Pyrfume: A window to the world's olfactory data

Abstract

Advances in theoretical understanding are frequently unlocked by access to large, diverse experimental datasets. Our understanding of olfactory neuroscience and psychophysics remain years behind the other senses, in part because rich datasets linking olfactory stimuli with their corresponding percepts, behaviors, and neural pathways remain scarce. Here we present a concerted effort to unlock and unify dozens of stimulus-linked olfactory datasets across species and modalities under a unified framework called Pyrfume. We present examples of how researchers might use Pyrfume to conduct novel analyses uncovering new principles, introduce trainees to the field, or construct benchmarks for machine olfaction.

Fig. 1

Overview of the Pyrfume ecosystem. Under the Pyrfume standard, data are always linked to the odor stimuli comprising a given experiment. The features, or experimental measurements, will depend on the particular experiment, but could include data such as amplitudes of glomerular calcium transients, vectorized perceptual descriptors, receptor sensitivities, etc. Any given data archive on Pyrfume (>40 to date) can be easily fetched by using the Pyrfume python and R packages or downloaded directly from GitHub as a zipfile. The orange rows of the odorant x feature matrices indicate odorant molecules, identified with CIDs, common across the experiments. The ability to easily extract data for a given molecule across experimental modalities and model systems is a unique strength of Pyrfume. See Supplementary Figures S1, S2 for examples of this.

Fig. 2

Schematic showing important data-formatting standards of Pyrfume. In a hypothetical and simplified experiment, 2 odorants were tested on two animals, and data were collected across a total of 5 glomeruli. The Pyrfume archive is organized around a subject-object distinction. The molecules.csv file (lower left) contains chemical descriptors, which can be used to index experimental measurements. The stimuli.csv file (lower right) provides a mapping between stimulus conditions and chemical information. The subjects.csv file (upper left) catalogs all experimental levels for all subjects. Lastly, behavior.csv (upper right) is indexed on the stimuli, and contains the actual experimental measurements, with one measurement per row.