partial_cor | R Documentation |

A method that integrates differential expression (DE) analysis and differential network (DN) analysis to select biomarker candidates for cancer studies. partial_cor is the second step of the partial correlation calculation after getting the result from select_rho_partial function.

partial_cor( data_list = NULL, rho_group1 = NULL, rho_group2 = NULL, p_val = NULL, permutation = 1000, permutation_thres = 0.05, fdr = TRUE )

`data_list` |
This is a list of pre-processed data outputted by the select_rho_partial function. |

`rho_group1` |
This is a character string indicating the rule for choosing rho value for group 1, "min": minimum rho, "ste": one standard error from minimum, or user can input rho of their choice. The default is minimum. |

`rho_group2` |
This is a character string indicating the rule for choosing rho value for group 2, "min": minimum rho, "ste": one standard error from minimum, or user can input rho of their choice, the default is minimum. |

`p_val` |
This is optional. It is a p*1 dataframe that contains the p-value for each biomolecule from DE analysis. |

`permutation` |
This is a positive integer representing the desired number of permutations. The default is 1000. |

`permutation_thres` |
This is a integer representing the threshold for the permutation test. The default is 0.05 to achieve 95 percent confidence. |

`fdr` |
This is a boolean value indicating whether to apply multiple testing correction (TRUE) or not (FALSE). The default is TRUE. However, if users find the output network is too sparse even after relaxing the permutation_thres, it's probably a good idea to turn off the multiple testing correction. |

A list containing an activity score dataframe with "ID", "P_value", "Node_Degree" and "Activity_Score" as columns and a differential network dataframe with the binary and the weight connection values.

# step 1: select_rho_partial pre_data <- select_rho_partial(data = Met_GU, class_label = Met_Group_GU, id = Met_name_GU, error_curve = TRUE) # step 2: partial_cor result <- partial_cor(data_list = pre_data, rho_group1 = 'min', rho_group2 = "min", p_val = pvalue_M_GU, permutation = 1000, permutation_thres = 0.05, fdr = TRUE)

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.