| Title: | Extract Cell Density and Nearest Distance Based on 'PerkinElmer InForm' Software Output |
| Version: | 1.0.5 |
| Date: | 2018-07-31 |
| Author: | Minyu Wang,Yu Sun,Yu-Kuan Huang |
| Maintainer: | Minyu Wang <minyu.wang@petermac.org> |
| Description: | Reads the output of the 'PerkinElmer InForm' software http://www.perkinelmer.com/product/inform-cell-analysis-one-seat-cls135781. In addition to cell-density count, it can derive statistics of intercellular spatial distance for each cell-type. |
| Depends: | R (≥ 3.4) |
| Suggests: | knitr, rmarkdown,dplyr |
| VignetteBuilder: | knitr |
| Imports: | gtools,stats,stringr,utils |
| License: | GPL-2 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 6.1.0 |
| NeedsCompilation: | no |
| Packaged: | 2018-08-20 03:39:33 UTC; wangminyu |
| Repository: | CRAN |
| Date/Publication: | 2018-08-20 11:30:03 UTC |
Find the nearest neighbour (NN) given a cell and a group of cells;
Description
Find the nearest neighbour (NN) given a cell and a group of cells;
Usage
findNN(cell, cellList, XY_LABELS = c("Cell.X.Position",
"Cell.Y.Position"))
Arguments
cell |
An object cell |
cellList |
A list of cell types to be calculated for |
XY_LABELS |
x and y positions of the cell |
Value
The Nearest Neibour Cell distance and calculate the distance
Examples
Cell.X.Position=sample (1:100,1)
Cell.Y.Position=sample (1:100,1)
Tcell=data.frame(Cell.X.Position,Cell.Y.Position)
Cell.X.Position=sample(1:500,5,replace=TRUE)
Cell.Y.Position=sample(1:500,5,replace=TRUE)
Tumor.cells=data.frame(Cell.X.Position,Cell.Y.Position)
findNN(Tcell,Tumor.cells,XY_LABELS=c('Cell.X.Position', 'Cell.Y.Position'))
Read a file and compute the NN through permutations;
Description
Read a file and compute the NN through permutations;
Usage
findNNs(filename, cell_names = NULL)
Arguments
filename |
the file to be processed |
cell_names |
A list of cell types |
Value
The Nearest Neibour Cell distance in the file
Get the count number of each phenotype for each tissue category
Description
Get the count number of each phenotype for each tissue category
Usage
getFileCount(dataFile)
Arguments
dataFile |
File path to the data file |
Value
a data frame summary of count
Extract the statistics from the result given by findNNs
Description
Extract the statistics from the result given by findNNs
Usage
procDist(distResult, thred = 30)
Arguments
distResult |
A distance result file from findNNs |
thred |
a threshold distance as cut-off |
Value
The statistics extracted from the distace result file
Examples
Cell.X.Position=sample(1:1000, 20, replace=TRUE)
Cell.Y.Position=sample(1:1000, 20, replace=TRUE)
distance = runif(20,min=0,max=100)
distResult = data.frame (Cell.X.Position,Cell.Y.Position,distance)
thred=30
procDist(distResult,thred)