Sachs multiparameter flow cytometry data and consensus model

Flow cytometry data and causal model from Sachs et al. (2005).

sachs

Format

"sachs" is a list of 5 objects:

1. "rawdata", a list of 14 data.frames containing raw flow cytometry data (Sachs et al., 2005);

2. "graph", consensus signaling network;

3. "model", consensus model (lavaan syntax);

4. "pkc", data.frame of 1766 samples and 11 variables, containing cd3cd28 (baseline) and pma (PKC activation) data;

5. "group", a binary group vector, where 0 is for cd3cd28 samples (n = 853) and 1 is for pma samples (n = 913).

6. "details", a data.frame containing dataset information.

Source

doi:10.1126/science.1105809

References

Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP (2019). Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data. Science, 308(5721): 523-529.

Examples

# Dataset content
names(sachs$rawdata)
#>  [1] "cd3cd28"               "cd3cd28_icam2"         "cd3cd28_aktinhib"     
#>  [4] "cd3cd28_g0076"         "cd3cd28_psitect"       "cd3cd28_u0126"        
#>  [7] "cd3cd28_ly"            "pma"                   "b2camp"               
#> [10] "cd3cd28icam2_aktinhib" "cd3cd28icam2_g0076"    "cd3cd28icam2_psit"    
#> [13] "cd3cd28icam2_u0126"    "cd3cd28icam2_ly"      
dim(sachs$pkc)
#> [1] 1766   11
table(sachs$group)
#> 
#>   0   1 
#> 853 913 
cat(sachs$model)
#> 
#> # path model
#> P38 ~ PKA + PKC
#> Jnk ~ PKA + PKC
#> Akt ~ PKA + PIP3
#> Erk ~ PKA + Mek
#> Mek ~ PKA + PKC + Raf
#> Raf ~ PKA + PKC
#> PKC ~ PIP2 + Plcg
#> PIP2 ~ PIP3 + Plcg
#> Plcg ~ PIP3
#> 
#> # covariances
#> PIP2 ~~ PIP3
gplot(sachs$graph)