Multi-TGDR: a regularization method for multi-class classification in microarray experiments

Background With microarray technology becoming mature and popular, the selection and use of a small number of relevant genes for accurate classification of samples is a hot topic in the circles of biostatistics and bioinformatics. However, most of the developed algorithms lack the ability to handle multiple classes, which arguably a common application. Here, we propose an extension to an existing regularization algorithm called Threshold Gradient Descent Regularization (TGDR) to specifically tackle multi-class classification of microarray data. When there are several microarray experiments addressing the same/similar objectives, one option is to use meta-analysis version of TGDR (Meta-TGDR), which considers the classification task as combination of classifiers with the same structure/model while allowing the parameters to vary across studies. However, the original Meta-TGDR extension did not offer a solution to the prediction on independent samples. Here, we propose an explicit method to estimate the overall coefficients of the biomarkers selected by Meta-TGDR. This extension permits broader applicability and allows a comparison between the predictive performance of Meta-TGDR and TGDR using an independent testing set. Results Using real-world applications, we demonstrated the proposed multi-TGDR framework works well and the number of selected genes is less than the sum of all individualized binary TGDRs. Additionally, Meta-TGDR and TGDR on the batch-effect adjusted pooled data approximately provided same results. By adding Bagging procedure in each application, the stability and good predictive performance are warranted. Conclusions Compared with Meta-TGDR, TGDR is less computing time intensive, and requires no samples of all classes in each study. On the adjusted data, it has approximate same predictive performance with Meta-TGDR. Thus, it is highly recommended

Incorporating a New Summary Statistic into the Min–Max Approach: A Min–Max–Median, Min–Max–IQR Combination of Biomarkers for Maximising the Youden Index

Linearly combining multiple biomarkers is a common practice that can provide a better diagnostic performance. When the number of biomarkers is sufficiently high, a computational burden problem arises. Liu et al. proposed a distribution-free approach (min–max approach) that linearly combines the minimum and maximum values of the biomarkers, involving only a single coefficient search. However, the combination of minimum and maximum biomarkers alone may not be sufficient in terms of discrimination. In this paper, we propose a new approach that extends that of Liu et al. by incorporating a new summary statistic, specifically, the median or interquartile range (min–max–median and min–max–IQR approaches) in order to find the optimal combination that maximises the Youden index. Although this approach is more computationally intensive than the one proposed by Liu et al, it includes more information and the number of parameters to be estimated remains reasonable. We compare the performance of the proposed approaches (min–max–median and min–max–IQR) with the min–max approach and logistic regression. For this purpose, a wide range of different simulated data scenarios were explored. We also apply the approaches to two real datasets (Duchenne Muscular Dystrophy and Small for Gestational Age)

The future of Viscum album L. in Europe will be shaped by temperature and host availability.

Viscum album L. is a plant of great importance due to its influence on the host trees and, by extension, entire ecosystems. The species is also significant to humans-on the one hand, because of its use in medicine, and on the other, because of the growing threat it poses to the stability of conifer stands. Therefore, it is important to recognize the future range of three mistletoe subspecies (Viscum album subsp. album, V. album subsp. austriacum, and V. album subsp. abietis). Modelling of the potential range of these subspecies was performed using MAXENT software. Locations were collected from literature and databases. A total number of 3335 stands were used. Bioclimatic data for the current conditions and three future scenarios (SSP 1.26, SSP 3.70, SSP 5.85) were downloaded from the CHELSA database. The results confirmed that the temperature is the key variable on the potential range of the analysed subspecies. V. album subsp. abietis is withdrawing from its range according to all scenarios. In the case of V. album subsp. austriacum, a slight range shift is visible. Only the V. album subsp. album will expand non-directionally. The reason is most likely a very large number of host species and greater genetic variability compared to the subspecies found on conifers

The future of Viscum album L. in Europe will be shaped by temperature and host availability.

Viscum album L. is a plant of great importance due to its influence on the host trees and, by extension, entire ecosystems. The species is also significant to humans-on the one hand, because of its use in medicine, and on the other, because of the growing threat it poses to the stability of conifer stands. Therefore, it is important to recognize the future range of three mistletoe subspecies (Viscum album subsp. album, V. album subsp. austriacum, and V. album subsp. abietis). Modelling of the potential range of these subspecies was performed using MAXENT software. Locations were collected from literature and databases. A total number of 3335 stands were used. Bioclimatic data for the current conditions and three future scenarios (SSP 1.26, SSP 3.70, SSP 5.85) were downloaded from the CHELSA database. The results confirmed that the temperature is the key variable on the potential range of the analysed subspecies. V. album subsp. abietis is withdrawing from its range according to all scenarios. In the case of V. album subsp. austriacum, a slight range shift is visible. Only the V. album subsp. album will expand non-directionally. The reason is most likely a very large number of host species and greater genetic variability compared to the subspecies found on conifers

Consequence of habitat specificity: a rising risk of habitat loss for endemic and sub-endemic woody species under climate change in the Hyrcanian ecoregion

Endemic species are more impacted by climate change than other taxa. However, assessing the vulnerability of endemics to these changes in some regions, such as the Hyrcanian forest, is limited, despite its importance for biodiversity and ecosystem function. To address the question of expected habitat shifts under climate change across the Hyrcanian ecoregion, we built an ensemble of species distribution models (SDM) under two emission scenarios (RCP 4.5 and RCP 8.5) for 15 endemic woody taxa. To identify the potential priority conservation areas, we also applied a spatial prioritization approach. Overall, our results suggest that the impacts of climate change are more severe on the eastern parts of the region (Golestan) and the Talysh Mountains (north-western Hyrcanian ecoregion) with over 85% and 34% loss of suitable habitats over the next 80 years. The central part of the Alborz Mountains (Mazandaran) and some areas in the Talysh Mountains could be potential climatic refugia under the future conditions for endemic taxa. The most prominent changes are expected for Ruscus hyrcanus, Gleditsia capsica, Acer velutinum, Frangula grandifolia, and Buxus hyrcana. The worrying predicted loss of suitable habitats for most studied taxa would dramatically affect the stability and resilience of forests, threatening thus biodiversity of the Hyrcanian ecoregion. We present the first estimation of the potential risks involved and provide useful support for regional climate-adaptation strategy, indicating potential conservation priority areas for maintaining and preserving its resources. Notably, only 13.4% of areas designated for conservation and management under climate change will be located within the current Hyrcanian protected areas, yet the majority of these areas are classified as low priority

The evolutionary heritage and ecological uniqueness of Scots pine in the Caucasus ecoregion is at risk of climate changes.

Scots pine is one of the most widely occurring pines, but future projections suggest a large reduction in its range, mostly at the southern European limits. A significant part of its range is located in the Caucasus, a global hot-spot of diversity. Pine forests are an important reservoir of biodiversity and endemism in this region. We explored demographic and biogeographical processes that shaped the genetic diversity of Scots pine in the Caucasus ecoregion and its probable future distribution under different climate scenarios. We found that the high genetic variability of the Caucasian populations mirrors a complex glacial and postglacial history that had a unique evolutionary trajectory compared to the main range in Europe. Scots pine currently grows under a broad spectrum of climatic conditions in the Caucasus, which implies high adaptive potential in the past. However, the current genetic resources of Scots pine are under high pressure from climate change. From our predictions, over 90% of the current distribution of Scots pine may be lost in this century. By threatening the stability of the forest ecosystems, this would dramatically affect the biodiversity of the Caucasus hot-spot