stemangiola / tidygate

Label elements within user drawn gates

tidygate: add gate information to your tibble

Please have a look also to

• nanny for tidy high-level data analysis and manipulation

• tidyHeatmap for producing heatmaps following tidy principles

• tidybulk for tidy and modular transcriptomics analyses

Installation

# From Github
devtools::install_github("stemangiola/tidygate")

# From CRAN
install.package("tidygate")

What is tidygate

It interactively or programmately labels points within custom gates on two dimensions, according to tidyverse principles. The information is added to your tibble. It is based on the package gatepoints from Wajid Jawaid.

The main benefits are

• in interactive mode you can draw your gates on extensive ggplot-like scatter plots
• you can draw multiple gates
• you can save your gates and apply the programmatically.

Input

A tibble of this kind

dimension1	dimension2	annotations
chr or fctr	numeric	…

Step-by-step instructons for Rstudio

1) Execute the following code in the console panel

tidygate_gate <-
  tidygate_data %>%
  mutate( gate = gate_chr( Dim1, Dim2 ) )

2) look at the Viewer and draw a gate clicking at least three times on the plot

3) Click the finish button on the top-right corner, or press escape on your keyboard

The output tibble

tidygate_gate

## # A tibble: 2,240 x 9
##    group   hierarchy `ct 1`    `ct 2`    relation cancer_ID   Dim1    Dim2 gate 
##    <chr>       <dbl> <chr>     <chr>        <dbl> <chr>      <dbl>   <dbl> <chr>
##  1 adrenal         1 endothel… epitheli…    -1    ACC       -0.874 -0.239  0    
##  2 adrenal         1 endothel… fibrobla…    -1    ACC       -0.740  0.114  1    
##  3 adrenal         1 endothel… immune_c…    -1    ACC       -0.988  0.118  0    
##  4 adrenal         1 epitheli… endothel…     1    ACC        0.851  0.261  0    
##  5 adrenal         1 epitheli… fibrobla…     1    ACC        0.839  0.320  0    
##  6 adrenal         1 epitheli… immune_c…     1    ACC        0.746  0.337  0    
##  7 adrenal         1 fibrobla… endothel…     1    ACC        0.722 -0.0696 0    
##  8 adrenal         1 fibrobla… epitheli…    -1    ACC       -0.849 -0.317  0    
##  9 adrenal         1 fibrobla… immune_c…     0.52 ACC       -0.776 -0.383  0    
## 10 adrenal         1 immune_c… endothel…     1    ACC        0.980 -0.116  0    
## # … with 2,230 more rows

Gates are saved in a temporary file for later use

## [[1]]
##            x          y
## 1 -0.9380459  0.2784375
## 2 -0.9555544 -0.1695209
## 3 -0.3310857  0.2116150
## 
## [[2]]
##             x          y
## 1  0.01324749  0.2165648
## 2 -0.31065917 -0.1026984
## 3 -0.11514794 -0.2982161
## 4  0.48013998  0.1225183

Programmatic gating

We can use previously drawn gates to programmately add the gate column

tidygate_data %>%
  mutate( gate = gate_chr(
    Dim1, Dim2,
     # Pre-defined gates
    gate_list = my_gates
  ))

## # A tibble: 2,240 x 9
##    group   hierarchy `ct 1`    `ct 2`    relation cancer_ID   Dim1    Dim2 gate 
##    <chr>       <dbl> <chr>     <chr>        <dbl> <chr>      <dbl>   <dbl> <chr>
##  1 adrenal         1 endothel… epitheli…    -1    ACC       -0.874 -0.239  0    
##  2 adrenal         1 endothel… fibrobla…    -1    ACC       -0.740  0.114  1    
##  3 adrenal         1 endothel… immune_c…    -1    ACC       -0.988  0.118  0    
##  4 adrenal         1 epitheli… endothel…     1    ACC        0.851  0.261  0    
##  5 adrenal         1 epitheli… fibrobla…     1    ACC        0.839  0.320  0    
##  6 adrenal         1 epitheli… immune_c…     1    ACC        0.746  0.337  0    
##  7 adrenal         1 fibrobla… endothel…     1    ACC        0.722 -0.0696 0    
##  8 adrenal         1 fibrobla… epitheli…    -1    ACC       -0.849 -0.317  0    
##  9 adrenal         1 fibrobla… immune_c…     0.52 ACC       -0.776 -0.383  0    
## 10 adrenal         1 immune_c… endothel…     1    ACC        0.980 -0.116  0    
## # … with 2,230 more rows