diff --git a/DESCRIPTION b/DESCRIPTION
index 643e58df09a198ed577a182b388f238a167739a1..8852f51948ba007b2c6c414ae87ce6351f6540cd 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,28 +1,53 @@
Package: splatter
Type: Package
Title: Simple Simulation of Single-cell RNA Sequencing Data
-Version: 0.99.7
-Date: 2016-12-29
+Version: 0.99.8
+Date: 2017-01-23
Author: Luke Zappia
-Authors@R: c(person("Luke", "Zappia", role = c("aut", "cre"), email =
- "luke.zappia@mcri.edu.au"), person("Belinda", "Phipson", role =
- c("aut"), email = "belinda.phipson@mcri.edu.au"),
- person("Alicia", "Oshlack", role = c("aut"), email =
- "alicia.oshlack@mcri.edu.au"))
+Authors@R:
+ c(person("Luke", "Zappia", role = c("aut", "cre"),
+ email = "luke.zappia@mcri.edu.au"),
+ person("Belinda", "Phipson", role = c("aut"),
+ email = "belinda.phipson@mcri.edu.au"),
+ person("Alicia", "Oshlack", role = c("aut"),
+ email = "alicia.oshlack@mcri.edu.au"))
Maintainer: Luke Zappia <luke.zappia@mcri.edu.au>
-Description: Splatter is a package for the simulation of single-cell
- RNA sequencing count data. It provides a simple interface for
- creating complex simulations that are reproducible and
- well-documented.
+Description: Splatter is a package for the simulation of single-cell RNA
+ sequencing count data. It provides a simple interface for creating complex
+ simulations that are reproducible and well-documented.
License: GPL-3 + file LICENSE
LazyData: TRUE
-Depends: R (>= 3.4), scater
-Imports: fitdistrplus, edgeR, stats, locfit, akima, Biobase, checkmate,
- methods, utils, matrixStats, ggplot2, scales
-Suggests: testthat, scran, progress, lme4, pscl, scDD, knitr,
- rmarkdown, BiocStyle, covr, S4Vectors, SummarizedExperiment
-biocViews: SingleCell, RNASeq, Transcriptomics, GeneExpression,
- Sequencing, Software
+Depends:
+ R (>= 3.4),
+ scater
+Imports:
+ fitdistrplus,
+ edgeR,
+ stats,
+ locfit,
+ akima,
+ Biobase,
+ checkmate,
+ methods,
+ utils,
+ matrixStats,
+ ggplot2,
+ scales
+Suggests:
+ testthat,
+ scran,
+ progress,
+ lme4,
+ pscl,
+ scDD,
+ knitr,
+ rmarkdown,
+ BiocStyle,
+ covr,
+ S4Vectors,
+ SummarizedExperiment
+biocViews: SingleCell, RNASeq, Transcriptomics, GeneExpression, Sequencing,
+ Software
URL: https://github.com/Oshlack/splatter
BugReports: https://github.com/Oshlack/splatter/issues
RoxygenNote: 5.0.1
diff --git a/NEWS.md b/NEWS.md
index 8e5aaade37f90a6f549ad2cd1a1d7b541cd4ba73..8611fd50b5d4c21fd161d4f70749e1a88f0faf2a 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,7 @@
+# 0.99.8
+
+* Fix bug that meant non-linear path factors weren't stored in output
+
# 0.99.7
* Small changes to avoid NOTEs and reduce check time
diff --git a/R/splat-simulate.R b/R/splat-simulate.R
index bccfb6ac33ed8d974bdc40318f898b93197c38ec..4e3efb0df119ceaf49aa566a37d355e3fdf32c74 100644
--- a/R/splat-simulate.R
+++ b/R/splat-simulate.R
@@ -53,27 +53,29 @@
#' \describe{
#' \item{Gene}{Unique gene identifier.}
#' \item{BaseGeneMean}{The base expression level for that gene.}
-#' \item{OutlierFactor}{Expression outlier factor for that gene. Values
-#' of 1 indicate the gene is not an expression outlier.}
+#' \item{OutlierFactor}{Expression outlier factor for that gene.
+#' Values of 1 indicate the gene is not an expression outlier.}
#' \item{GeneMean}{Expression level after applying outlier factors.}
-#' \item{DEFac[Group]}{The differential expression factor for each gene
-#' in a particular group. Values of 1 indicate the gene is not
+#' \item{DEFac[Group]}{The differential expression factor for each
+#' gene in a particular group. Values of 1 indicate the gene is not
#' differentially expressed.}
#' \item{GeneMean[Group]}{Expression level of a gene in a particular
#' group after applying differential expression factors.}
+#' \item{SigmaFac[Path]}{Factor applied to genes that have
+#' non-linear changes in expression along a path.}
#' }
#' }
#' \item{\code{assayData}}{
#' \describe{
-#' \item{BaseCellMeans}{The expression of genes in each cell adjusted for
-#' expected library size.}
-#' \item{BCV}{The Biological Coefficient of Variation for each gene in
-#' each cell.}
-#' \item{CellMeans}{The expression level of genes in each cell adjusted
-#' for BCV.}
+#' \item{BaseCellMeans}{The expression of genes in each cell
+#' adjusted for expected library size.}
+#' \item{BCV}{The Biological Coefficient of Variation for each gene
+#' in each cell.}
+#' \item{CellMeans}{The expression level of genes in each cell
+#' adjusted for BCV.}
#' \item{TrueCounts}{The simulated counts before dropout.}
-#' \item{Dropout}{Logical matrix showing which values have been dropped
-#' in which cells.}
+#' \item{Dropout}{Logical matrix showing which values have been
+#' dropped in which cells.}
#' }
#' }
#' }
@@ -449,6 +451,15 @@ splatSimPathCellMeans <- function(sim, params) {
group.names <- unique(groups)
exp.lib.sizes <- pData(sim)$ExpLibSize
+ # Generate non-linear path factors
+ for (idx in seq_along(path.from)) {
+ # Select genes to follow a non-linear path
+ is.nonlinear <- as.logical(rbinom(nGenes, 1, path.nonlinearProb))
+ sigma.facs <- rep(0, nGenes)
+ sigma.facs[is.nonlinear] <- path.sigmaFac
+ fData(sim)[[paste0("SigmaFacPath", idx)]] <- sigma.facs
+ }
+
# Generate paths. Each path is a matrix with path.length columns and
# nGenes rows where the expression from each genes changes along the path.
path.steps <- lapply(seq_along(path.from), function(idx) {
@@ -462,16 +473,13 @@ splatSimPathCellMeans <- function(sim, params) {
# Find the means at the end position
means.end <- fData(sim)[[paste0("GeneMeanPath", idx)]]
- # Select genes to follow a non-linear path
- is.nonlinear <- as.logical(rbinom(nGenes, 1, path.nonlinearProb))
- sigma.facs <- rep(0, nGenes)
- sigma.facs[is.nonlinear] <- path.sigmaFac
+ # Get the non-linear factors
+ sigma.facs <- fData(sim)[[paste0("SigmaFacPath", idx)]]
+
# Build Brownian bridges from start to end
steps <- buildBridges(means.start, means.end, n = path.length[idx],
sigma.fac = sigma.facs)
- fData(sim)[[paste0("SigmaFacPath", idx)]] <- sigma.facs
-
return(t(steps))
})
diff --git a/man/splatSimulate.Rd b/man/splatSimulate.Rd
index a9b2424933d851b2aef58472614a452b40787193..d65b54a2c841d5243d749f70fa0db9f32b8bb526 100644
--- a/man/splatSimulate.Rd
+++ b/man/splatSimulate.Rd
@@ -78,27 +78,29 @@ slots. This additional information includes:
\describe{
\item{Gene}{Unique gene identifier.}
\item{BaseGeneMean}{The base expression level for that gene.}
- \item{OutlierFactor}{Expression outlier factor for that gene. Values
- of 1 indicate the gene is not an expression outlier.}
+ \item{OutlierFactor}{Expression outlier factor for that gene.
+ Values of 1 indicate the gene is not an expression outlier.}
\item{GeneMean}{Expression level after applying outlier factors.}
- \item{DEFac[Group]}{The differential expression factor for each gene
- in a particular group. Values of 1 indicate the gene is not
+ \item{DEFac[Group]}{The differential expression factor for each
+ gene in a particular group. Values of 1 indicate the gene is not
differentially expressed.}
\item{GeneMean[Group]}{Expression level of a gene in a particular
group after applying differential expression factors.}
+ \item{SigmaFac[Path]}{Factor applied to genes that have
+ non-linear changes in expression along a path.}
}
}
\item{\code{assayData}}{
\describe{
- \item{BaseCellMeans}{The expression of genes in each cell adjusted for
- expected library size.}
- \item{BCV}{The Biological Coefficient of Variation for each gene in
- each cell.}
- \item{CellMeans}{The expression level of genes in each cell adjusted
- for BCV.}
+ \item{BaseCellMeans}{The expression of genes in each cell
+ adjusted for expected library size.}
+ \item{BCV}{The Biological Coefficient of Variation for each gene
+ in each cell.}
+ \item{CellMeans}{The expression level of genes in each cell
+ adjusted for BCV.}
\item{TrueCounts}{The simulated counts before dropout.}
- \item{Dropout}{Logical matrix showing which values have been dropped
- in which cells.}
+ \item{Dropout}{Logical matrix showing which values have been
+ dropped in which cells.}
}
}
}