# Predicting Interactomes from Co-Elution

## Documentation for package ‘PrInCE’ version 1.3.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

adjacency_matrix_from_data_frame | Create an adjacency matrix from a data frame
adjacency_matrix_from_list | Create an adjacency matrix from a list of complexes
aic | Model selection for Gaussian mixture models
build_gaussians | Deconvolve profiles into Gaussian mixture models
calculate_features | Calculate the default features used to predict interactions in PrInCE
calculate_precision | Calculate precision at each point in a sequence
check_gaussians | Check the format of a list of Gaussians
choose_gaussians | Fit a Gaussian mixture model to a co-elution profile
clean_profile | Preprocess a co-elution profile
clean_profiles | Preprocess a co-elution profile matrix
concatenate_features | Combine features across multiple replicates
co_apex | Calculate the co-apex score for every protein pair
detect_complexes | Detect significantly interacting complexes in a chromatogram matrix
filter_profiles | Filter a co-elution profile matrix
fit_curve | Output the fit curve for a given mixture of Gaussians
fit_gaussians | Fit a mixture of Gaussians to a chromatogram curve
gaussian_aic | Model selection for Gaussian mixture models
gaussian_aicc | Model selection for Gaussian mixture models
gaussian_bic | Model selection for Gaussian mixture models
gold_standard | Reference set of human protein complexes
impute_neighbors | Impute single missing values
is_unweighted | Test whether a network is unweighted
is_weighted | Test whether a network is weighted
kristensen | Interactome of HeLa cells
kristensen_gaussians | Fitted Gaussian mixture models for the 'kristensen' dataset
make_feature_from_data_frame | Create a feature vector for a classifier from a data frame
make_feature_from_expression | Create a feature vector from expression data
make_initial_conditions | Make initial conditions for curve fitting with a mixture of Gaussians
make_labels | Make labels for a classifier based on a gold standard
match_matrix_dimensions | Match the dimensions of a query matrix to a profile matrix
predict_ensemble | Predict interactions using an ensemble of classifiers
predict_interactions | Predict interactions given a set of features and examples
PrInCE | PrInCE: Prediction of Interactomes from Co-Elution
replace_missing_data | Replace missing data with median ± random noise
scott | Cytoplasmic interactome of Jurkat T cells during apoptosis
scott_gaussians | Fitted Gaussian mixture models for the 'scott' dataset
threshold_precision | Threshold interactions at a given precision cutoff