MLCut: exploring multi-level cuts in dendrograms for biological data.

Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alternative automated or semi-automated methods that cut dendrograms in multiple levels make assumptions about the data in hand. In an attempt to help the user to find patterns in the data and resolve ambiguities in cluster assignments, we developed MLCut: a tool that provides visual support for exploring dendrograms of heterogeneous data sets in different levels of detail. The interactive exploration of the dendrogram is coordinated with a representation of the original data, shown as parallel coordinates. The tool supports three analysis steps. Firstly, a single-height similarity threshold can be applied using a dynamic slider to identify the main clusters. Secondly, a distinctiveness threshold can be applied using a second dynamic slider to identify “weak-edges” that indicate heterogeneity within clusters. Thirdly, the user can drill-down to further explore the dendrogram structure - always in relation to the original data - and cut the branches of the tree at multiple levels. Interactive drill-down is supported using mouse events such as hovering, pointing and clicking on elements of the dendrogram. Two prototypes of this tool have been developed in collaboration with a group of biologists for analysing their own data sets. We found that enabling the users to cut the tree at multiple levels, while viewing the effect in the original data, is a promising method for clustering which could lead to scientific discoveries.

Protein feeding of Queensland fruit fly Bactrocera tryoni and cucumber fly Zeugodacus cucumis (Diptera: Tephritidae) on non-host vegetation: effect of plant species and bait height

Perimeter-baiting of non-crop vegetation using toxic protein baits was developed overseas as a technique for control of melon fly, Zeugodacus (Zeugodacus) cucurbitae (Coquillett) (formerly Bactrocera (Zeugodacus) cucurbitae), and evidence suggests that this technique may also be effective in Australia for control of local fruit fly species in vegetable crops. Using field cage trials and laboratory reared flies, primary data were generated to support this approach by testing fruit flies' feeding response to protein when applied to eight plant species (forage sorghum, grain sorghum, sweet corn, sugarcane, eggplant, cassava, lilly pilly and orange jessamine) and applied at three heights (1, 1.5 and 2 m). When compared across the plants, Queensland fruit fly, Bactrocera tryoni (Froggatt), most commonly fed on protein bait applied to sugarcane and cassava, whereas more cucumber fly, Zeugodacus (Austrodacus) cucumis (French) (formerly Bactrocera (Austrodacus) cucumis), fed on bait applied to sweet corn and forage sorghum. When protein bait was applied at different heights, B. tryoni responded most to bait placed in the upper part of the plants (2 m), whereas Z. cucumis preferred bait placed lower on the plants (1 and 1.5 m). These results have implications for optimal placement of protein bait for best practice control of fruit flies in vegetable crops and suggest that the two species exhibit different foraging behaviours.

Assessment of SARAL/AltiKa Wave Height Measurements Relative to Buoy, Jason-2, and Cryosat-2 Data

SARAL/AltiKa GDR-T are analyzed to assess the quality of the significant wave height (SWH) measurements. SARAL along-track SWH plots reveal cases of erroneous data, more or less isolated, not detected by the quality flags. The anomalies are often correlated with strong attenuation of the Ka-band backscatter coefficient, sensitive to clouds and rain. A quality test based on the 1Hz standard deviation is proposed to detect such anomalies. From buoy comparison, it is shown that SARAL SWH is more accurate than Jason-2, particularly at low SWH, and globally does not require any correction. Results are better with open ocean than with coastal buoys. The scatter and the number of outliers are much larger for coastal buoys. SARAL is then compared with Jason-2 and Cryosat-2. The altimeter data are extracted from the global altimeter SWH Ifremer data base, including specific corrections to calibrate the various altimeters. The comparison confirms the high quality of SARAL SWH. The 1Hz standard deviation is much less than for Jason-2 and Cryosat-2, particularly at low SWH. Furthermore, results show that the corrections applied to Jason-2 and to Cryosat-2, in the data base, are efficient, improving the global agreement between the three altimeters.

Neuropsychiatric disease (NPD) clustering in families with Autism Spectrum Disorder (ASD): genetic, epigenetic and environmental issues

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication/interaction and by unusual repetitive and restricted behaviors and interests. ASD often co-occurs in the same families with other neuropsychiatric diseases (NPD), such as intellectual disability, schizophrenia, epilepsy, depression and attention deficit hyperactivity disorder. Genetic factors have an important role in ASD etiology. Multiple copy number variants (CNVs) and single nucleotide variants (SNVs) in candidate genes have been associated with an increased risk to develop ASD. Nevertheless, recent heritability estimates and the high genotypic and phenotypic heterogeneity characteristic of ASD indicate a role of environmental and epigenetic factors, such as long noncoding RNA (lncRNA) and microRNA (miRNA), as modulators of genetic expression and further clinical presentation. Both miRNA and lncRNA are functional RNA molecules that are transcribed from DNA but not translated into proteins, instead they act as powerful regulators of gene expression. While miRNA are small noncoding RNAs with 22-25 nucleotides in length that act at the post-transcriptional level of gene expression, the lncRNA are bigger molecules (>200 nucleotides in length) that are capped, spliced, and polyadenylated, similar to messenger RNA. Although few lncRNA were well characterized until date, there is a great evidence that they are implicated in several levels of gene expression (transcription/post-transcription/post-translation, organization of protein complexes, cell– cell signaling as well as recombination) as shown in figure 1.

Preliminary evaluation of macadamia rootstocks for yield and tree height

Rootstock has profound effects on traits such as yield and tree size in various horticultural industries, however relatively little is known about rootstock effects for macadamia. In this study, 12 cultivars were propagated as open-pollinated seedling and clonal rootstocks, and own-rooted cuttings. The same cultivars were also used as scions, and grafted to a subset of rootstocks, then planted at four trial locations. In this preliminary analysis, rootstock accounted for 19% of the variance in yield compared with 72% for scion, and 23% in height compared with 72% for scion. There was no interaction between rootstock and scion for yield, and only a small effect for height. The interaction between rootstock and propagation method (seedling, clonal, own roots) was not significant for height. A small effect was observed for yield, with the own roots treatment producing significantly lower yield than grafted trees for all rootstock cultivars except 'HAES 849'. 'H2' seedling rootstock produced a cumulative yield to age 10 years of 11.1 kg tree -1 compared to the highest yield of 13.6 kg tree -1 for 'Beaumont' clonal rootstocks. 'H2' seedling rootstock produced 4.8 m trees at age 11 years, compared to the smallest grafted tree which was 'HAES 849' seedling at 4.7 m.

In-situ based reanalysis of the global ocean temperature and salinity with ISAS: variability of the heat content and steric height

The In Situ Analysis System (ISAS) was developed to produce gridded fields of temperature and salinity that preserve as much as possible the time and space sampling capabilities of the Argo network of profiling floats. Since the first global re-analysis performed in 2009, the system has evolved and a careful delayed mode processing of the 2002-2012 dataset has been carried out using version 6 of ISAS and updating the statistics to produce the ISAS13 analysis. This last version is now implemented as the operational analysis tool at the Coriolis data centre. The robustness of the results with respect to the system evolution is explored through global quantities of climatological interest: the Ocean Heat Content and the Steric Height. Estimates of errors consistent with the methodology are computed. This study shows that building reliable statistics on the fields is fundamental to improve the monthly estimates and to determine the absolute error bars. The new mean fields and variances deduced from the ISAS13 re-analysis and dataset show significant changes relative to the previous ISAS estimates, in particular in the southern ocean, justifying the iterative procedure. During the decade covered by Argo, the intermediate waters appear warmer and saltier in the North Atlantic and fresher in the Southern Ocean than in WOA05 long term mean. At inter-annual scale, the impact of ENSO on the Ocean Heat Content and Steric Height is observed during the 2006-2007 and 2009-2010 events captured by the network.

Reconstructability of 3-Dimensional Upper Ocean Circulation from SWOT Sea Surface Height Measurements

Utilizing the framework of effective surface quasi-geostrophic (eSQG) theory, we explored the potential of reconstructing the 3D upper ocean circulation structures, including the balanced vertical velocity (w) field, from high-resolution sea surface height (SSH) data of the planned SWOT satellite mission. Specifically, we utilized the 1/30°, submesoscale-resolving, OFES model output and subjected it through the SWOT simulator that generates the along-swath SSH data with expected measurement errors. Focusing on the Kuroshio Extension region in the North Pacific where regional Rossby numbers range from 0.22 to 0.32, we found that the eSQG dynamics constitutes an effective framework for reconstructing the 3D upper ocean circulation field. Using the modeled SSH data as input, the eSQG-reconstructed relative vorticity (ζ) and w fields are found to reach a correlation of 0.7–0.9 and 0.6–0.7, respectively, in the 1,000m upper ocean when compared to the original model output. Degradation due to the SWOT sampling and measurement errors in the input SSH data for the ζ and w reconstructions is found to be moderate, 5–25% for the 3D ζ field and 15-35% for the 3D w field. There exists a tendency for this degradation ratio to decrease in regions where the regional eddy variability (or Rossby number) increases.

GENETIC DIVERSITY AMONG SORGHUM LANDRACES OF SOUTHWESTERN HIGHLANDS OF UGANDA

Sorghum ( Sorghum bicolor L. Moench) is an economic and staple crop in sub-Saharan Africa. The genetic diversity in its germplasm is an invaluable aid for its crop improvement. The objective of this study was to assess the existing genetic diversity among sorghum landraces in the southwestern highlands of Uganda. A total of 47 sorghum landraces, collected from southwestern highlands of Uganda, were characterised using 12 qualitative and 13 quantitative traits. The study was conducted at Kachwekano Research Farm in Kabale District, at an altitude of 2,223 m above sea level, during growing season of December 2014 to August 2015. Panicle shape and compactness were the most varied qualitative traits. Grain yield (1.23 to 11.31 t ha-1) and plant height (144.7 to 351.6 cm) were among quantitative traits that showed high variability. Days to 50% flowering (115 to 130 days) showed the least variability. Results of UPGMA cluster analysis generated a dendrogram with three clusters. Panicle weight, leaf width, stem girth, exertion length, peduncle length, panicle shape and compactness, glume colour and threshability were major traits responsible for the observed clustering (P<0.001). Principal Component Analysis revealed the largest variation contributors.

Modeling height-diameter relationship in pinus pinaster ait. in the forest intervention zone of Lomba, NE-Portugal

In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

Clustering of variables with a three-way approach for health sciences

© 2014 Cises This work is distributed with License Creative Commons Attribution-Non commercial-No derivatives 4.0 International (CC BY-BC-ND 4.0)