Help for package GeneScape

Type:

Package

Title:

Simulation of Single Cell RNA-Seq Data with Complex Structure

Version:

1.0

Date:

2023-6-4

Maintainer:

Qi Gao <qi.gao@duke.edu>

Description:

Simulating single cell RNA-seq data with complicated structure. This package is developed based on the Splat method (Zappia, Phipson and Oshlack (2017) <doi:10.1186/s13059-017-1305-0>). 'GeneScape' incorporates additional features to simulate single cell RNA-seq data with complicated differential expression and correlation structures, such as sub-cell-types, correlated genes (pathway genes) and hub genes.

Encoding:

UTF-8

License:

GPL (≥ 3)

Imports:

MASS (≥ 7.3-53.1), corpcor (≥ 1.6.10), stats

RoxygenNote:

7.2.3

NeedsCompilation:

Packaged:

2023-06-13 01:46:17 UTC; qg

Author:

Qi Gao [aut, cre]

Repository:

CRAN

Date/Publication:

2023-06-13 09:00:09 UTC

GeneScape

Description

This function simulate single cell RNAseq data with complicated differential expression and correlation structure.

Usage

GeneScape(
  nCells = 6000,
  nGroups = NULL,
  groups = NULL,
  lib.size.loc = 9.3,
  lib.size.scale = 0.25,
  de.fc.mat = NULL,
  nGenes = 5000,
  gene.mean.shape = 0.3,
  gene.mean.rate = 0.15,
  gene.means = NULL,
  de.n = 50,
  de.share = NULL,
  de.id = NULL,
  de.fc.loc = 0.7,
  de.fc.scale = 0.2,
  add.sub = FALSE,
  sub.major = NULL,
  sub.prop = 0.1,
  sub.group = NULL,
  sub.de.n = 20,
  sub.de.id = NULL,
  sub.de.common = FALSE,
  sub.de.fc.loc = 0.7,
  sub.de.fc.scale = 0.2,
  add.cor = FALSE,
  cor.n = 4,
  cor.size = 20,
  cor.cor = 0.7,
  cor.id = NULL,
  band.width = 10,
  add.hub = FALSE,
  hub.n = 10,
  hub.size = 20,
  hub.cor = 0.4,
  hub.id = NULL,
  hub.fix = NULL,
  drop = FALSE,
  dropout.location = -2,
  dropout.slope = -1
)

Arguments

nCells

number of cells

nGroups

number of cell groups

groups

group information for cells

lib.size.loc

location parameter for library size (log-normal distribution)

lib.size.scale

scale parameter for library size (log-normal distribution)

de.fc.mat

differential expression fold change matrix, could be generated by this function

nGenes

number of genes

gene.mean.shape

shape parameter for mean expression level (Gamma distribution)

gene.mean.rate

rate parameter for mean expression level (Gamma distribution)

gene.means

mean gene expression levels

de.n

number of differentially expressed genes in each cell type. Should be a integer or a vector of length nGroups

number of shared DE genes between neighbor cell types. Should be a vector of length (nGroups - 1)

de.id

the index of genes that are DE across cell types. Should be a list of vectors. Each vector corresponds to a cell type. With non-null value of de.id, de.n and de.share would be ignored.

de.fc.loc

the location parameter for the fold change of DE genes. Should be a number, a vector of length nGroups

de.fc.scale

the scale parameter for fold change (log-normal distribution). Should be a number or a vector of length nGroups

add.sub

whether to add sub-cell-types

sub.major

the major cell types correspond to the sub-cell-types

sub.prop

proportion of sub-cell-types in the corresponding major cell type

sub.group

cell index for sub-cell-types. With non-null sub.group specified, sub.prop would be ignored.

sub.de.n

number of differentially expressed genes in each sub-cell-type compared to the corresponding major cell type. Should be a integer or a vector of length sub.major

sub.de.id

the index of additional differentially expressed genes between sub-cell-types and the corresponding major cell types

sub.de.common

whether the additional differential expression structure should be same for all sub-cell-types

sub.de.fc.loc

similar to de.fc.loc, but for addtional differentially expressed genes in sub-cell-types

sub.de.fc.scale

similar to de.fc.scale, but for addtional differentially expressed genes in sub-cell-types

add.cor

whether to add pathways (correlated genes)

cor.n

number of pathways included. Should be a integer.

cor.size

number of correlated genes (length of pathway). Should be a number or a vector of length cor.n

cor.cor

correlation parameters

cor.id

gene index of correlated (pathway) genes. Should be a list of vectors, with each vector represents a pathway. With non-null value of cor.id, cor.n would be ignored.

band.width

No correlation exists if distance of 2 genes are further than band_width in a pathway

add.hub

whether to add hub genes

hub.n

number of hub genes included. Should be a integer.

hub.size

number of genes correlated to the hub gene. Should be a number or a vector of length hub.n

hub.cor

correlation parameters between hub genes and their correlated genes

hub.id

gene index of hub genes. Should be a list of vectors. With non-null value of hub.id, hub.n would be ignored.

hub.fix

user defined genes correlated to hub genes (others are randomly selected). Should be a list of vectors of length hub.n or same as hub.id.

drop

whether to add dropout

dropout.location

dropout mid point (the mean expression level at which the probability is equal to 0.5, same as splat. Could be negative)

dropout.slope

how dropout proportion changes with increasing expression

Details

Compared to splat method in Splatter R package, this function can fix the number and position of differentially expressed genes, have more complicated differential expression structure, add sub-cell-types, correlated genes (AR(1) correlation structure with bound, mimicking pathways) and hub genes.

Value

A list of observed data, true data (without dropout), differential expression rate and hub gene indices.

References

Zappia, L., Phipson, B., & Oshlack, A. (2017). Splatter: Simulation of single-cell RNA sequencing data. Genome Biology, 18(1). https://doi.org/10.1186/s13059-017-1305-0

Examples

set.seed(1)
data <- GeneScape()

fcsim

Description

This function similate differential expression fold change level

Usage

fcsim(n.gene, de.id, fc.loc, fc.scale)

Arguments

n.gene

total number of genes

de.id

index of differentially expressed genes

fc.loc

location parameter for fold change (log-normal distribution)

fc.scale

scale parameter for fold change (log-normal distribution)

References

Zappia, L., Phipson, B., & Oshlack, A. (2017). Splatter: Simulation of single-cell RNA sequencing data. Genome Biology, 18(1). https://doi.org/10.1186/s13059-017-1305-0