Simulate pseudo-bulk or spatial transcriptomics profiles from single-cell data

Generates pseudo-bulk expression profiles by sampling cells from a single-cell reference according to Dirichlet-drawn cell-type fractions. With mode = "spatial" the same machinery produces spot-level profiles instead, pooling only a handful of cells per spot and restricting each spot to a small number of cell types. Optionally returns per-cell-type signature profiles and a global signature matrix.

Usage

quasar_sim_bulk(
  ...,
  n_bulk_samples = NULL,
  cells_per_bulk = 500,
  mode = c("bulk", "spatial"),
  cells_per_spot_range = c(5L, 11L),
  celltypes_per_spot_range = c(1L, 5L),
  spatial_background = 1e-06,
  cell_type_column = "cell_type",
  patient_id_column = NULL,
  select_ct = NULL,
  dirich_alpha = 1,
  seet = 1,
  sparse = FALSE,
  sparse_prob = 0.5,
  rare = FALSE,
  rare_percentage = 0.4,
  return_used_samples = FALSE,
  return_patient_metadata = FALSE,
  return_signature_matrix = FALSE,
  verbose = TRUE
)

Arguments

...

The single-cell reference, supplied in one of two forms:

A single object: a Seurat object (counts taken from the "RNA" assay) or a SingleCellExperiment (counts taken from counts()).
Two objects: a genes \(\times\) cells count matrix followed by a cell-metadata data.frame whose row names match the column names of the count matrix.

n_bulk_samples

Integer number of pseudo-bulk samples to generate. If NULL (default), 1000 * (number of cell types) samples are generated.

cells_per_bulk

Integer number of cells pooled into each pseudo-bulk sample. Default 500. Ignored when mode = "spatial", where the pool size is drawn per spot from cells_per_spot_range.

mode

Character scalar selecting the simulation type. "bulk" (default) pools cells_per_bulk cells per sample from a symmetric Dirichlet over all cell types. "spatial" emulates spot-level transcriptomics: each spot keeps only a few cell types and pools a small, randomly drawn number of cells.

cells_per_spot_range

Integer vector of length two giving the inclusive range from which the number of cells per spot is drawn uniformly when mode = "spatial". Default c(5, 11).

celltypes_per_spot_range

Integer vector of length two giving the inclusive range from which the number of cell types present in a spot is drawn uniformly when mode = "spatial". Default c(1, 5), capped at the number of available cell types.

spatial_background

Numeric scalar giving the Dirichlet concentration assigned to cell types that are not selected for a spot when mode = "spatial". A small positive value leaves trace amounts rather than exact zeros, which is what the reference implementation does. Default 1e-6.

cell_type_column

Name of the metadata column holding cell-type labels. Default "cell_type".

patient_id_column

Optional name of a metadata column holding patient/donor IDs. When supplied, each pseudo-bulk is drawn from a single donor where that donor has cells of the required type (falling back to the full cell-type pool otherwise). Default NULL (no patient structure).

select_ct

Optional character vector restricting which cell types are used (and fixing their order in the output). Default NULL (all cell types).

dirich_alpha

Concentration parameter of the symmetric Dirichlet used to draw cell-type fractions. Smaller values give more skewed mixtures. Default 1 (uniform over the simplex).

seet

Integer random seed (passed to set.seed) for reproducibility. Default 1.

sparse

Logical; if TRUE, randomly zero out a fraction of cell-type entries before renormalisation, producing samples in which some cell types are absent. Default FALSE.

sparse_prob

Probability that a given cell-type fraction is dropped when sparse = TRUE. Default 0.5.

rare

Logical; if TRUE, force a random subset of cell-type fractions to small values in [0, 0.03] before renormalisation, to emulate rare populations. Default FALSE.

rare_percentage

Probability that a given cell-type fraction is made rare when rare = TRUE. Default 0.4.

return_used_samples

Logical; if TRUE, include the per-sample, per-cell-type cell indices that were drawn. Default FALSE.

return_patient_metadata

Logical; if TRUE and patient_id_column is set, include a data frame mapping each pseudo-bulk to its source donor. Default FALSE.

return_signature_matrix

Logical; if TRUE, also compute per-cell-type signature profiles (one genes \(\times\) bulk matrix per cell type) and a global genes \(\times\) cell-types signature matrix. Default FALSE.

verbose

Logical; if TRUE (default), print the header, progress bars, and timing summary. If FALSE, nothing is printed.

Value

A named list containing:

bulk_expression_profiles: Genes \(\times\) n_bulk_samples matrix of summed pseudo-bulk counts.
ground_truth_proportions: n_bulk_samples \(\times\) cell-types matrix of realized proportions (rows sum to 1).
cells_per_sample: Integer vector giving the realized number of cells pooled into each sample. Constant in bulk mode, variable in spatial mode.
used_samples_by_ct: (if return_used_samples) list of length n_bulk_samples, each a per-cell-type list of drawn cell indices.
bulk_patient_metadata: (if return_patient_metadata and patient mode) data frame mapping sample_id to patient_id.
bulk_signature_profiles: (if return_signature_matrix) list of per-cell-type genes \(\times\) bulk mean-expression matrices.
global_signature_matrix: (if return_signature_matrix) genes \(\times\) cell-types matrix of mean signatures.
timing: list with pseudobulk_seconds, signature_seconds, and total_seconds.

Details

In mode = "bulk", cell-type fractions are drawn from a symmetric Dirichlet, optionally modified by the sparse/rare masks, renormalised per sample, and turned into integer cell counts by floor(fraction * cells_per_bulk) (each bulk is guaranteed at least one cell).

In mode = "spatial", each spot first draws how many cell types it contains, then a Dirichlet whose concentration is dirich_alpha for the selected types and spatial_background for the rest. The number of cells in the spot is drawn uniformly from cells_per_spot_range and allocated by round(fraction * n_cells) rather than floor, because flooring a handful of cells would empty most spots. The sparse and rare arguments are ignored in this mode, since sparsity is already imposed by the per-spot cell-type selection.

In both modes cells are then sampled with replacement from the reference and summed, so the returned ground_truth_proportions reflect the *realized* allocations rather than the raw Dirichlet draws.

Examples


## Tiny synthetic reference: 1000 genes, 3 cell types, 100 cells each
set.seed(1)
n_genes        <- 1000
cell_types     <- c("Tcell", "Bcell", "Mono")
cells_per_type <- 100
n_cells        <- length(cell_types) * cells_per_type

counts <- matrix(
  rpois(n_genes * n_cells, lambda = 5),
  nrow = n_genes, ncol = n_cells
)
rownames(counts) <- paste0("gene_", seq_len(n_genes))
colnames(counts) <- paste0("cell_", seq_len(n_cells))

meta <- data.frame(
  cell_type = rep(cell_types, each = cells_per_type),
  row.names = colnames(counts)
)

## Generate 50 pseudo-bulks of 100 cells each, with signatures
res <- quasar_sim_bulk(
  counts, meta,
  n_bulk_samples          = 50,
  cells_per_bulk          = 100,
  return_signature_matrix = TRUE,
  verbose                 = TRUE
)
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#> Generated 50 pseudobulks (100 cells each) from 1000 genes
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#> Computed bulk_signature_profiles (list of genes×bulk matrices per cell type)
#> Signature matrix time: 0.01 secs
#> Returned global_signature_matrix (genes × celltypes)
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#> 

dim(res$bulk_expression_profiles)   # 1000 x 50
#> [1] 1000   50
head(res$ground_truth_proportions)  # rows sum to 1
#>               Tcell     Bcell       Mono
#> sample_1 0.04081633 0.4897959 0.46938776
#> sample_2 0.25252525 0.3838384 0.36363636
#> sample_3 0.71717172 0.2222222 0.06060606
#> sample_4 0.16161616 0.3333333 0.50505051
#> sample_5 0.02040816 0.5408163 0.43877551
#> sample_6 0.43877551 0.3877551 0.17346939
dim(res$global_signature_matrix)    # 1000 x 3
#> [1] 1000    3

## Spatial spots: few cells and few cell types per spot
spots <- quasar_sim_bulk(
  counts, meta,
  n_bulk_samples = 200,
  mode           = "spatial",
  verbose        = TRUE
)
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#> [███████████                   ]  36.00%
#> Spots         : 72 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████                   ]  37.00%
#> Spots         : 74 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████                   ]  38.00%
#> Spots         : 76 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████                  ]  39.00%
#> Spots         : 78 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████                  ]  40.00%
#> Spots         : 80 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████                  ]  41.00%
#> Spots         : 82 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████                 ]  42.00%
#> Spots         : 84 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████                 ]  43.00%
#> Spots         : 86 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████                 ]  44.00%
#> Spots         : 88 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████                ]  45.00%
#> Spots         : 90 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████                ]  46.00%
#> Spots         : 92 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████                ]  47.00%
#> Spots         : 94 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████                ]  48.00%
#> Spots         : 96 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████               ]  49.00%
#> Spots         : 98 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████               ]  50.00%
#> Spots         : 100 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████               ]  51.00%
#> Spots         : 102 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████              ]  52.00%
#> Spots         : 104 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████              ]  53.00%
#> Spots         : 106 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████              ]  54.00%
#> Spots         : 108 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████              ]  55.00%
#> Spots         : 110 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████             ]  56.00%
#> Spots         : 112 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████             ]  57.00%
#> Spots         : 114 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████             ]  58.00%
#> Spots         : 116 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████            ]  59.00%
#> Spots         : 118 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████            ]  60.00%
#> Spots         : 120 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████            ]  61.00%
#> Spots         : 122 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████           ]  62.00%
#> Spots         : 124 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████           ]  63.00%
#> Spots         : 126 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████           ]  64.00%
#> Spots         : 128 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████          ]  65.00%
#> Spots         : 130 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████          ]  66.00%
#> Spots         : 132 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████          ]  67.00%
#> Spots         : 134 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████          ]  68.00%
#> Spots         : 136 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████         ]  69.00%
#> Spots         : 138 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████         ]  70.00%
#> Spots         : 140 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████         ]  71.00%
#> Spots         : 142 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████        ]  72.00%
#> Spots         : 144 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████        ]  73.00%
#> Spots         : 146 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████        ]  74.00%
#> Spots         : 148 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████        ]  75.00%
#> Spots         : 150 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████████       ]  76.00%
#> Spots         : 152 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████████       ]  77.00%
#> Spots         : 154 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████████       ]  78.00%
#> Spots         : 156 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████      ]  79.00%
#> Spots         : 158 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████      ]  80.00%
#> Spots         : 160 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████      ]  81.00%
#> Spots         : 162 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████████     ]  82.00%
#> Spots         : 164 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████████     ]  83.00%
#> Spots         : 166 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████████     ]  84.00%
#> Spots         : 168 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████████    ]  85.00%
#> Spots         : 170 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████████    ]  86.00%
#> Spots         : 172 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████████    ]  87.00%
#> Spots         : 174 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████████    ]  88.00%
#> Spots         : 176 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████████████   ]  89.00%
#> Spots         : 178 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████████████   ]  90.00%
#> Spots         : 180 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [███████████████████████████   ]  91.00%
#> Spots         : 182 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████████  ]  92.00%
#> Spots         : 184 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████████  ]  93.00%
#> Spots         : 186 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████████  ]  94.00%
#> Spots         : 188 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [████████████████████████████  ]  95.00%
#> Spots         : 190 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████████████ ]  96.00%
#> Spots         : 192 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████████████ ]  97.00%
#> Spots         : 194 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [█████████████████████████████ ]  98.00%
#> Spots         : 196 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████████████]  99.00%
#> Spots         : 198 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> 
Creating spatial spots
#> [██████████████████████████████] 100.00%
#> Spots         : 200 / 200
#> Elapsed       : 00:00
#> ETA           : 00:00
#> Generated 200 spatial spots (4-12 cells each, median 8) from 1000 genes
#> Median cell types per spot: 2
#> Spot creation time: 0.25 secs
#> Total quasar_sim_bulk time: 0.25 secs
#> 

dim(spots$bulk_expression_profiles)  # 1000 x 200
#> [1] 1000  200
range(spots$cells_per_sample)        # within cells_per_spot_range
#> [1]  4 12
table(rowSums(spots$ground_truth_proportions > 0))
#> 
#>  1  2  3 
#> 74 85 41