tidygate (version 1.0.14)

gate_chr: Label points within a scatter plot drawing a gate

Description

gate() takes as input a `tbl` formatted as | <DIMENSION 1> | <DIMENSION 2> | <...> | and calculates the rotated dimensional space of the feature value.

Usage

gate_chr(
  .dim1,
  .dim2,
  .color = NULL,
  .shape = NULL,
  .size = NULL,
  opacity = 1,
  how_many_gates = 1,
  .group_by = NULL,
  gate_list = NULL,
  ...
)
gate_int(
  .dim1,
  .dim2,
  .color = NULL,
  .shape = NULL,
  .size = NULL,
  opacity = 1,
  how_many_gates = 1,
  .group_by = NULL,
  gate_list = NULL,
  ...
)

Value

An character vector, with "0" for elements outside gates and "1..N" for the elements inside the N gates.

An integer vector, with 0 for elements outside gates and 1..N for the elements inside the N gates.

Arguments

.dim1

A column symbol. The x dimension

.dim2

A column symbol. The y dimension

.color

A column symbol. Colour of points

.shape

A column symbol. Shape of points

.size

A column symbol. Size of points

opacity

A number between 0 and 1. The opacity level of the data points

how_many_gates

An integer. The number of gates to label

.group_by

A column symbol. The column that is used to calculate distance (i.e., normally genes)

gate_list

A list of gates. It is returned by gate function as attribute \"gate\". If you want to create this list yourself, each element of the list is a data frame with x and y columns. Each row is a coordinate. The order matter.

...

Further parameters passed to the function gatepoints::fhs

Details

lifecycle::badge("maturing")

This function allow the user to label data points in inside one or more 2D gates. This package is based on on the package gatepoints.

Examples

# Standard use - interactive

if(interactive()){

  tidygate::tidygate_data  %>%
    distinct(`ct 1` , `ct 2`, Dim1, Dim2) %>%
    mutate(gate = gate_chr( Dim1, Dim2)) 

}

library(magrittr)
library(dplyr)

# Standard use - programmatic
res_distinct =
 tidygate::tidygate_data  %>%
 distinct(`ct 1` , `ct 2`, Dim1, Dim2) %>%
 mutate(gate = gate_chr( Dim1, Dim2,gate_list = tidygate::gate_list)) 

# Grouping - programmatic
res =
 tidygate::tidygate_data  %>%
   mutate(gate = gate_chr( 
     Dim1, Dim2,
     .group_by = c(`ct 1` , `ct 2`), 
     gate_list = tidygate::gate_list
   ))