scMultiSim

https://zhanglabgt.github.io/scMultiSim/
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scMultiSim is an in silico simulator that generates multi-modality single-cell data, including gene...
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### Install scMultiSim from Bioconductor

Source: https://zhanglabgt.github.io/scMultiSim/index.html

Recommended installation method using BiocManager.

```R
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("scMultiSim")
```

--------------------------------

### Install scMultiSim development version

Source: https://zhanglabgt.github.io/scMultiSim/index.html

Install the latest features directly from the GitHub repository.

```R
devtools::install_github("ZhangLabGT/scMultiSim@main")
```

--------------------------------

### Initialize Island Layout

Source: https://zhanglabgt.github.io/scMultiSim/articles/spatialCCI.html

Start a simulation using the islands layout configuration.

```R
results <- sim_true_counts(spatial_options(
```

--------------------------------

### Phyla1(len = 1)

Source: https://zhanglabgt.github.io/scMultiSim/reference/Phyla1.html

Creates a linear example tree of a specified length.

```APIDOC
## Phyla1

### Description
Creates a linear example tree for use in phylogenetic simulations.

### Usage
Phyla1(len = 1)

### Arguments
- **len** (numeric) - The length of the tree.

### Value
Returns an R phylo object.

### Example
```r
Phyla1(len = 1)
```
```

--------------------------------

### Implement a sequential grid layout

Source: https://zhanglabgt.github.io/scMultiSim/articles/spatialCCI.html

Example of a layout function that places cells sequentially in a grid starting from the bottom-left.

```R
results <- sim_true_counts(spatial_options(
  layout = function (grid_size, cell_types) {
    ncells <- length(cell_types)
    new_locs <- matrix(nrow = ncells, ncol = 2)
    # for each cell...
    for (i in 1:ncells) {
      # ...place it in the grid
      new_locs[i,] <- c(i %% grid_size, i %/% grid_size)
    }
    return(new_locs)
  }
))
```

--------------------------------

### Example execution of sim_example_200_cells

Source: https://zhanglabgt.github.io/scMultiSim/reference/sim_example_200_cells.html

Demonstrates the basic execution of the function and the resulting output structure.

```R
sim_example_200_cells()
#> Time spent: 0.01 mins
#> <environment: 0x301abe038>
#> attr(,"name")
#> [1] "scMultiSim Result"
```

--------------------------------

### Simulating Observed Counts Example

Source: https://zhanglabgt.github.io/scMultiSim/reference/True2ObservedCounts.html

An example demonstrating how to generate an observed count matrix using simulated cell data and gene length information.

```R
results <- sim_example_200_cells()
#> Time spent: 0.01 mins
data(gene_len_pool)
gene_len <- sample(gene_len_pool, results$num_genes, replace = FALSE)
True2ObservedCounts(
  results$counts, results$cell_meta, protocol = "nonUMI", randseed = 1,
  alpha_mean = 0.1, alpha_sd = 0.05, gene_len = gene_len, depth_mean = 1e5, depth_sd = 3e3
)
#> 50..100..150..200..
#>         [,1]  [,2] [,3] [,4] [,5] [,6]  [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#>   [1,]  2855  1252 2756  402 2156 2601   651 2771 1673  1189    36  1877  1650
#>   [2,]   437     0  955  388 1007  822   377  699  528   281  2058   251   124
#>   [3,]     0   535    0  533  324  105     0    0  111     0     0     0     0
#>   [4,]   260     0    0    0  104    0     0    0    0     0     0     0     0
#>   [5,] 46522  3111 6317 1042 1122 2140  8310 5735 7225  7794  1250  3003  6211
#>   [6,]     0     0    0    0    0    0     0    0    0     0   600     0     0
#>   [7,]   716  3291 4531 2578 1883 3640  4362 2240 5645  3432  2614  3870  6287
#>   [8,]  3292  1907 1862  396 2443 1044  2211 1900 1594  2167  3758  2488  3306
#>   [9,]   580   662  324  370    0 1020  1281    0  621  1179   820   835     0
#>  [10,]     0     0    0    0    0    0     0    0    0     0     0     0     0
#>  [11,]   197     0  168    0    0    0     0    0  435     0     0     0     0
#>  [12,]   313  1351    0    0  389    0     0    0    0  1100   123     0     0
#>  [13,]     0   189  595    0    0    0    97   74  608   282     0     0     0
#>  [14,]     0     0    0    0 1066    0    55    0    0   167     0   398     0
#>  [15,]    35   538    0  306    0    0     0  466  124   228     0   379     0
#>  [16,]     0     0    0  110  222    0     0    0    0     0     0     0     0
#>  [17,]   985  1870 1081  990  717 1236  3496   77  711  1339     0  1019  1007
#>  [18,]    69  1004  630  620  143  744  1476 1271  361  1213     0     0   703
#>  [19,]     0   658    0    0    0  759     0    0    0     0     0     0     0
#>  [20,]  1567  1453 4420 1169 2743 2613  1589 3414 1173  1049  3481  2695  5893
#>  [21,]  1063  3436 3535  587 1278  367  1103  262  879  1376  1276  2792  3820
#>  [22,]     0     0  185 1074   84  132     0  202  132   598     0     0     0
#>  [23,]     0  1596  362    0  216    0     0  590   31     0     0     0   307
#>  [24,]   539     0    0    0  511  276     0    0  769     0     0     0     0
#>  [25,]     0     0  223  437    0    0    28    0  182     0     0     0     0
#>  [26,]     0    70  816 1717 1158    0   251    0 1062   336   759   680  3019
```

--------------------------------

### Example of plotting the CCI grid

Source: https://zhanglabgt.github.io/scMultiSim/reference/plot_grid.html

Demonstrates generating simulation results and plotting the grid.

```R
results <- sim_example_200_cells_spatial()
#> CCI simulation is enabled.
#> Get CIF...100..200..Done
#> Get params...Done
#> Simulating...50..100..150..200..
#> Time spent: 2.13 mins
plot_grid(results)
```

--------------------------------

### Phyla3(plotting = FALSE)

Source: https://zhanglabgt.github.io/scMultiSim/reference/Phyla3.html

Creates an example phylogenetic tree with 3 tips and 2 internal nodes.

```APIDOC
## Phyla3(plotting = FALSE)

### Description
Creates an example phylogenetic tree with 3 tips and 2 internal nodes.

### Usage
Phyla3(plotting = FALSE)

### Arguments
- **plotting** (boolean) - Optional - True for plotting the tree on console, False for no plot.

### Value
Returns an R phylo object.

### Examples
```r
Phyla3()
```
```

--------------------------------

### sim_example_200_cells(velocity = FALSE)

Source: https://zhanglabgt.github.io/scMultiSim/reference/sim_example_200_cells.html

Simulates a small example dataset with 200 cells and the 100-gene GRN.

```APIDOC
## sim_example_200_cells

### Description
Simulate a small example dataset with 200 cells and the 100-gene GRN.

### Usage
```R
sim_example_200_cells(velocity = FALSE)
```

### Arguments
- **velocity** (logical) - Optional - Whether to simulate RNA velocity. Defaults to FALSE.

### Value
Returns the simulation result as an environment object.

### Examples
```R
sim_example_200_cells()
```
```

--------------------------------

### Phyla5(plotting = FALSE)

Source: https://zhanglabgt.github.io/scMultiSim/reference/Phyla5.html

Generates an example phylogenetic tree with 5 tips. Returns an R phylo object.

```APIDOC
## Phyla5

### Description
Creates an example phylogenetic tree with 5 tips.

### Usage
Phyla5(plotting = FALSE)

### Arguments
- **plotting** (logical) - Optional - If TRUE, plots the tree on the console.

### Value
Returns an R phylo object.

### Examples
```r
Phyla5()
```
```

--------------------------------

### Example: Plotting cell locations

Source: https://zhanglabgt.github.io/scMultiSim/reference/plot_cell_loc.html

Demonstrates how to generate a plot using a simulation result object.

```R
results <- sim_example_200_cells_spatial()
#> CCI simulation is enabled.
#> Get CIF...100..200..Done
#> Get params...Done
#> Simulating...50..100..150..200..
#> Time spent: 2.17 mins
plot_cell_loc(results)
```

--------------------------------

### Example Output of sim_example_200_cells_spatial

Source: https://zhanglabgt.github.io/scMultiSim/reference/sim_example_200_cells_spatial.html

Shows the console output and return value structure when running the simulation.

```R
sim_example_200_cells_spatial()
#> CCI simulation is enabled.
#> Get CIF...100..200..Done
#> Get params...Done
#> Simulating...50..100..150..200..
#> Time spent: 2.17 mins
#> <environment: 0x30047b3c8>
#> attr(,"name")
#> [1] "scMultiSim Result"
```

--------------------------------

### Example usage of divide_batches

Source: https://zhanglabgt.github.io/scMultiSim/reference/divide_batches.html

Demonstrates the workflow of simulating cells, adding noise, and then applying batch effects.

```R
results <- sim_example_200_cells()
#> Time spent: 0.01 mins
add_expr_noise(results)
#> Adding experimental noise...
#> 50..100..150..200..Using atac_counts
#> Time spent: 0.02 mins
divide_batches(results)
#> Adding batch effects...
```

--------------------------------

### Get_ATAC_correlation Example

Source: https://zhanglabgt.github.io/scMultiSim/reference/Get_ATAC_correlation.html

Example usage demonstrating the function with simulated data.

```R
results <- sim_example_200_cells()
#> Time spent: 0.02 mins
Get_ATAC_correlation(results$counts, results$atacseq_data, results$num_genes)
#> [1] 0.1455535
```

--------------------------------

### Example usage of gene_corr_cci

Source: https://zhanglabgt.github.io/scMultiSim/reference/gene_corr_cci.html

Demonstrates running the correlation analysis on a simulated dataset.

```R
results <- sim_example_200_cells_spatial()
#> CCI simulation is enabled.
#> Get CIF...100..200..Done
#> Get params...Done
#> Simulating...50..100..150..200..
#> Time spent: 2.11 mins
gene_corr_cci(results)
#> [[1]]
#>   target regulator correlation corr.non.nbs corr.non.ct
#> 1    101       103  0.13046674  -0.04319376  0.02076041
#> 2    102       104  0.05855992   0.02218742  0.01952666
#> 
#> [[2]]

#> 
```

--------------------------------

### Example usage of plot_gene_module_cor_heatmap

Source: https://zhanglabgt.github.io/scMultiSim/reference/plot_gene_module_cor_heatmap.html

Demonstrates generating a heatmap from simulation results.

```R
results <- sim_example_200_cells()
#> Time spent: 0.01 mins
plot_gene_module_cor_heatmap(results)

#> NULL
```

--------------------------------

### Get_1region_ATAC_correlation Example

Source: https://zhanglabgt.github.io/scMultiSim/reference/Get_1region_ATAC_correlation.html

Example usage demonstrating the function with simulated data.

```R
results <- sim_example_200_cells()
#> Time spent: 0.02 mins
Get_1region_ATAC_correlation(results$counts, results$atacseq_data, results$region_to_gene)
#> [1] 0.211397
```

--------------------------------

### sim_example_200_cells_spatial()

Source: https://zhanglabgt.github.io/scMultiSim/reference/sim_example_200_cells_spatial.html

Executes a simulation of a small example dataset with 200 cells and a 100-gene GRN, including spatial cell-cell interactions.

```APIDOC
## sim_example_200_cells_spatial()

### Description
Simulates a small example dataset with 200 cells and the 100-gene GRN, with CCI enabled.

### Usage
```R
sim_example_200_cells_spatial()
```

### Value
Returns the simulation result as an environment object.
```

--------------------------------

### Configure CCI Parameters

Source: https://zhanglabgt.github.io/scMultiSim/articles/options

Example of defining the 'cci' list with a data frame of ligand-receptor interaction effects.

```R
cci = list(
  params = data.frame(
    target    = c(2,   6,   10,   8, 20,  30),
    regulator = c(101, 102, 103, 104, 105, 106),
    effect    = 20
  )
)
```

--------------------------------

### Example of gen_clutter execution

Source: https://zhanglabgt.github.io/scMultiSim/reference/gen_clutter.html

Demonstrates a basic call to generate 10 cells centered at coordinates (5, 5).

```R
gen_clutter(10, 10, c(5, 5))
#> Error in gen_clutter(10, 10, c(5, 5)): could not find function "gen_clutter"
```

--------------------------------

### Example of generating a t-SNE plot

Source: https://zhanglabgt.github.io/scMultiSim/reference/plot_tsne.html

Demonstrates how to generate a t-SNE plot using simulated cell data.

```R
results <- sim_example_200_cells()
#> Time spent: 0.01 mins
plot_tsne(log2(results$counts + 1), results$cell_meta$pop)
```

--------------------------------

### Display Observed Count Matrix

Source: https://zhanglabgt.github.io/scMultiSim/reference/True2ObservedCounts.html

Example output showing a subset of the observed count matrix generated by the simulation.

```text
#>  [58,]   1229    516    979   1119   1050   1130    659   3416   3065   1516
#>  [59,]      0   4265   3529   1584    970   2525     94    586   3354    158
#>  [60,]      0   3060      0   1803    686    881   3129    177    189   2626
#>  [61,]      0   1011      0   1544    888      0    193      0   1541    138
#>  [62,]      0      0      0    132      0    565      0      0      0    458
#>  [63,]   4705      0      0      0   2374    451    371    845    872   1345
#>  [64,]    660      0    509    604      0      0      0      0      0      0
#>  [65,]      0      0    659     61    990      0    537    177      0      0
#>  [66,]      0   2288   6486    803    752    856   1379   3675   1877   1862
#>  [67,]   3534   1029    562      0   1405    153   2053   2546    151      0
#>  [68,]      0      0   3452      0      0   3744     86      0      0   3468
#>  [69,]      0      0      0      0      0      0      0      0      0      0
#>  [70,]      0   2609      0   1411    257      0    292      0     99      0
#>  [71,]      0      0      0   3146    261      0      0      0    154      0
#>  [72,]    830   7625      0      0   2589    738   1018    410    423    361
#>  [73,]   1168   2995   1083    314   2271   1106   2043   4303   1284   4774
#>  [74,]      0   2856      0      0      0      0      0    801    688      0
#>  [75,]      0    587   1494    384    928      0   1129    767   2111    546
#>  [76,]      0      0      0      0      0      0      0      0      0    101
#>  [77,]      0      0      0    721      0      0   1237    870     60    512
#>  [78,]   1441   3174   3951   1223    403   1116    908   1606   1047    595
#>  [79,]      0      0      0   1036    848      0      0      0      0    448
#>  [80,]      0      0   2552    470    616      0    816      0   1183   2105
#>  [81,]      0   1425    500   1514   1612    428   1593    620   1537   5118
#>  [82,]      0      0   2537      0      0      0      0    318      0    151
#>  [83,]      0      0      0   2246      0    320      0   1653      0      0
#>  [84,]   1982    228   3664    402      0      0    168   2453   1997   1374
#>  [85,]      0      0   5487      0      0   5316   2037    446    471    404
#>  [86,]      0    801   3199     69    221   3114      0      0   1362    272
#>  [87,]   2632      0      0   1468      0   2314      0   1038    476      0
#>  [88,]   3045    400      0    738  11073   2065      0   1496   3013   3633
#>  [89,]      0      0      0      0      0      0      0      0    559    180
#>  [90,]   1212   1959   1176      0   1192   1893    553      0      0      0
#>  [91,]      0      0    630    871      0    730    666    243    176      0
#>  [92,]    496      0   2540    124    222    932    546    573    299    351
#>  [93,]      0   1583    761      0   1545   1720    373      0    476      0
#>  [94,]   4796   6173   4442   5172   8824   1289   5501   6922   6441   3143
#>  [95,]   1289    488      0    846      0   1588    255      0      0      0
#>  [96,]    212   2180      0    526   1399   2093    698   1502    965    229
#>  [97,]   1976   5941   1521   4440    943    383   2650   2170   3271    561
#>  [98,]      0      0      0   1517   2294   2754   1912   1623      0      0
#>  [99,]      0      0      0      0      0      0      0      0      0      0
#> [100,]    412      0      0    276      0      0    252    569      0      0
#> [101,]      0    836   1260      0   1178      0   1464    580   1076   1661
#> [102,]      0      0      0      0      0      0    212      0    644      0
#> [103,]      0      0   1497    300   1053      0    553     98      0      0
#> [104,]   3077      0      0      0      0   2112    400      0    909      0
#> [105,]      0      0      0      0      0    378      0      0      0      0
#> [106,]    511      0      0      0      0      0    889    290    185      0
#> [107,]   2966    972    233   1007    670   4475    685    294   1414   1282
#> [108,]    723      0      0   1984   2819    356   1399    459    484   1121
#> [109,]      0    478      0   1330      0      0    749    821      0      0
#> [110,]      0      0    557      0      0      0   1094    403      0      0
#>        [,168] [,169] [,170] [,171] [,172] [,173] [,174] [,175] [,176] [,177]
#>   [1,]    633      0   2161   1396      0    899   4540      0   1920      0
#>   [2,]    214    731   1617    274    355    307      0   2856    586    613
#>   [3,]    112      0      0    308    358      0    424      0      0      0
#>   [4,]      0      0      0      0      0      0      0      0      0      0
#>   [5,]   1522   6018   3115    335   2063   2254   2372   2933   3769   4315
#>   [6,]      0      0      0      0      0      0      0      0      0      0
#>   [7,]   7031   5548   2912   1550   3241    121    919   2219   1718      0
#>   [8,]    487   3384   4977   3740   2973   2382   1311   5274   2529   1535
```

--------------------------------

### Initialize spatial domain layout

Source: https://zhanglabgt.github.io/scMultiSim/articles/spatialCCI.html

Start defining a layout function for creating spatial domains using circular clustering.

```R
layout_fn <- function(grid_size, final_types) {
  ncells <- length(final_types)
  grid_center <- c(round(grid_size / 2), round(grid_size / 2))
  all_locs <- gen_clutter(ncells, grid_size, grid_center)
```

--------------------------------

### Example usage of gene_corr_regulator

Source: https://zhanglabgt.github.io/scMultiSim/reference/gene_corr_regulator.html

Demonstrates initializing simulation results and querying correlations for a specific regulator ID.

```R
results <- sim_example_200_cells()
#> Time spent: 0.01 mins
gene_corr_regulator(results, 2)
#> Gene correlations for 2:
#> 78(0.80) 102 5(0.63) 37(0.62) 109 7(0.61) 73 54(0.59) 57 3(0.57) 36 1(0.55) 45 38 8(0.55) 20 30 108 88 33 72 101 29 21 75 42 25 66 56 58 27 44 61 13 17 47 51 84 69 50 97 79 59 46 9(0.39) 39 18 60 89(0.36) 48 95 83 80 93 92 67 65 31 32 77 28 96 104 10 99 64 107 15 62 43 41 68 90 103 40 26 35 98 71 81 24 85 52 74 6 87 14 19 11 53 49 70 76 16 63 4(0.10) 34 94 55 91 100 82 105 22 110 12 86(-0.08) 106 23 
```

--------------------------------

### Example usage of plot_rna_velocity

Source: https://zhanglabgt.github.io/scMultiSim/reference/plot_rna_velocity.html

Demonstrates generating a simulation result object with velocity data and plotting it.

```R
results <- sim_example_200_cells(velocity = TRUE)
#> Time spent: 0.05 mins
plot_rna_velocity(results)
#> $raw

#> 
#> $normalized

#> 
#> $knn_normalized

#>
```

--------------------------------

### Access help for ext.cif.giv

Source: https://zhanglabgt.github.io/scMultiSim/articles/spatialCCI.html

Displays documentation for the ext.cif.giv parameter.

```R
scmultisim_help("ext.cif.giv")
```

--------------------------------

### Launch the Shiny App

Source: https://zhanglabgt.github.io/scMultiSim/index.html

Run the interactive visualization and parameter adjustment tool.

```R
run_shiny()
```

--------------------------------

### Access dynamic GRN help documentation

Source: https://zhanglabgt.github.io/scMultiSim/articles/basics.html

Displays usage information and configuration options for the dynamic GRN simulation module.

```R
scmultisim_help("dynamic.GRN")
```

--------------------------------

### Access scMultiSim help

Source: https://zhanglabgt.github.io/scMultiSim/articles/basics.html

Retrieve documentation for simulation options or specific parameters.

```R
scmultisim_help("options")
```

--------------------------------

### Configure simulation options

Source: https://zhanglabgt.github.io/scMultiSim/articles/basics.html

Sets up the simulation parameters including cell count, GRN, and trajectory settings.

```R
options <- list(
  rand.seed = 0,
  GRN = GRN_params,
  num.cells = 1000,
  num.cifs = 50,
  cif.sigma = 0.5,
  tree = Phyla5(),
  diff.cif.fraction = 0.8,
  do.velocity = TRUE
)
```

--------------------------------

### Observed Counts Matrix Output

Source: https://zhanglabgt.github.io/scMultiSim/reference/True2ObservedCounts.html

Example of the numerical matrix output generated by the True2ObservedCounts function.

```text
#>  [32,]      0      0      0    364    824    331    118    613      0    676
#>  [33,]    925   1445   1616    259   3152    425      0    712   1151   1089
#>  [34,]      0      0      0      0      0      0      0      0      0      0
#>  [35,]    849   2017    541   2165    474      0   1728    352   1734   4446
#>  [36,]   1890   2902   2729   2642   2432   3410   2397   3501   2880   6153
#>  [37,]    967   1033    479    326   2177   1619   3053   4383   1550   4201
#>  [38,]      0      0    320      0      0    816      0      0    104      0
#>  [39,]    115    332      0   1660      0      0      0    445   1188      0
#>  [40,]      0      0    774    237      0      0      0    658      0      0
#>  [41,]      0      0    840      0     29      0      0   1461      0      0
#>  [42,]   4167    940   3192   5142   3073   1320   1545   7201    901   6089
#>  [43,]    249   1783    199    682   1959      0    260      0    601   1238
#>  [44,]   4404   2510   3105   2221   1841   1536    478   2633   2392   2077
#>  [45,]   1825      0    288    226   2330    295    668      0   3428      0
#>  [46,]    650   1787   2641    998   1749   2678   2098   1721    455   1021
#>  [47,]      0    778    392    726   1746      0      0   1131    273    616
#>  [48,]      0   1152    743   2872   2186      0   1816    405    526    426
#>  [49,]    326    322      0      0      0    273      0      0      0      0
#>  [50,]   7058      0   7044  10253    956   5257   5534   9375   6983   7300
#>  [51,]      0      0    126      0      0      0      0      0    108    219
#>  [52,]      0      0      0      0      0    522      0    879    240      0
#>  [53,]      0      0      0    680      0      0    352      0    471      0
#>  [54,]    206   2702    935     62    415   2234    426    887    891   1471
#>  [55,]      0      0      0      0      0      0      0    123      0      0
#>  [56,]   2155    124    762   1359   2680    258      0    194   1629   3204
#>  [57,]    179    254   1383      0    853    240    709      0    652      0
#>  [58,]   4913    519      0      0   1141      0    193   1437   2507      0
#>  [59,]   1859   2297    194      0   1042    923     30   1690   2536      0
#>  [60,]    711      0    179    256    649    224   3270    260    774   1303
#>  [61,]      0      0    716   1406   1910   1365   2543      0    146      0
#>  [62,]      0      0    315    743      0    482   1609     96   1730      0
#>  [63,]   1755    455    404   1222    348   1214      0   3482      0    836
#>  [64,]    787      0    109    550    447      0      0      0      0      0
#>  [65,]    741      0      0      0    475      0      0    354      0      0
#>  [66,]   2181   3376    564      0   4140   1356   1080   2046   2201    888
#>  [67,]   2402   1566   1918   1793   1990   2934   2252    226   2987   2870
#>  [68,]    666      0      0   2578   1510      0    313   1019    782   2601
#>  [69,]      0      0    762      0      0      0      0      0    654      0
#>  [70,]      0   1643   1680   1467    868      0   1091    276      0   2303
#>  [71,]      0      0    269    685      0      0      0    634    171      0
#>  [72,]   1673   2420   2509    855    146    561      0   1509    931    164
#>  [73,]   3027   1465    834   3856   3962   3073   1366      0   2236   2384
#>  [74,]      0      0      0   1642   2450   2241   5031   7454    736      0
#>  [75,]   2888    404   2192   1019    969    687    577     44   1290    547
#>  [76,]      0      0      0   2407      0      0      0      0      0      0
#>  [77,]      0   2066    903      0   1870    482      0      0      0   2596
#>  [78,]   1123   2947   1248   2440   3158   6668   4982   1429   1099   1120
#>  [79,]      0      0      0      0      0      0      0      0      0      0
#>  [80,]    400    684    494   2829   1605      0      0    210   1562   1411
#>  [81,]   1254      0   3695      0   1002    619      0      0   1187      0
#>  [82,]      0      0      0   1310      0      0      0    403     51      0
#>  [83,]      0      0      0    642    341      0      0    213      0      0
#>  [84,]    664   1070    917   1667    499   1490   1256    100   2791    649
#>  [85,]   2802    505   2756      0    818    846   1454    864      0      0
#>  [86,]      0      0      0      0      0   3114      0      0      0      0
#>  [87,]      0   1076    254    864   1562    340   1385   1030    324      0
#>  [88,]      0    362   1307   2186    667      0   1562   3085    205      0
#>  [89,]      0      0    342      0      0    625      0      0      0      0
#>  [90,]    359   1411   5395   1544   1188    931   1722      0   1342   2031
#>  [91,]      0      0    248      0    237      0      0    755    507      0
#>  [92,]      0    322    918      0   1331    614    636    388    946   1264
#>  [93,]      0    386      0      0    633      0   1723      0    275      0
```

--------------------------------

### Help output for ext.cif.giv

Source: https://zhanglabgt.github.io/scMultiSim/articles/spatialCCI.html

Documentation text for the ext.cif.giv function.

```text
## ext.cif.giv  (default: NA)
##  Add customized CIF and GIV. The function takes one argument, the kinetic
##   parameter index (1=kon, 2=koff, 3=s). It should return a list of two el
##  ements: the extra CIF matrix (n_extra_cif x n_cells) and the GIV matrix 
##  (n_genes x n_extra_cif). Return NULL for no extra CIF and GIV.
##  should be a function
```

--------------------------------

### run_shiny()

Source: https://zhanglabgt.github.io/scMultiSim/reference/run_shiny.html

Launches the interactive Shiny application for simulation configuration.

```APIDOC
## run_shiny()

### Description
Launches the Shiny application to configure the simulation parameters through a graphical user interface.

### Usage
```r
run_shiny()
```
```

--------------------------------

### scmultisim_help(topic = NULL)

Source: https://zhanglabgt.github.io/scMultiSim/reference/scmultisim_help.html

Displays detailed documentation for scMultiSim parameters. Users can specify a topic to filter the help information.

```APIDOC
## scmultisim_help(topic = NULL)

### Description
Displays detailed documentation for scMultiSim parameters. Calling this function without arguments prints help for options by default.

### Parameters
- **topic** (string) - Optional - The category of parameters to display. Supported values: "options", "dynamic.GRN", or "cci".

### Usage Example
```r
# Display general options
scmultisim_help()

# Display dynamic GRN documentation
scmultisim_help(topic = "dynamic.GRN")
```
```
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