fe: Feature engineer the data
In aef1004/cytotypr: Pipeline to Identify Cell Types from Cytometry Data
Description
Usage
Arguments
Value
Examples
Description
Feature engineer the data
Usage
1
fe(quantile_df, marker, marker_name)
Arguments
quantile_df
the dataframe that contains the list of cutoffs for each marker
marker
name of the marker column to feature engineer
marker_name
name of the marker column to feature engineer in quotes
Value
convert the marker data column into either a 0 for negative expression or 1 for positive expressoin
Examples
1
2
3
4
5
library(dplyr)
all_of(df_all_gated) %>%
select("Alexa Fluor 532-A") %>%
rename("CD3" = "Alexa Fluor 532-A") %>%
mutate(CD3 = fe(add_quantile, CD3, "CD3"))
aef1004/cytotypr documentation built on Dec. 25, 2021, 8:46 a.m.
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Description Usage Arguments Value Examples
Description
Feature engineer the data
Usage
1 | fe(quantile_df, marker, marker_name)
|
Arguments
quantile_df |
the dataframe that contains the list of cutoffs for each marker |
marker |
name of the marker column to feature engineer |
marker_name |
name of the marker column to feature engineer in quotes |
Value
convert the marker data column into either a 0 for negative expression or 1 for positive expressoin
Examples
1 2 3 4 5 | library(dplyr)
all_of(df_all_gated) %>%
select("Alexa Fluor 532-A") %>%
rename("CD3" = "Alexa Fluor 532-A") %>%
mutate(CD3 = fe(add_quantile, CD3, "CD3"))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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