Author: Daniel Münch
Detecting volatile chemicals and encoding these into neuronal activity is a vital task for all animals that is performed by their olfactory sensory systems… Olfactory sensory neuron (OSN) classes are tuned to defined but overlapping sets of odors. Thus a single odor usually elicits differential responses across an ensemble of OSNs. This ensemble code is able to encode thousands of odors, even in comparably simple olfactory systems.
To better understand the underlying logic of this ensemble code, one would ideally want to know the specific ensemble codes each and every chemical elicits across an olfactory system, the so-called “olfactome”. Obviously this is not feasible to tackle experimentally, yet many labs work with e.g. the olfactory system of Drosophila and publish studies containing responses of different odor-OSN combinations.
DoOR takes these heterogeneous data measured in different labs, with different techniques in different metrics and maps/merges them into a common response space, creating a consensus data-set of all odor responses. By this, DoOR provides access to the most-complete version of the Drosophila olfactome available.
The DoOR project consists of two packages, DoOR.data and DoOR.functions. While the first mainly provides the raw data-sets, the latter performs the processing i.e. the actual merging process, data import and export, data analysis and visualization.
Read the full post here: https://ropensci.org/blog/2018/03/27/door/