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Hi--

I'm analyzing a dataset with FAUST imported from FlowJo with CytoML::flowjo_to_gatingset(). I'm having trouble finding exactly what/where the transformation is that is applied to the raw data in the FAUST or CytoML documentation. Could you clarify this? Thanks!

Hi,

I would want to extract cell ids in each cell type. I do notice that the file annotationMatrix.csv provides cluster information but I wonder if there is a more concise way of getting them.

Thanks in advance for your help.

Allen

Hi,
I think the ScoreLines should be made clearer. When the number of markers increases, it's difficult to match colors to markers. I would suggest using adding marker names of the right and link them to lines by use of ggrepl. Alternatively a two columns table (marker, score) would be helpful.
Thanks.

Hi,

First of all, I have very limited knowledge of gating...
In the FAUST package document, at step three, "Live" is assigned to startingNode. But what if the gating strategy of my dataset is not provided? I created a gatingSet for my data but I don't know how to get around this manual assignment. It turned out that the gatingSet object of the work example possesses more classes than my gatingSet object. The instruction said openCyto can be used to gate live cells so I browsed the webpage

https://bioconductor.org/packages/devel/bioc/vignettes/openCyto/inst/doc/HowToAutoGating.html

However, it seems that I still have to reference some variables such as "Live" to indicate the root population that my data don't have... I'm stuck...

Thanks in advance for your help.

Allen

Hi,
The outputs of FAUST are multiple. Is there a map? ;-)
I would like to analyze FAUST clustering result on a synthetic dataset. Which output file should I use to get the cluster assigned to each cell of a flowset of a unique flowframe? I built compressed codes by reading annotationMatrix.csv file.
codes = apply(read.csv("c:/demo/FAUST/faustData/sampleData/V1/annotationMatrix.csv", header = FALSE)-1, 1, paste0, collapse = "")
But I am not sure because the cell counts do not match exactly the counts from count.long obtained as in the vignette. If you could help me...
Best,
Samuel

I've used FAUST successfully on one dataset (12 markers), so thanks! I'm applying it now to a dataset with ~24 markers, and finding a large proportion of cells (40-60%) per sample are unannotated as '0_0_0_0_0'. Gates look sensible and most markers are clearly bimodal.

Is this the expected behaviour? It looks like there are two ways a cell can be unannotated: are there any parameters I can tune to explore this? Thanks for any advice.

Hi

I'm trying to install FAUST but I'm having a problem to install scamp (see RGLab/scamp#3
)

I have also tried to install it from source following instructions from

https://support.rstudio.com/hc/en-us/articles/200486088-Using-Rcpp-with-RStudio

but I get this error:

install.packages('C:/Users/njo47/R/win-library/3.6/scamp', type="source")
Installing package into ‘C:/Users/njo47/R/win-library/3.6’
(as ‘lib’ is unspecified)
Warning in install.packages :
package ‘C:/Users/njo47/R/win-library/3.6/scamp’ is not available (for R version 3.6.0)

Any ideas of where is the problem and how to install FAUST?

Thanks
Juan

Hi,

In step five of the work example, you set the lower bound to 0. Now I want zeros to be considered so I changed 0 to -0.01. However, it turned out that the code chunk in step seven keeps running without any warning/error message. The chunk has been running for more than 5 hours. Previously, with the lower boundary equal 0, the chunk was done within 10 minutes. So is it because there is too much computation involved as 0s are being considered, or simply because the algorithm doesn't accept negative values?

P.S. I noted a tiny contradiction in step five. At the very beginning, you said

"For example, we would expect any cell populations with a median fluorescence intensity (MFI) below 0 in a channel to be annotated as “Low” for that channel."

However, later you stated

"Expression values in a channel less than or equal to the value in the “Low” row are treated as low, by default, and not actively considered when FAUST processes the data."

So 0s are actually considered as active or not in your algorithm?

Thanks in advance for your help.

Allen

Thanks for this software!

I am hoping to use it to define cell annotations, then compare the expression of a marker (not used in annotation) across these annotation clusters. I am having trouble linking the per-cell FAUST annotation to markers that were not used in the annotation strategy. For instance levelExprs.rds in the levelData outputs only includes the markers used in annotation (and this appears to be identical to the exprsMat.rds in sampleData?).

Is there an easy way to pull this data from the FAUST outputs? Thanks!

Hi Evan,

scamp and FAUST installed successfully from source, including options to install vignette - however vignette still not found. What would you suggest?

Initial trial of vignette

> library(faust)
> vignette('faustIntro')
Warning message:
vignette ‘faustIntro’ not found 

Trial re-install faust needs force = TRUE option

> devtools::install_github("RGLab/FAUST", build = TRUE, build_opts = c("--no-resave-data", "--no-manual"))
Skipping install of 'faust' from a github remote, the SHA1 (a02f71a0) has not changed since last install.
  Use `force = TRUE` to force installation

With force = TRUE

> devtools::install_github("RGLab/FAUST", build = TRUE, build_opts = c("--no-resave-data", "--no-manual"), force = TRUE)
Downloading GitHub repo RGLab/FAUST@master
These packages have more recent versions available.
Which would you like to update?

1: All                            
2: CRAN packages only             
3: None                           
4: ggplot2 (3.2.0 -> 3.2.1) [CRAN]

Enter one or more numbers, or an empty line to skip updates:
> 3
✔  checking for file ‘/private/var/folders/kp/dwz7y9gx6n37wt0f12yp8x2s8cbn2c/T/Rtmp9SNAhb/remotes25b093441ba/RGLab-FAUST-a02f71a/DESCRIPTION’ ...
─  preparing ‘faust’: (2.4s)
✔  checking DESCRIPTION meta-information ...
─  cleaning src
─  checking for LF line-endings in source and make files and shell scripts
─  checking for empty or unneeded directories
─  building ‘faust_0.0.2.901.tar.gz’
   Warning: invalid uid value replaced by that for user 'nobody'
   
* installing *source* package ‘faust’ ...
** using staged installation
** libs

## clang++ output omitted

** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (faust)

Re-trial of vignette

> vignette('faustIntro')
Warning message:
vignette ‘faustIntro’ not found 

What do you think?

> sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.6

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

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

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

other attached packages:
 [1] faust_0.0.2.901           tidyr_0.8.3               dplyr_0.8.3              
 [4] knitr_1.23                cowplot_1.0.0             ggplot2_3.2.0            
 [7] scamp_0.2.36              ggdendro_0.1-20           flowWorkspace_3.32.0     
[10] ncdfFlow_2.30.1           BH_1.69.0-1               RcppArmadillo_0.9.600.4.0
[13] flowCore_1.50.0           flowWorkspaceData_2.20.0 

loaded via a namespace (and not attached):
 [1] matrixStats_0.54.0  fs_1.3.1            usethis_1.5.1       devtools_2.1.0      RColorBrewer_1.1-2 
 [6] rprojroot_1.3-2     Rgraphviz_2.28.0    tools_3.6.0         backports_1.1.4     R6_2.4.0           
[11] KernSmooth_2.23-15  lazyeval_0.2.2      BiocGenerics_0.30.0 colorspace_1.4-1    withr_2.1.2        
[16] tidyselect_0.2.5    gridExtra_2.3       prettyunits_1.0.2   processx_3.4.1      curl_4.0           
[21] compiler_3.6.0      graph_1.62.0        cli_1.1.0           Biobase_2.44.0      desc_1.2.0         
[26] scales_1.0.0        DEoptimR_1.0-8      hexbin_1.27.3       mvtnorm_1.0-11      robustbase_0.93-5  
[31] ggridges_0.5.1      callr_3.3.1         stringr_1.4.0       digest_0.6.20       rmarkdown_1.14     
[36] rrcov_1.4-7         pkgconfig_2.0.2     htmltools_0.3.6     sessioninfo_1.1.1   rlang_0.4.0        
[41] rstudioapi_0.10     magrittr_1.5        Rcpp_1.0.2          munsell_0.5.0       viridis_0.5.1      
[46] stringi_1.4.3       whisker_0.3-2       yaml_2.2.0          MASS_7.3-51.4       zlibbioc_1.30.0    
[51] pkgbuild_1.0.3      plyr_1.8.4          grid_3.6.0          parallel_3.6.0      crayon_1.3.4       
[56] lattice_0.20-38     ps_1.3.0            pillar_1.4.2        corpcor_1.6.9       stats4_3.6.0       
[61] pkgload_1.0.2       glue_1.3.1          evaluate_0.14       latticeExtra_0.6-28 data.table_1.12.2  
[66] remotes_2.1.0       BiocManager_1.30.4  RcppParallel_4.4.3  testthat_2.2.1      gtable_0.3.0       
[71] purrr_0.3.2         assertthat_0.2.1    xfun_0.8            IDPmisc_1.1.19      pcaPP_1.9-73       
[76] viridisLite_0.3.0   tibble_2.1.3        memoise_1.1.0       flowViz_1.48.0      cluster_2.1.0

Hi,

I have seemingly managed to install scamp. However, after running the suggested lines

tryCatch(installed.packages()["knitr","Version"],
error = function(e){
install.packages("knitr")
})
tryCatch(installed.packages()["rmarkdown","Version"],
error = function(e){
install.packages("rmarkdown")
})
tryCatch(installed.packages()["ggdendro","Version"],
error = function(e){
install.packages("ggdendro")
})
tryCatch(installed.packages()["remotes","Version"],
error = function(e){
install.packages("remotes")
})
remotes::install_github("RGLab/FAUST", force = TRUE, build_vignettes = TRUE)

I came across some suspicious/error messages

E creating vignettes (2m 22.4s)
--- re-building ‘faustIntro.Rmd’ using rmarkdown
Quitting from lines 70-83 (faustIntro.Rmd)
Error: processing vignette 'faustIntro.Rmd' failed with diagnostics:
there is no package called 'flowWorkspaceData'
--- failed re-building ‘faustIntro.Rmd’

SUMMARY: processing the following file failed:
‘faustIntro.Rmd’

Error: Vignette re-building failed.
Execution halted
Error: Failed to install 'faust' from GitHub:
System command 'R' failed, exit status: 1, stderr empty

Thanks in advance for your help.

Allen