Closed QinglinMei closed 3 years ago
Hi @QinglinMei
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The DESCRIPTION file for this package is:
Package: RCSL
Version: 0.99.0
Date: 2021-04-01
Title: Rank Constrained Similarity Learning for single cell RNA sequencing data
Description: A novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.
Authors@R: c(
person(given = "Qinglin", family = "Mei", email = "meiqinglinkf@163.com", role = c("cre","aut")),
person(given = "Guojun", family = "Li", email = "guojunsdu@gmail.com", role = "fnd"),
person(given = "Zhengchang", family = "Su", email = "zcsu@uncc.edu", role = "fnd")
)
URL: https://github.com/QinglinMei/RCSL
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
biocViews: SingleCell, Software, Clustering, DimensionReduction,
RNASeq, Visualization, Sequencing
Suggests: knitr, rmarkdown, mclust, RcppAnnoy
VignetteBuilder: knitr
Imports:
RcppAnnoy,
igraph
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CMD check on 0.99.91 gives me the following, would you check please?
The error most likely occurred in:
> ### Name: PlotMST
> ### Title: Plot the visualization of constructed Minimum Spanning Tree
> ### based on the clustering results of RCSL
> ### Aliases: PlotMST
>
> ### ** Examples
>
> gfData <- GenesFilter(yan)
> TrueLabel <- ann$cell_type1
> res_SimS <- SimS(gfData)
Calculate the Spearman correlation
Calculate the Nerighbor Representation
Find neighbors by KNN(Euclidean)
> C <- EstClusters(res_SimS$drData,res_SimS$S)
======== Calculate maximal strongly connected components ========
======== Calculate maximal strongly connected components ========
======== Calculate maximal strongly connected components ========
> res_BDSM <- BDSM(res_SimS$S,C)
======== Calculate maximal strongly connected components ========
> PlotMST(res_SimS$drData,res_BDSM$y,TrueLabel)
Error in geom_point(data = reducedData, aes(x = X1, y = X2, color = label), :
could not find function "geom_point"
Even in Rstudio, if I add library(ggplot2) before attempting example(PlotMST), the plot that I get is not what you intend. I get
by introducing plotly::ggplotly, where transparency is better supported, I get
Please run your example in command-line R and try to set the graphics parameters so a reasonable display is produced in this bare-bones setup. Or advise the user on the transparency-capable visualization approach to be used.
I see you are passing check on the builder but on my machine
> example(PlotMST)
PltMST> gfData <- GenesFilter(yan)
PltMST> TrueLabel <- ann$cell_type1
PltMST> res_SimS <- SimS(gfData)
Calculate the Spearman correlation
Calculate the Nerighbor Representation
Find neighbors by KNN(Euclidean)
PltMST> C <- EstClusters(res_SimS$drData,res_SimS$S)
======== Calculate maximal strongly connected components ========
======== Calculate maximal strongly connected components ========
======== Calculate maximal strongly connected components ========
PltMST> res_BDSM <- BDSM(res_SimS$S,C)
======== Calculate maximal strongly connected components ========
PltMST> PlotMST(res_SimS$drData,res_BDSM$y,TrueLabel)
Error in geom_point(data = reducedData, aes(x = X1, y = X2, color = label), :
could not find function "geom_point"
Enter a frame number, or 0 to exit
1: example(PlotMST)
2: source(tf, local, echo = echo, prompt.echo = paste0(prompt.prefix, getOptio
3: withVisible(eval(ei, envir))
4: eval(ei, envir)
5: eval(ei, envir)
6: Rex423963b68e6b#13: PlotMST(res_SimS$drData, res_BDSM$y, TrueLabel)
Selection: 0
> library(ggplot2)
1/1 packages newly attached/loaded, see sessionInfo() for details.
> PlotMST(res_SimS$drData,res_BDSM$y,TrueLabel)
In other words the example needs to have library(ggplot2) added.
Would you please look at this?
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