R: An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer

# An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer

## Documentation for package ‘GSgalgoR’ version 1.22.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

GSgalgoR-package | GSgalgoR: A bi-objective evolutionary meta-heuristic to identify robust transcriptomic classifiers associated with patient outcome across multiple cancer types.
calculate_distance | Functions to calculate distance matrices using cpu computing
calculate_distance_euclidean_cpu | Functions to calculate distance matrices using cpu computing
calculate_distance_pearson_cpu | Functions to calculate distance matrices using cpu computing
calculate_distance_spearman_cpu | Functions to calculate distance matrices using cpu computing
calculate_distance_uncentered_cpu | Functions to calculate distance matrices using cpu computing
callback_base_report | Print basic info per generation
callback_base_return_pop | A base callback function that returns a galgo.Obj
callback_default | A default call_back function that does nothing.
callback_no_report | Print minimal information to the user about galgo execution.
classify_multiple | Classify samples from multiple centroids
cluster_algorithm | Wrapper function to perform partition around medioids (PAM) for GalgoR
cluster_classify | Distance to centroid classifier function
cosine_similarity | Function for calculating the cosine similarity
create_centroids | Create Centroids
galgo | GSgalgoR main function
galgo.Obj | Galgo Object class
galgo.Obj-class | Galgo Object class
GSgalgoR | GSgalgoR: A bi-objective evolutionary meta-heuristic to identify robust transcriptomic classifiers associated with patient outcome across multiple cancer types.
k_centroids | Function to calculate the centroids of different groups (classes)
non_dominated_summary | Summary of the non dominated solutions
plot_pareto | Plot pareto front from an galgo.Obj
select_distance | Functions to calculate distance matrices using cpu computing
surv_fitness | Survival fitness function using the Restricted Mean Survival Time (RMST) of each group
to_dataframe | Convert galgo.Obj to data.frame
to_list | Convert galgo.Obj to list