HoloNet.plotting.lr_rank_in_mgc#
- HoloNet.plotting.lr_rank_in_mgc(trained_MGC_model_list, lr_df, repeat_filter_num=0, repeat_attention_scale=True, plot_lr_num=15, fname=None, display=True, plot_cluster=True, cluster_col='cluster')#
Analyze the MGC attention value corresponding to each LR pair, and plot the LR pairs serving as the core mediators of FCEs.
- Parameters
- trained_MGC_model_list
List[MGC_Model] A list of trained MGC model for generating the expression of one target gene.
- lr_df
DataFrame The used preprocessed LR-gene dataframe, must contain the ‘LR_pair’ column.
- repeat_filter_num
int(default:0) The number of repetitions to be filtered out. If the attention obtained from a certain training has too low variance, delete the training result. If 0, not filter any training.
- repeat_attention_scale
bool(default:True) If True, scale the attention of each training to 0-1.
- plot_lr_num
int(default:15) The number of LR pair displayed in the output figure.
- fname
str|Path|NoneUnion[str,Path,None] (default:None) The output file name. If None, not save the figure.
- display
bool(default:True) If False, not plot the figure.
- plot_cluster
bool(default:True) If True, plot the cluster information of LR pairs as the color bar of heatmap.
- cluster_col
str(default:'cluster') The columns in lr_df dataframe storing the clustering results of each LR pair, which is necessary if plot_cluster == True.
- trained_MGC_model_list
- Return type
- Returns
: lr_df added column ‘MGC_layer_attention’, which contains the attention value of each LR pair.