-
Notifications
You must be signed in to change notification settings - Fork 0
/
README.Rmd
85 lines (59 loc) · 4.02 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
---
output: github_document
#always_allow_html: yes
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
#collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# interactmapper
<!-- badges: start -->
[](https://travis-ci.org/octaviamd/interactmapper?branch=master)
[](https://ci.appveyor.com/project/octaviamd/interact-mapper)
<!-- badges: end -->
The goal of interactmapper is to make analyzing dimension reduction plots more intuitive and user-friendly, by allowing users to overlay features of interest of the dataset onto the plot via color
## Installation
You can install the released version of interactmapper from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("interactmapper")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("octaviamd/interactmapper")
```
## interact_qual
Here is a walkthrough of how to use the different functions in the interactmapper package. For greater ease, the `iris` dataset will be used to show how the functions can be used. Illustrative gifs showing the kinds of interactive plots that can be generated will be provided soon!
The `interact_qual` function is best suited to represent qualitative features of your data (ex: race/ethnicity of patients, smoker status, treatment groups, cell types, etc...). In the example below, the dimension reduction method `UMAP` is applied to the `iris` dataset, which is plotted and color coded based on `iris$Species`, representing the Species of each iris represented in the dataset. Upon mouse hover, the qualitative feature of interest is presented in a text box, as well as the sample name.
``` r
library(interactmapper)
#interactmapper::interact_qual(iris[,1:4], iris$Species, "UMAP")
```
<img src="man/figures/interact_qual_iris_plot.png" width="100%" />
The plot generated by `interact_qual` also has a helpful side-bar that displays all of the variant options of your qualitative feature of interest, and allows you to select which variant(s) you want represented on your plot. By clicking on the feature option names, you can either show or hide the points associated with those features. In the UMAP plot below, setosa and versicolor have been hidden in order to have a better look at the virginica irises.
<img src="man/figures/interact_qual_select.png" width="100%" />
Here is an example of applying PCA instead of UMAP to the same data, looking at the same feature, `iris$Species`.
``` r
#interactmapper::interact_qual(iris[,1:4], iris$Species, "PCA")
```
<img src="man/figures/interact_qual_pca.png" width="100%" />
## interact_quant
The `interact_quant` function is used to represent features that are quantitative in nature (gene expression, DNA methylation, height, etc...).
``` r
#interact_quant(iris[,1:4], "Petal Width", iris[,4], "UMAP")
```
Below you can see an example of the interact_quant function being applied to color the datapoints of the plot based on the feature of interest, the petal width of the irises. Upon hovering over a point, a pop-up box displaying the Sample Name and the feature of interest appears.
<img src="man/figures/iris_quant.png" width="100%" />
The color palette used can be chosen from a range of available palettes from the package [colourvalues](https://github.com/SymbolixAU/colourvalues) displayed below based on your preferences to best suit your data and how to display it:
<img src="man/figures/color_options.png" width="100%" />
The default palette option is "matlablike_2". Here is the same plot, only with the palette "viridis".
``` r
#interactmapper::interact_quant(iris[,1:4], "Petal Width", iris[,4], "UMAP", "viridis")
```
You’ll still need to render `README.Rmd` regularly, to keep `README.md`
up-to-date.