When comparing two datasets of predicted transfers that differ in their expected false-positive rate, we find that the more stringent dataset shows a stronger enrichment of clustered pairs.
This combined and more stringent dataset yielded a total of 1103 proteins, quantified by emPAI, based on 13469 observed peptides with unique parent ions (10339 unique sequences) from 209 LC-MS/MS runs with less than 5% false positive rate (see Supplementary Tables S2 [see Additional file 2] and S3 [see Additional file 3], for all identified proteins and peptides, respectively).
The observation that several of the initially detected pathways did not remain significant in our more stringent analysis suggests that they could be false positive findings because of inclusion of house keeping processes in the initial dataset and over-detection of small and less defined pathways in the more stringent dataset.
Selecting oil palm sequences that had a start and stop codon at a position similar to the protein sequence in GenBank resulted in a more stringent and accurate dataset of full-length ORFs.
Under these circumstances, a more stringent standard than the Limited Dataset is required.
We therefore performed the OPLS analysis for this experiment on the entire set of 54,794 nuclear gene models and then restricted the gene list obtained to only those gene models represented on the UPSC POP2 array (we consider this to be a more stringent approach than limiting the dataset to only those genes present on the UPSC POP2 array before performing the OPLS analysis).
For larger datasets, a more stringent enrichment score cutoff of either >0.9 or >1.0 was used, as seen from lowest score cutoffs listed in the table below per analysis.
Due to challenges in obtaining a reliable blood plasma protein list, HUPO later re-analysed their own original dataset with a more stringent statistical treatment that resulted in a much reduced list of high confidence (at least 95%) proteins compared with their original findings.
We accept that our study group was small, and for this reason we could not keep separate training and test datasets for a more stringent assessment of the multivariate models.
On the other hand, an attempt to eliminate one of the two such similar sequences by using of a more stringent similarity threshold could result in elimination of most of the dataset.
