tidygate
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Label elements within user drawn gates
tidygate: add gate information to your tibble
Please have a look also to
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nanny for tidy high-level data analysis and manipulation
-
tidyHeatmap for producing heatmaps following tidy principles
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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