View source: R/Demuxlet_Tools.R
demux.SNP.summary | R Documentation |
Plots the number of SNPs sequenced per droplet
demux.SNP.summary(
object,
group.by = "Lane",
color.by = group.by,
plots = c("jitter", "boxplot"),
boxplot.color = "grey30",
add.line = 50,
min = 0,
...
)
object |
A Seurat or SingleCellExperiment object |
group.by |
String "name" of a metadata to use for grouping values. Default is "Lane". |
color.by |
String "name" of a metadata to use for coloring.
Default is whatever was provided to |
plots |
String vector which sets the types of plots to include: possibilities = "jitter", "boxplot", "vlnplot", "ridgeplot". NOTE: The order matters, so use c("back","middle","front") when inputing multiple to put them in the order you want. |
boxplot.color |
The color of the lines of the boxplot. |
add.line |
numeric value(s) where a dashed horizontal line should go. Default = 50, a high confidence minimum number of SNPs per cell for highly accurate demuxlet sample deconvolution. |
min |
numeric value which sets the minimum value shown on the y-axis. |
... |
extra arguments passed to |
This function is a wrapper that essentially runs dittoPlot
("demux.N.SNP")
with a few modified defaults.
The altered defaults:
Data is grouped and colored by the "Lane" metadata (unless group.by
or color.by
are adjusted otherwise).
Data is displayed as boxplots with gray lines on top of dots for individual cells (unless plots
or boxplot.color
are adjusted otherwise).
The plot is set to have minimum y axis value of zero (unless min
is adjusted otherwise).
A dashed line is added at the value 50, a very conservative minimum number of SNPs for high confidence sample calls (unless add.line
is adjusted otherwise).
A ggplot, made with dittoPlot
showing a summary of how many SNPs were available to Demuxlet for each cell of a dataset.
Alternatively, a plotly object if data.hover = TRUE
is provided.
Alternatively, list containing a ggplot and the underlying data as a dataframe if data.out = TRUE
is provided.
Daniel Bunis
demux.calls.summary
for plotting the number of sample annotations assigned within each lane.
This is the other Demuxlet-associated QC visualization included with dittoSeq.
dittoPlot
, as demux.SNP.summary
is essentially just a dittoPlot
wrapper.
importDemux
, for how to import relevant demuxlet information as metadata.
Kang et al. Nature Biotechnology, 2018 https://www.nature.com/articles/nbt.4042 for more information about the demuxlet cell-sample deconvolution method.
example(importDemux, echo = FALSE)
demux.SNP.summary(myRNA)
#Function wraps dittoPlot. See dittoPlot docs for more examples
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