intensity2circle: Infer Angles for Single-cell Samples Using Fluorescence... In jhsiao999/peco: A Supervised Approach for Predicting Cell Cycle Progression Using Single-Cell RNA-seq Data

Description

We use FUCCI intensities to infer the position of the cells in cell cycle progression. The result is a vector of angles on a unit circle corresponding to the positions of the cells in cell cycle progression.

Usage

 `1` ```intensity2circle(mat, plot.it = FALSE, method = c("trig", "algebraic")) ```

Arguments

 `mat` A matrix with two columns giving summarized fluorescence intensities. Rows correspond to samples. `plot.it` `TRUE` or `FALSE`. If ```plot.it = TRUE```, plot the fitted results. `method` The method used to fit the circle. ```method = "trig"``` uses trignometry to transform intensity measurements from cartesian coordinates to polar coordinates; ```method = "algebraic"``` uses an algebraic approach for circle fitting, implemented in the `conicfit` package.

Value

The inferred angles on a unit circle based on the input intensity measurements.

Joyce Hsiao

Examples

 ```1 2 3 4 5 6 7 8``` ```library(SingleCellExperiment) data(sce_top101genes) # Compute FUCCI scores---the log10-transformed sum of intensities # corrected for background noise. ints <- colData(sce_top101genes)[,c("rfp.median.log10sum.adjust", "gfp.median.log10sum.adjust")] intensity2circle(ints, plot.it=TRUE, method = "trig") ```

jhsiao999/peco documentation built on Nov. 21, 2020, 5:34 p.m.