chenweiyan / landscent Goto Github PK

Hi Weiyan,

Thank you so much for previous help! Now the whole thing is working for me.
I was just wondering whether there is the possibility to colour the dots according to phenotype information when doing the DiffusionMap?
I haven't found any solution so far.

Best regards,
Katharina

Dear Chen Weiyan,

I deeply admire your groups research work and really appreciate that you wrote this awesome R package! (Although I would have preferred a python package, but that's a matter of taste.)

I don't know if it matters for calculation, but I realized that your ppi matrix files contain duplicate rows and columns.

• net13Jun12.m has shape (8434, 8434), though would have shape (7887,7885).
• net17Jan16.m has shape (11751,11751), though would have shape (10653,10653).

I attached tab separated value files with dropped duplicated rows. Maybe they are useful.
net13Jun2012.entrez.m.tsv.gz
net17Jan2016.entrez.m.tsv.gz

Best, Elmar Bucher

Seurat object how to switch to a singlecellexperiment matrix to use LandSCENT?and I wonder the time about running time in 10000 cells conditions? THANKS

Hi,

I was able to run through the demo smoothly. I'm now trying a subset of my own data (SmartSeq2, about 900 cells). I'm using the SingleCellExperiment class with gene symbols. I was able to obtain the EntrezIDs through mapIds feature of AnnotationDbi. So I ultimately had EntrezIDs as row names (features/genes), and cell names as columns in my sce, which also contained additional metadata.

I'm looking to use the PPI network provided within the package, so both are loaded:
data(net13Jun12.m)
data(net17Jan16.m)

My data is in sce, when I try running the following:
Integration.l <- DoIntegPPI(exp.m = sce, ppiA.m = net17Jan16.m, log_trans = FALSE)
I get:

Error in DoIntegPPI(exp.m = sce, ppiA.m = net17Jan16.m, log_trans = FALSE) : 
  scRNA-seq data should have the same gene identifier with the network!

I get the same error with net13Jun12.m and when I try to use a matrix of either counts, normcounts, or logcounts all extracted from sce.

Here are the first 5x5 of my data:

                A1               A3              A4                   A5              A6
14679     0.00               0              0                   0.00           57.15
12544    55.97               0              0                   0.00            0.00
14955     0.00               0              0                   0.00            0.00
107815    0.00               0              0                   0.00            0.00
67608     0.00               0              0                   3.23           46.02

Any help would be appreciated. Thank you.

Hi @ChenWeiyan, thanks for the great package. I am following the tutorial and I'm getting at error message at the InferLandmark() step. The error is as follows:

InferLandmark.o <- InferLandmark(InferPotency.o, pheno.v = data.sce$orig.ident, reduceMethod = "PCA", clusterMethod = "PAM",k_pam = 2)
[1] "Now estimating number of significant components of variation in scRNA-Seq data"
[1] "Centering and scaling matrix"
[1] "Done, now performing SVD"
[1] "Performing full SVD since dimensionality of data matrix is not big"
[1] "Done"
[1] "Number of significant components = 1"
[1] "Do dimension reduction via PCA"
Error in svd.o$v[, 1:2] : subscript out of bounds

How can I fix this ? Thanks in advance for your help.

Hi,

Thank you for the amazing tool. I have found great results with it so far. I wish to compare the SR values with different datasets.

Do I need to combine dataset A and B into a single object and then perform analysis? Or do I keep them separately and only need to compare the resulting normalized SR/MaxSR from either dataset?

Is the MaxSR specific to the analysis for a single dataset?

Thanks,
Danh

Used in version R-4.3.2，While running

SR.o <- CompSRana(Integration.l, local = TRUE, mc.cores = 8)

Windows does not support 'mc.cores' > 1

Is it possible for me to use 8 cores for me to run the programe?

Hi Weiyan,

Thank you for a great package. I'm trying to analyze about 53k cells. Basically, I'm using the seurat object and convert to the SingleCellExperiment object.

1. I succeeded to plot LandSR.total as tutorial, but CellSR.o didn't show the tsne like below.
   

2. When I calculated the DoDiffusionMap.o, the DoDiffusionMap.o$root was null so I cannot do following processes.

DoDiffusionMap.o <- DoDiffusionMap(Integration.l,
                                   mean_gap = 1, sd_gap = 1,
                                   root = c("cell", "state"),
                                   num_comp = 3,
                                   k = 30)

DoDiffusionMap didn't cause errors, but when I tried to Plot_DiffusionMap, the error happened like below.

Plot_DiffusionMap(DoDiffusionMap.o,TIPs = c(1,2,3),
                 dim = c(1, 2, 3),
                  color_by = "SR",
                  phi = 40,
                  theta = 135,
                  bty = "g",
                  PDF = FALSE)

Error message is

Error in destiny::DPT(dm, tips = Integration.l$root): you need to specify 1-3 tips, got 0
Traceback:

1. Plot_DiffusionMap(DoDiffusionMap.o, TIPs = c(1, 2, 3), dim = c(1, 
 .     2, 3), color_by = "SR", phi = 40, theta = 135, bty = "g", 
 .     PDF = FALSE)
2. destiny::DPT(dm, tips = Integration.l$root)
3. stop("you need to specify 1-3 tips, got ", length(tips))

Any help would be appreciated. Thank you.

Hi,
I am running LandSCENT on a dataset of 5000 cells and the command CompSRana takes ages to run on a HP Z800 workstation with 10 cores assigned ... Is it normal ? how can I improve it in order to rerun some features or even bigger datasets?
By the way the results are great !
Thanks.
Jaime.

Thanks for your tool.
When I applied the tool to my data, the SR for about 1/3 of cells is NULL.

I try several times to install the package on R or Studio but i couldn't. In RStudio
Version 1.3.1093 and R 4.0.3
The i try to install it by downloading the zip file and install from file but unfortunately give me below error :
error 1 in extracting from zip file
Warning in install.packages :
cannot open compressed file 'excess_pi_covid-master/DESCRIPTION', probable reason 'No such file or directory'
Error in install.packages : cannot open the connection

please show me a simple way to use the package
Thanks

Hi,

I am trying to install LandSCENT via if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools") devtools::install_github("ChenWeiyan/LandSCENT")
But I met this error:
Error: Failed to install 'unknown package' from GitHub: Failed to connect to api.github.com port 443: Connection refused

Here are my sessionInfo():
`R version 3.6.0 (2019-04-26)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.15.3

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

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

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

other attached packages:
[1] devtools_2.2.2 usethis_1.5.1

loaded via a namespace (and not attached):
[1] Rcpp_1.0.1 magrittr_1.5 uuid_0.1-4 pkgload_1.0.2
[5] R6_2.4.0 rlang_0.4.5 tools_3.6.0 pkgbuild_1.0.6
[9] sessioninfo_1.1.1 cli_1.1.0 withr_2.1.2 htmltools_0.4.0
[13] ellipsis_0.3.0 remotes_2.1.1 assertthat_0.2.1 digest_0.6.25
[17] rprojroot_1.3-2 crayon_1.3.4 processx_3.4.2 IRdisplay_0.7.0
[21] repr_1.1.0 callr_3.4.2 base64enc_0.1-3 fs_1.3.1
[25] ps_1.3.2 IRkernel_1.1 curl_4.3 testthat_2.3.2
[29] evaluate_0.14 memoise_1.1.0 glue_1.3.1 pbdZMQ_0.3-3
[33] pillar_1.4.2 compiler_3.6.0 desc_1.2.0 backports_1.1.4
[37] prettyunits_1.1.1 jsonlite_1.6.1 `

Hello, maybe I missed it but how do you install the package?

Hi Weiyan,
I am trying to run a dataset of 13 000 cells in a cluster, assigning 200 cores and 1TB of memory and it is not enough still ... Is this normal ?? Could you specify the characteristics of the machine you ran those 100k cells ?
Thanks in advance.
Best, Jaime.

Hi Weiyan,

Thank you for a great package. I'm trying to analyze about 8k cells. Basically, I'm using the Seurat object and converting to the SingleCellExperiment object. I am following the tutorial and able to calculate "SR.o" . When I am trying to plot the box plot then I am getting following error.

boxplot(SR.o$SR ~ my.data$type, main = "SR values against cell types", xlab = "Cell Types", ylab = "SR values")
Error in stats::model.frame.default(formula = SR.o$SR ~ my.data$type) :
invalid type (list) for variable 'SR.o$SR'

My SR.o$SR looks like

SR.o$SR
:[[997]]
[1] 0.8880284
[[998]]
[1] 0.874321
[[999]]
NULL
[[1000]]
NULL
[ reached getOption("max.print") -- omitted 7607 entries ]

and my.data$type looks like:

my.data$type
[993] "noninf" "noninf" "noninf" "noninf" "noninf" "noninf" "noninf" "noninf"
[ reached getOption("max.print") -- omitted 7607 entries ]

I tried to check SR using following command

anyNA(SR.o$SR)
[1] FALSE

I also tried to calculate InferPotency and getting following error:

InferPotency.o <- InferPotency(SR.o, pheno.v = my.data$type)
[1] "Fit Gaussian Mixture Model to Signaling Entropies"
Error in 1 - sr.v : non-numeric argument to binary operator

Any help would be highly appreciated.
Thank you.

Hi Chen,

I am trying to install LandSCENT via GitHub

My sessioninfo():
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding

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

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

other attached packages:
[1] swirl_2.4.5 igraph_1.2.6 paxtoolsr_1.22.0 XML_3.99-0.5 rJava_0.9-13

loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 pillar_1.4.7 compiler_4.0.3 plyr_1.8.6 R.methodsS3_1.8.1 R.utils_2.10.1
[7] bitops_1.0-6 tools_4.0.3 testthat_3.0.0 digest_0.6.27 jsonlite_1.7.1 lifecycle_0.2.0
[13] tibble_3.0.4 pkgconfig_2.0.3 rlang_0.4.8 cli_2.2.0 rstudioapi_0.13 curl_4.3
[19] yaml_2.2.1 httr_1.4.2 stringr_1.4.0 vctrs_0.3.5 hms_0.5.3 glue_1.4.2
[25] R6_2.5.0 fansi_0.4.1 readr_1.4.0 magrittr_2.0.1 ellipsis_0.3.1 assertthat_0.2.1
[31] utf8_1.1.4 stringi_1.5.3 RCurl_1.98-1.2 crayon_1.3.4 rjson_0.2.20 R.oo_1.24.0

THE ERROR MESSAGE:

devtools::install_github("ChenWeiyan/LandSCENT")
Downloading GitHub repo ChenWeiyan/LandSCENT@HEAD
✓ checking for file ‘/private/var/folders/px/ncqctk414lx71h5wq13b91lcvpnkxl/T/Rtmp5ifQqs/remotes9ee28480512/ChenWeiyan-LandSCENT-ea35ec9/DESCRIPTION’ ...
─ preparing ‘LandSCENT’:
✓ checking DESCRIPTION meta-information ...
─ installing the package to process help pages
Error: Failed to install 'LandSCENT' from GitHub:
stderr is not a pipe.

Thank you
Arcadi