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Merge pull request #592 from satijalab/release/4.0.4
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Prep for release of 4.0.4
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mojaveazure authored Aug 20, 2021
2 parents 03879ed + 3c1dbf6 commit c1591c0
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4 changes: 2 additions & 2 deletions DESCRIPTION
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Package: Seurat
Version: 4.0.3.9015
Date: 2021-08-09
Version: 4.0.4
Date: 2021-08-19
Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
Authors@R: c(
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4 changes: 2 additions & 2 deletions NEWS.md
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## Unreleased
## Seurat 4.0.4 (2020-08-19)
## Added
- Add `reduction` parameter to `BuildClusterTree()` ([#4598](https://github.com/satijalab/seurat/issues/4598))
- Add DensMAP option to `RunUMAP()` ([#4630](https://github.com/satijalab/seurat/pull/4630))
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- Fix issue in SingleCellExperiment conversion where the mainExp would not be set properly
- Fix for default dispersion info displayed in `VariableFeaturePlot()`

## Seurat 4.0.3 (2020-06-10)`
## Seurat 4.0.3 (2020-06-10)
## Added
- Add `jitter` parameter to `FeatureScatter()`

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2 changes: 1 addition & 1 deletion R/dimensional_reduction.R
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Expand Up @@ -1514,7 +1514,7 @@ RunUMAP.Graph <- function(
numeric_version(x = "0.5.0")) {
umap.args <- c(umap.args, list(
densmap = densmap,
densmap_kwds = densmap_kwds,
densmap_kwds = densmap.kwds,
output_dens = FALSE
))
}
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10 changes: 5 additions & 5 deletions cran-comments.md
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# Seurat v4.0.3
# Seurat v4.0.4

## Test environments
* local Ubuntu 20.04 install, R 4.0.5
* local Ubuntu 20.04 install, R 4.1.0
* Ubuntu 16.04.6 (on travis-ci), R 4.0.0, R devel
* macOS 10.13.6 (on travis-ci), R 4.0.2
* Windows Server 2012 R2 (on AppVeyor), R 4.1.0 Patched
* win-builder (release, devel)
* win-builder (oldrelease, release, devel)

## R CMD check results
There were no ERRORs, WARNINGs, or NOTEs
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There is one package that depends on Seurat: tidyseurat; this update does not impact its functionality

There are seven packages that imports Seurat: CDSeq, DUBStepR, rPanglaoDB, scMappR, Signac, SignacX, and SoupX; this update does not impact their functionality
There are eight packages that import Seurat: CDSeq, DUBStepR, PhitestR, rPanglaoDB, scMappR, Signac, SignacX, and SoupX; this update does not impact their functionality

There are ten packages that suggest Seurat: BisqueRNA, ClustAssess, clustree, conos, DIscBIO, dyngen, harmony, rliger, Rmagic, VAM; this update does not impact their functionality.
There are ten packages that suggest Seurat: BisqueRNA, ClustAssess, clustree, conos, DIscBIO, dyngen, harmony, rliger, Rmagic, and VAM; this update does not impact their functionality.
4 changes: 3 additions & 1 deletion vignettes/spatial_vignette.Rmd
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Expand Up @@ -144,7 +144,9 @@ SpatialFeaturePlot(brain, features = c("Hpca", "Ttr"))
library(ggplot2)
plot <- SpatialFeaturePlot(brain, features = c("Ttr")) +
theme(legend.text = element_text(size = 0), legend.title = element_text(size = 20), legend.key.size = unit(1, "cm"))
ggsave(filename = "../output/images/spatial_vignette_ttr.jpg", height = 7, width = 12, plot = plot, quality = 50)
jpeg(filename = "../output/images/spatial_vignette_ttr.jpg", height = 700, width = 1200, quality = 50)
print(plot)
dev.off()
```

The default parameters in Seurat emphasize the visualization of molecular data. However, you can also adjust the size of the spots (and their transparency) to improve the visualization of the histology image, by changing the following parameters:
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