Plot Splines for Features Based on Top Table Information
plot_splines.RdThis function generates plots for each feature listed in the top table using spline interpolation for fitted values. It creates individual plots for each feature and combines them into a single composite plot. The function is internal and not exported.
Usage
plot_splines(
top_table,
data,
meta,
X,
time_unit_label,
plot_info,
adj_pthreshold,
replicate_column,
level
)Arguments
- top_table
A dataframe containing the indices and names of features, along with their statistical metrics such as intercepts and spline coefficients.
- data
A matrix or dataframe containing the raw data values for each feature.
- meta
A dataframe containing metadata for the data, including time points.
- X
The limma design matrix that defines the experimental conditions.
- time_unit_label
A string shown in the plots as the unit for the time, such as min or hours.
- plot_info
List containing the elements y_axis_label (string), time_unit (string), treatment_labels (character vector), treatment_timepoints (integer vector). All can also be NA. This list is used to add this info to the spline plots. time_unit is used to label the x-axis, and treatment_labels and -timepoints are used to create vertical dashed lines, indicating the positions of the treatments (such as feeding, temperature shift, etc.).
- adj_pthreshold
Double > 0 and < 1 specifying the adj. p-val threshold.
- replicate_column
String specifying the column of the meta dataframe that contains the labels of the replicate measurents. When that is not given, this argument is NULL.