A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

A molecular phylogeny for the Tribe Dacini (Diptera: Tephritidae) : systematic and biogeographic implications

With well over 700 species, the Tribe Dacini is one of the most species-rich clades within the dipteran family Tephritidae, the true fruit flies. Nearly all Dacini belong to one of two very large genera, Dacus Fabricius and Bactrocera Macquart. The distribution of the genera overlap in or around the Indian subcontinent, but the greatest diversity of Dacus is in Africa and the greatest diversity of Bactrocera is in south-east Asia and the Pacific. The monophyly of these two genera has not been rigorously established, with previous phylogenies only including a small number of species and always heavily biased to one genus over the other. Moreover, the subgeneric taxonomy within both genera is complex and the monophyly of many subgenera has not been explicitly tested. Previous hypotheses about the biogeography of the Dacini based on morphological reviews and current distributions of taxa have invoked an out-of-India hypothesis; however this has not been tested in a phylogenetic framework. We attempted to resolve these issues with a dated, molecular phylogeny of 125 Dacini species generated using 16S, COI, COII and white eye genes. The phylogeny shows that Bactrocera is not monophyletic, but rather consists of two major clades: Bactrocera s.s. and the ‘Zeugodacus group of subgenera’ (a recognised, but informal taxonomic grouping of 15 Bactrocera subgenera). This ‘Zeugodacus’ clade is the sister group to Dacus, not Bactrocera and, based on current distributions, split from Dacus before that genus moved into Africa. We recommend that taxonomic consideration be given to raising Zeugodacus to genus level. Supportive of predictions following from the out-of-India hypothesis, the first common ancestor of the Dacini arose in the mid-Cretaceous approximately 80 mya. Major divergence events occurred during the Indian rafting period and diversification of Bactrocera apparently did not begin until after India docked with Eurasia (50–35 mya). In contrast, diversification in Dacus, at approximately 65 mya, apparently began much earlier than predicted by the out-of-India hypothesis, suggesting that, if the Dacini arose on the Indian plate, then ancestral Dacus may have left the plate in the mid to late Cretaceous via the well documented India–Madagascar–Africa migration route. We conclude that the phylogeny does not disprove the predictions of an out-of-India hypothesis for the Dacini, although modification of the original hypothesis is required.

Population structure of Bactrocera dorsalis s.s., B. papayae and B. philippinensis (Diptera: Tephritidae) in southeast Asia: evidence for a single species hypothesis using mitochondrial DNA and wingshape data

Background Bactrocera dorsalis s.s. is a pestiferous tephritid fruit fly distributed from Pakistan to the Pacific, with the Thai/Malay peninsula its southern limit. Sister pest taxa, B. papayae and B. philippinensis, occur in the southeast Asian archipelago and the Philippines, respectively. The relationship among these species is unclear due to their high molecular and morphological similarity. This study analysed population structure of these three species within a southeast Asian biogeographical context to assess potential dispersal patterns and the validity of their current taxonomic status. Results Geometric morphometric results generated from 15 landmarks for wings of 169 flies revealed significant differences in wing shape between almost all sites following canonical variate analysis. For the combined data set there was a greater isolation-by-distance (IBD) effect under a ‘non-Euclidean’ scenario which used geographical distances within a biogeographical ‘Sundaland context’ (r2 = 0.772, P < 0.0001) as compared to a ‘Euclidean’ scenario for which direct geographic distances between sample sites was used (r2 = 0.217, P < 0.01). COI sequence data were obtained for 156 individuals and yielded 83 unique haplotypes with no correlation to current taxonomic designations via a minimum spanning network. BEAST analysis provided a root age and location of 540kya in northern Thailand, with migration of B. dorsalis s.l. into Malaysia 470kya and Sumatra 270kya. Two migration events into the Philippines are inferred. Sequence data revealed a weak but significant IBD effect under the ‘non-Euclidean’ scenario (r2 = 0.110, P < 0.05), with no historical migration evident between Taiwan and the Philippines. Results are consistent with those expected at the intra-specific level. Conclusions Bactrocera dorsalis s.s., B. papayae and B. philippinensis likely represent one species structured around the South China Sea, having migrated from northern Thailand into the southeast Asian archipelago and across into the Philippines. No migration is apparent between the Philippines and Taiwan. This information has implications for quarantine, trade and pest management.