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While one test dataset consisted of 32 fungal adhesins, the other had 310 non-adhesins from different fungi species (Datasets S3 and S4 respectively).
As expected, N scores from the genome dataset correlated much more strongly with those from the representative dataset than with those from the species datasets (Table 3).
To estimate the differing contributions from species and strains, i.e. the within and between-species variation, we calculated N scores for the three species datasets and the representative dataset.
The N scores from the species datasets revealed more information as they were small or zero before 1995 and rose sharply after that year (Figure 4), probably because few sequences were obtained from the three species in early years while many sequences were obtained in the last few years.
Protein domain analysis revealed significant differences between the two species datasets.
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The combustion chemistry of di-n‑butyl ether (DBE, C8H18O), conceivable as a potential biofuel candidate, was studied here for the first time under flame conditions with examining a detailed species dataset.
Some examples are aircraft datasets [6, 7]; Caltech-UCSD bird species dataset [8] consisting of 12 K images, car make, and model datasets; Standford cars dataset [9] containing 16 K car images; and CompCars dataset [10] of 130 K images.
In order to test the universality of our method, we performed 40 PHYLORPH runs, with one species dataset out of the 21 available in FUNYBASE blasted against two to five whole genomes in each run (Table S2).
Upon user request (selection of one protein dataset and at least two full genome sequences located in the same class or order than the non-model species targeted), genomes are automatically downloaded from various sources (NCBI, JGI, BROAD and others; Table S1), formatted for tblastn searches and interrogated for similarities with the protein sequences of the species dataset selected.
Each record contains the information of probeset_ID, SPM value, species, dataset and tissue while available.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com