Man pages for junyangq/multiSnpnet
Fit a sparse reduced rank regression model on large-scale SNP data and multivariate responses
| check_early_stopping_condition | Check if the early stopping condition is satisfied |
| check_if_metric_exists | Check if the training (or validation) set metric exists in... |
| coef_multisnpnet | Extract Coefficients from the Fitted Object or File |
| drop_bulky_stuff_in_fit_object | drop feature statistics and individual-level data |
| extract_all_metrics | Extract all weighted and unweighted metrics |
| extract_metrics | Extract metrics |
| extract_weight | Extract weights |
| extract_weighted_metrics | Extract weighted metrics |
| find_best_lambda_index | Select the "best" lambda index given the training (and... |
| find_prev_iter | Get the index of the previous iteration in a specified... |
| get_cb_colors | Generate color palette |
| get_non_NA_lines | Given a matrix, return non-NA lines |
| get_non_zero_coefficients | Extract the non-zero coefficients from the fit object |
| get_non_zero_coefficients_as_data_frame | Extract the non-zero coefficients from the fit object and... |
| get_non_zero_lines | Given a matrix, return lines with non-zero entries |
| get_rdata_path | Get the path of the R data file |
| get_summary_metrics | Tabulate the best lambda index |
| load_multiSnpnetRdata | Given a results directory and lambda index (optional), load... |
| load_multiSnpnetResultsFromRDataFiles | Load the results of multiSnpnet |
| multisnpnet | Fast Multi-Phenotype SRRR on SNP Data |
| plot_biplot | Make biplots of the multisnpnet results |
| plot_multisnpnet | Make plots of the multisnpnet results |
| plot_scree | Generate a scree plot visualization based on the decomposed... |
| predict_multisnpnet | Predict from the Fitted Object or File |
| prepare_multiSnpnetResults | Set the results of multiSnpnet run in a list |
| read_lambda_sequence_from_multiSnpnetResults | Read the lambda sequence from the initial fit with a... |
| read_pvar | Read the list of genetic variants present in the dataset. |
| score_contribution | Compute the contribution scores |
| score_squared_cosine | Compute the squared cosine scores |
| separate_ID_ALT_into_two_columns | Given a data frame with ID_ALT column, this function... |
| tsvd_of_C_variant_loadings_as_data_framte | Extract the variant loadings of the SVD of coefficients as a... |
| tsvd_of_C_with_names | Compute the TSVD of the regression coefficient |
| weighted_rowMeans | weighted row means |
