Content | Loading DoOR | Modifying, building and updating DoOR | Importing new data with import_new_data() | Looking up InChIKeys If you do not know the InChIKeys of the odorants in | Building the complete data base with | Updating parts of the data base with | Using the heuristic approach This is the faster way to perform a merge of | Trying all permutations The more exhaustive way to update the data base is | model_response() and model_response_seq() | Merging using the heuristic with model_response() model_response() | Merging in a specific sequence with model_response_seq() | Removing a study with remove_study(){#remove_study} remove_study() will | Updating the odor information with | Helper functions | trans_id() | reset_sfr(){#reset_sfr} reset_sfr() subtracts the values of a specified | door_default_values(){#door_default_values} door_default_values() returns | get_responses(){#get_responses} get_responses() returns the response | get_normalized_responses() | count_studies(){#count_studies} count_studies() counts the number of studies | export_door_data(){#export_door_data} export_door_data() exports all or

Content | Loading data | Identifying the sensillum we are recording from with identify_sensillum() | using correlations | using Euclidean distances | returning data instead of plots | Finding neuron-specific odorants with private_odorant() | Mapping response data from an unknown source with map_receptor() | Changing the response unit (spikes, deltaF/F, ...) with back_project() | Quantifying tuning curves with sparse()

Content | Loading data | Visualizing odorants vs responding units with dplot_response_matrix() | Visualizing ensemble responses with dplot_al_map() | Visualizing tuning curves with dplot_tuningCurve() | Responding units | Odorants | Visualizing response profiles dplot_response_profile() | Comparing response profiles dplot_compare_profiles() | Comparing original data sets | Comparing DoOR response profiles | Visualizing responses across responding units with dplot_across_ru() | Visualizing odorant responses across OSNs with dplot_across_osns()