Proteomics Data Analysis and Modeling Tools

Documentation for package ‘promor’ version 0.2.1

aver_techreps	Compute average intensity
corr_plot	Correlation between technical replicates
covid_fit_df	Suvarna et al 2021 LFQ data (fit object)
covid_norm_df	Suvarna et al 2021 LFQ data (normalized)
create_df	Create a data frame of protein intensities
ecoli_fit_df	Cox et al 2014 LFQ data (fit object)
ecoli_norm_df	Cox et al 2014 LFQ data (normalized)
feature_plot	Visualize feature (protein) variation among conditions
filterbygroup_na	Filter proteins by group level missing data
find_dep	Identify differentially expressed proteins between groups
heatmap_de	Heatmap of differentially expressed proteins
heatmap_na	Visualize missing data
impute_na	Impute missing values
impute_plot	Visualize the impact of imputation
normalize_data	Normalize intensity data
norm_plot	Visualize the effect of normalization
onegroup_only	Proteins that are only expressed in a given group
performance_plot	Model performance plot
pre_process	Pre-process protein intensity data for modeling
rem_feature	Remove user-specified proteins (features) from a data frame
rem_sample	Remove user-specified samples
roc_plot	ROC plot
split_data	Split the data frame to create training and test data
test_models	Test machine learning models on test data
train_models	Train machine learning models on training data
varimp_plot	Variable importance plot
volcano_plot	Volcano plot