CancerInSilico

Here CancerInSilico method will be demonstrated clearly and hope that this document can help you.

Estimating parameters from a real dataset

Before simulating datasets, it is important to estimate some essential parameters from a real dataset in order to make the simulated data more real. If you do not have a single-cell transcriptomics count matrix now, you can use the data collected in simmethods package by simmethods:data command.

library(simmethods)
library(SingleCellExperiment)
# Load data
ref_data <- simmethods::data
dim(ref_data)
# [1] 4000  160

Using simmethods::CancerInSilico_estimation command to execute the estimation step.

estimate_result <- simmethods::CancerInSilico_estimation(ref_data = ref_data,
                                                         verbose = T,
                                                         seed = 10)
# Estimating parameters using CancerInSilico

Simulating datasets using CancerInSilico

After estimating parameter from a real dataset, we will simulate a dataset based on the learned parameters with different scenarios.

  1. Datasets with default parameters
  2. Determin the number of cells

Datasets with default parameters

The reference data contains 160 cells and 4000 genes, if we simulate datasets with default parameters and then we will obtain a new data which has the same size as the reference data.

simulate_result <- simmethods::CancerInSilico_simulation(
  parameters = estimate_result[["estimate_result"]],
  return_format = "SCE",
  seed = 111
)
# 
# time = 0.00
# size = 1
# time = 1.00
# size = 1
# nCells: 160
# nGenes: 4000
SCE_result <- simulate_result[["simulate_result"]]
dim(SCE_result)
# [1] 4000  160
head(colData(SCE_result))
# DataFrame with 6 rows and 1 column
#         cell_name
#       <character>
# Cell1       Cell1
# Cell2       Cell2
# Cell3       Cell3
# Cell4       Cell4
# Cell5       Cell5
# Cell6       Cell6
head(rowData(SCE_result))
# DataFrame with 6 rows and 1 column
#         gene_name
#       <character>
# Gene1       Gene1
# Gene2       Gene2
# Gene3       Gene3
# Gene4       Gene4
# Gene5       Gene5
# Gene6       Gene6

Determin the number of cells

In CancerInSilico, we can set nCells to specify the number of cells. Here, we simulate a new dataset with 2000 cells:

simulate_result <- simmethods::CancerInSilico_simulation(
  parameters = estimate_result[["estimate_result"]],
  return_format = "list",
  other_prior = list(nCells = 2000),
  seed = 111
)
# 
# time = 0.00
# size = 1
# time = 1.00
# size = 1
# nCells: 2000
# nGenes: 4000
result <- simulate_result[["simulate_result"]][["count_data"]]
dim(result)
# [1] 4000 2000