LS-TreeBoost and LAD-TreeBoost for Gene Regulatory Network Reconstruction

add_names | Add row and column names to the adjacency matrix A |

apply_row_deviation | Apply row-wise deviation on the inferred GRN |

consider_previous_information | Remember the intermediate inferred GRN while generating the... |

first_GBM_step | Perform either LS-Boost or LAD-Boost ('GBM') on expression... |

GBM | Calculate Gene Regulatory Network from Expression data using... |

GBM.test | Test GBM predictor |

GBM.train | Train GBM predictor |

get_colids | Get the indices of recitifed list of Tfs for individual... |

get_filepaths | Generate filepaths to maintain adjacency matrices and images |

get_ko_experiments | Get indices of experiments where knockout or knockdown... |

get_tf_indices | Get the indices of all the TFs from the data |

normalize_matrix_colwise | Column normalize the obtained adjacency matrix |

null_model_refinement_step | Perform the null model refinement step |

regularized_GBM_step | Perform the regularized GBM modelling once the initial GRN is... |

regulate_regulon_size | Regulate the size of the regulon for each TF |

RGBM | Regularized Gradient Boosting Machine for inferring GRN |

RGBM.test | Test rgbm predictor |

RGBM.train | Train RGBM predictor |

second_GBM_step | Re-iterate through the core GBM model building with optimal... |

select_ideal_k | Identifies the optimal value of k i.e. top k Tfs for each... |

test_regression_stump_R | Test the regression model |

train_regression_stump_R | Train the regression stump |

transform_importance_to_weights | Log transforms the edge-weights in the inferred GRN |

v2l | Convert adjacency matrix to a list of edges |

z_score_effect | Generates a matrix S2 of size Ntfs x Ntargets using the... |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.