cola: an R/Bioconductor package for consensus partitioning through a general framework

Classification of high-throughput genomic data is a powerful method to assign samples to subgroups with specific molecular profiles. Consensus partitioning is the most widely applied approach to reveal subgroups by summarizing a consensus classification from a list of individual classifications generated by repeatedly executing clustering on random subsets of the data. It is able to evaluate the stability of the classification. We implemented a new R/Bioconductor package, cola, that provides a general framework for consensus partitioning. With cola, various parameters and methods can be user-defined and easily integrated into different steps of an analysis, e.g., feature selection, sample classification or defining signatures. cola provides a new method named ATC (ability to correlate to other rows) to extract features and recommends spherical k-means clustering (skmeans) for subgroup classification. We show that ATC and skmeans have better performance than other commonly used methods by a comprehensive benchmark on public datasets. We also benchmark key parameters in the consensus partitioning procedure, which helps users to select optimal parameter values. Moreover, cola provides rich functionalities to apply multiple partitioning methods in parallel and directly compare their results, as well as rich visualizations. cola can automate the complete analysis and generates a comprehensive HTML report.

Partitioning a reaction–diffusion ecological network for dynamic stability

The loss of dispersal connections between habitat patches may destabilize populations in a patched ecological network. This work studies the stability of populations when one or more communication links is removed. An example is finding the alignment of a highway through a patched forest containing a network of metapopulations in the patches. This problem is modelled as that of finding a stable cut of the graph induced by the metapopulations network, where nodes represent the habitat patches and the weighted edges model the dispersal between habitat patches. A reaction–diffusion system on the graph models the dynamics of the predator–prey system over the patched ecological network. The graph Laplacian's Fiedler value, which indicates the well-connectedness of the graph, is shown to affect the stability of the metapopulations. We show that, when the Fiedler value is sufficiently large, the removal of edges without destabilizing the dynamics of the network is possible. We give an exhaustive graph partitioning procedure, which is suitable for smaller networks and uses the criterion for both the local and global stability of populations in partitioned networks. A heuristic graph bisection algorithm that preserves the preassigned lower bound for the Fiedler value is proposed for larger networks and is illustrated with examples.

Building Latent Class Trees, With an Application to a Study of Social Capital

Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical variables. However, especially when the number of classes required to obtain a good fit is large, interpretation of the latent classes may not be straightforward. To overcome this problem, we propose an alternative way of performing LC analysis, Latent Class Tree (LCT) modeling. For this purpose, a recursive partitioning procedure similar to divisive hierarchical cluster analysis is used: classes are split until a certain criterion indicates that the fit does not improve. The advantage of the LCT approach compared to the standard LC approach is that it gives a clear insight into how the latent classes are formed and how solutions with different numbers of classes relate. We also propose measures to evaluate the relative importance of the splits. The practical use of the approach is illustrated by the analysis of a data set on social capital.

Contrasting intra-annual patterns of six biotic groups with different dispersal mode and ability in Mediterranean temporary ponds

The temporal patterns of six biotic groups (from phytoplankton to amphibians) and their responses to environmental variation were studied in a set of Mediterranean temporary ponds. These biotic groups differed widely in dispersal ability and dispersal mode (active v. passive) and, for this reason, we predicted that they would exhibit different temporal patterns and responses to environmental factors. Six temporary ponds were sampled three times: at the beginning (January), middle (March) and end (May) of the hydroperiod. For each biotic group, we evaluated temporal variation in composition, species richness, among-pond similarities and number of typifying taxa. Moreover, a β diversity partitioning procedure was used to obtain the relative contributions of the replacement and richness components to overall β diversity. Finally, the effects of water, pond and landscape variables on composition and taxa richness were analysed for each group. Different temporal patterns were observed among the biotic groups studied, and in some (but not all) cases these differences were explained by their dispersal ability. Similarly, we observed that environmental control was group specific. These results advance the notion that communities in Mediterranean temporary ponds are highly variable over time and that generalisations with regard to patterns and controls across taxonomic groups are not supported.

Cytotoxic Compounds from Aerial Organs of Xanthium Strumarium

Xanthium strumarium L., the main species of the genus Xanthium, is ubiquitously distributed. The aim of this study was to determine the cytotoxic effect of aerial organs of X. strumarium, grown in Cuba, against cancer cell lines and the isolation of compounds potentially responsible for this activity. Initially, an ethanol partitioning procedure yielded the XSE extract that was subsequently fractionated with chloroform resulting in a XSCF fraction. Both, XSE and XSCF fractions exhibited cytotoxic effects on MDA MB-231, MCF7, A549 and CT26 cell lines by using the MTT assay. Above all, the XSCF fraction was more active than XSE. For this reason, XSCF was subsequently fractionated by silica gel chromatography and the active fractions submitted to semi-preparative HPLC for isolation of bioactive compounds. Six sub-fractions (SF1 to SF6) were recovered. Sub-fractions 3 and 6 were the most active on each assayed cell line, while sub-fractions 4 and 5 were only active against A549 and CT26 cell lines. In each case, sub-fraction 6 showed the strongest inhibitory effect. The HPLC-DAD fingerprint of sub-fraction 6 showed a single peak that was identified by GC-MS as (-) spathulenol, a sesquiterpene with reported antitumor activity.

Total and fractionation metal contents obtained with sequential extraction procedures in a sediment core from Terra Nova Bay, West Antarctica

A suite of 21 elements, namely Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, La, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V and Zn, was investigated in a sediment core from the Ross Sea, Antarctica. The experimental results were treated by chemometric techniques. The elemental composition of core H2 was found to be mainly dominated by terrigenous elements, but it is also influenced by biological factors, such as the presence of corals. No evidence of anthropogenic contamination was observed, even in the top layer of the sediment. Furthermore, the modified Community Bureau of Reference (BCR) three-step sequential extraction procedure was applied to evaluate metal mobility and availability. The results confirmed the separation between higher and lower sections of the core and showed the presence of Fe as amorphous and crystalline oxide and of Mn mostly as nodules. The high percentages of metals extracted into the fourth fraction indicate their strong binding with the sediment matrix. Finally, BCR procedure was compared to Tessier's protocol which made it possible to distinguish between mobile and mobilizable fraction. Therefore, in general partitioning procedure must be chosen taking into account the nature of the sample and the aim of the research.