed with Seurat and would like to try Meringue to compute spatial correlation test across spatial spots with cell type names present in metadata slots.
Is there any good or easy way to convert this object to Meringue compatible format?
Thanks in advance!

Hello,

I heard that Meringue was used to compute the correlation between genes in the Visium 10XGenomics public datasets posted on their website (https://www.10xgenomics.com/resources/datasets). Is that right? Is that information available somewhere?

Thank you

Hi Jean and team,

Thanks for your work! I'm wondering if I can use MERINGUE with multicore properly. I'd like to compare the computational effeiciency of MERINGUE with other approaches.

Thanks in advance!

Hello,

I am using human lymph node data from 10x visium spatial transcriptomics data set. Also, I am little new to coding. I was trying to understand the package STdeconvolve using your youtube tutorial. However, my picture of the dataset generated using MERINGUE looked flipped and rotated and some areas seemed to get cut off. I am attaching both images below for your reference.
I tried changing parameters of parmfrow and using the following code however I was not succesful. Could you help me with understanding how to rotate and get the full image.
pdf("output_plot.pdf", width = 8, height = 10)
par(mfrow = c(1, 1), mar = c(2, 2, 2, 2))
Thank you so much for your help! Kindly let me know if you need more information.

Image of HE section

Rstudio plot

Hi MERINGUE team,
I encountered the following issue when running a demo Vizgen data. Can you help? Thanks.

Fan

suppressMessages(library(MERINGUE))

data_path<-"/home/fgao/Data_vizgen/"
mtx_BC<-read.csv(paste(data_path, "datasets_mouse_brain_map_BrainReceptorShowcase_Slice1_Replicate1_cell_by_gene_S1R1.csv", sep=""), header=T, row.names=1)
rownames(mtx_BC)<-as.factor(rownames(mtx_BC))
mtx_BC[is.na(mtx_BC)] <- 0

meta_BC<-read.csv(paste(data_path, "datasets_mouse_brain_map_BrainReceptorShowcase_Slice1_Replicate1_cell_metadata_S1R1.csv", sep=""), header=T, row.names=1)
rownames(meta_BC)<-rownames(mtx_BC)

counts_BC<-t(mtx_BC[, 1:483])
#filter out genes with less than 1000 counts across all cells and cells with less than 100 total counts
cc <- cleanCounts(counts_BC, min.reads = 1000, min.lib.size = 100, plot=TRUE)

#CPM normalization
mat <- normalizeCounts(cc, log=FALSE, verbose=TRUE)
#Normalized matrix has 67576 cells and 382 genes.

pos_BC<-meta_BC[,c("center_x", "center_y")]
colnames(pos_BC)<-c("x", "y")
pos_BC$slice<-1
  
pos_mat_BC <- pos_BC[intersect(rownames(pos_BC), colnames(mat)),]

#Get neighbor-relationship

w <- getSpatialNeighbors(pos_mat_BC, filterDist = 2.5)

Got the following error message when running getSpatialNeighbors

Error: cons memory exhausted (limit reached?)
Error during wrapup: cons memory exhausted (limit reached?)
Error: no more error handlers available (recursive errors?); invoking 'abort' restart

Dear author,
Thank you for providing these fantastic tools.

I am currently seeking assistance with utilizing the tool to calculate the correlation between genes using my VIsium data. It appears that the 'spatialCrossCorMatrix' function is capable of returning correlation coefficients. However, I am unsure about how to obtain p-values for the test at this particular stage.

Your guidance on this matter would be greatly appreciated.

Thank you,
Jihyun.

Hello Jean and team,

Thank you for all your previous help. I'm writing to ask if there's a good way to identify a filterDist value within getSpatialNeighbors. Are there specific characteristics to look in the plots generated by getSpatialNeighbors?

Thank you in advance!

Hi,
Wonderful job!

I have searched through many articles and am looking for a Shiny app that can handle spatial transcriptomics data in a similar manner to how Shinycell handles single-cell transcriptomics data.

However, currently, there is no R package available that fulfills this requirement.

However, I noticed that there is a function called makeApp in your R package that seems to be able to achieve this functionality.
Since I am only familiar with using the Seurat package for spatial transcriptomics data analysis, would you be able to create an interface for the Seurat package so that Seurat objects can be used with makeApp to create Shiny apps? With the increasing depth of research in spatial transcriptomics, I believe this feature would greatly advance the field. Looking forward to your response.
Best,
Young

Dear JEFworks team,

Thank you very much for the great package.

As described in #15 , the first part of the pipeline to detect spatial patterns can be parallelized. Since the downstream steps such as filterSpatialPatterns and spatialCrossCorMatrix do not work genewise, I expect the mentioned block-wise processing of gene groups cannot be applied here.
Could you think of another way to parallelize these downstream steps?
I am currently working on a dataset with ~25.000 spots and 7.000 genes.

Thank you in advance,
Best,

Christoph

Hi,

I can't install on windows, I get the following error during compilation:

* installing *source* package 'MERINGUE' ...
** using staged installation
** libs
"C:/rtools40/mingw64/bin/"g++ -std=gnu++11  -I"C:/Users/RICARD~1.GUE/DOCUME~1/R/R-41~1.1/include" -DNDEBUG  -I'C:/Users/ricardo.guerreiro/Documents/R/R-4.1.1/library/Rcpp/include' -I'C:/Users/ricardo.guerreiro/Documents/R/R-4.1.1/library/RcppArmadillo/include' -I'C:/Users/ricardo.guerreiro/Documents/R/R-4.1.1/library/RcppProgress/include'        -O2 -Wall  -mfpmath=sse -msse2 -mstackrealign  -c RcppExports.cpp -o RcppExports.o
"C:/rtools40/mingw64/bin/"g++ -std=gnu++11  -I"C:/Users/RICARD~1.GUE/DOCUME~1/R/R-41~1.1/include" -DNDEBUG  -I'C:/Users/ricardo.guerreiro/Documents/R/R-4.1.1/library/Rcpp/include' -I'C:/Users/ricardo.guerreiro/Documents/R/R-4.1.1/library/RcppArmadillo/include' -I'C:/Users/ricardo.guerreiro/Documents/R/R-4.1.1/library/RcppProgress/include'        -O2 -Wall  -mfpmath=sse -msse2 -mstackrealign  -c functions.cpp -o functions.o
C:/rtools40/mingw64/bin/g++ -std=gnu++11 -shared -s -static-libgcc -o MERINGUE.dll tmp.def RcppExports.o functions.o -LC:/Users/RICARD~1.GUE/DOCUME~1/R/R-41~1.1/bin/x64 -lR
C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_[_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_]+0x293): undefined reference to `dgemm_'
C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_[_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_]+0x627): undefined reference to `dgemv_'
C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_[_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_]+0x6f2): undefined reference to `dgemv_'
C:/rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: functions.o:functions.cpp:(.text$_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_[_ZN4arma10glue_times5applyIdLb0ELb1ELb0ENS_3ColIdEES3_EEvRNS_3MatIT_EERKT3_RKT4_S5_]+0x91a): undefined reference to `dsyrk_'
collect2.exe: error: ld returned 1 exit status
no DLL was created
ERROR: compilation failed for package 'MERINGUE'

Running this as you suggest:

install.packages("remotes")
require(remotes)
remotes::install_github('JEFworks-Lab/MERINGUE', build_vignettes = TRUE)

Do I have missing dependencies? I don't see a list of requirements

Cheers,

dear @JEFworks and @bmill3r :
I tried to install MERINGUE, though I installed lapack.so and blas.so, I still failed to install MERINGUE. So now I don't know what to do, begging for your generous help, plz.
`> install.packages("~/MERINGUE-master", repos = NULL, type = "source")
Installing package into ‘/home/hxh/R/x86_64-pc-linux-gnu-library/4.1’
(as ‘lib’ is unspecified)

• installing source package ‘MERINGUE’ ...
  ** using staged installation
  ** libs
  g++ -std=gnu++14 -shared -L/usr/lib/R/lib -Wl,-Bsymbolic-functions -flto=auto -ffat-lto-objects -flto=auto -Wl,-z,relro -o MERINGUE.so RcppExports.o functions.o -L/usr/lib/R/lib -lR
  RcppExports.o: file not recognized: file format not recognized
  collect2: error: ld returned 1 exit status
  make: *** [/usr/share/R/share/make/shlib.mk:10: MERINGUE.so] Error 1
  ERROR: compilation failed for package ‘MERINGUE’
• removing ‘/home/hxh/R/x86_64-pc-linux-gnu-library/4.1/MERINGUE’
  Warning in install.packages :
  installation of package ‘/home/hxh/MERINGUE-master’ had non-zero exit status`