ALBERT

Description: : As sequencing becomes cheaper and more widely available, there is a greater need to quickly and effectively analyze large-scale genomic data. While the functionality of AVIA v1.0, whose implementation was based on ANNOVAR, was comparable with other annotation web servers, AVIA v2.0 represents an enhanced web-based server that extends genomic annotations to cell-specific transcripts and protein-level functional annotations. With AVIA’s improved interface, users can better visualize their data, perform comprehensive searches and categorize both coding and non-coding variants. Availability and implementation : AVIA is freely available through the web at http://avia.abcc.ncifcrf.gov . Contact : Hue.Vuong@fnlcr.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : As new methods for multivariate analysis of genome wide association studies become available, it is important to be able to combine results from different cohorts in a meta-analysis. The R package MultiMeta provides an implementation of the inverse-variance-based method for meta-analysis, generalized to an n -dimensional setting. Availability and implementation: The R package MultiMeta can be downloaded from CRAN. Contact: dragana.vuckovic@burlo.trieste.it ; vi1@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Parasite host range can be influenced by physiological, behavioral, and ecological factors. Combining data sets on host–parasite associations with phylogenetic information of the hosts and the parasites involved can generate evolutionary hypotheses about the selective forces shaping host range. Here, we analyzed associations between the nest-parasitic flies in the genus Philornis and their host birds on Trinidad. Four of ten Philornis species were only reared from one species of bird. Of the parasite species with more than one host bird species, P. falsificus was the least specific and P. deceptivus the most specific attacking only Passeriformes. Philornis flies in Trinidad thus include both specialists and generalists , with varying degrees of specificity within the generalists. We used three quantities to more formally compare the host range of Philornis flies: the number of bird species attacked by each species of Philornis , a phylogenetically informed host specificity index (Poulin and Mouillot's S TD ), and a branch length-based S TD . We then assessed the phylogenetic signal of these measures of host range for 29 bird species. None of these measures showed significant phylogenetic signal, suggesting that clades of Philornis did not differ significantly in their ability to exploit hosts. We also calculated two quantities of parasite species load for the birds – the parasite species richness, and a variant of the S TD index based on nodes rather than on taxonomic levels – and assessed the signal of these measures on the bird phylogeny. We did not find significant phylogenetic signal for the parasite species load or the node-based S TD index. Finally, we calculated the parasite associations for all bird pairs using the Jaccard index and regressed these similarity values against the number of nodes in the phylogeny separating bird pairs. This analysis showed that Philornis on Trinidad tend to feed on closely related bird species more often than expected by chance. Host range, parasite species load, and community similarity are important descriptors of host-parasite interactions. We used a phylogenetic approach to explore host-associations between birds and their Philornis parasites on the island of Trinidad.

Description: We analyzed individual variation in work load (nest visit rate) during chick-rearing, and the consequences of this variation in terms of breeding productivity, in a highly synchronous breeder, the European starling ( Sturnus vulgaris ) focusing on female birds. There was marked (10- to 16-fold) variation in total, female and male nest visit rates, among individuals, but individual variation in female nest visit rate was independent of environment (rainfall, temperature) and metrics of individual quality (laying date, clutch size, amount of male provisioning help), and was only weakly associated with chick demand (i.e., day 6 brood size). Female nest visit rate was independent of date and experimentally delayed birds provisioned at the same rate as peak-nesting birds; supporting a lack of effect of date per se. Brood size at fledging was positively but weakly related to total nest visit rate (male + female), with 〉fivefold variation in nest visit rate for any given brood size, and in females brood size at fledging and chick mass at fledging were independent of female nest visit rate, that is, individual variation in workload was not associated with higher productivity. Nevertheless, nest visit rate in females was repeatable among consecutive days (6–8 posthatching), and between peak (first) and second broods, but not among years. Our data suggest that individual females behave as if committed to a certain level of parental care at the outset of their annual breeding attempt, but this varies among years, that is, behavior is not fixed throughout an individual's life but represents an annually variable decision. We suggest females are making predictable decisions about their workload during provisioning that maximizes their overall fitness based on an integration of information on their current environment (although these cues currently remain unidentified). Traditional metrics of parental workload vary considerably and we elucidate an uncoupling of female provisioning effort and fitness benefits. We suggest females are making predictable decisions about their workload during provisioning that maximizes their overall fitness based on an integration of information on their current environment.

Description: Motivation: Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Methods: Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. Results: We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. Contact: tperkins@ohri.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typical for molecular data. Assuming that the underlying signal is sparse, i.e. that only a fraction of features contribute to a principal component (PC), this estimation consistency can be retained. Most existing sparse PCA methods use L1-penalization, i.e. the lasso , to perform feature selection. But, the lasso is known to lack variable selection consistency in high dimensions and therefore a subsequent interpretation of selected features can give misleading results. Results: We present S4VDPCA, a sparse PCA method that incorporates a subsampling approach, namely stability selection. S4VDPCA can consistently select the truly relevant variables contributing to a sparse PC while also consistently estimate the direction of maximal variability. The performance of the S4VDPCA is assessed in a simulation study and compared to other PCA approaches, as well as to a hypothetical oracle PCA that ‘knows’ the truly relevant features in advance and thus finds optimal, unbiased sparse PCs. S4VDPCA is computationally efficient and performs best in simulations regarding parameter estimation consistency and feature selection consistency. Furthermore, S4VDPCA is applied to a publicly available gene expression data set of medulloblastoma brain tumors. Features contributing to the first two estimated sparse PCs represent genes significantly over-represented in pathways typically deregulated between molecular subgroups of medulloblastoma. Availability and implementation: Software is available at https://github.com/mwsill/s4vdpca . Contact: m.sill@dkfz.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner. Results: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N -linked glycan library and PDB homologous/non-homologous N -glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility. Availability and implementation: http://www.glycanstructure.org/gsalign . Contact: wonpil@ku.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Impedance-based technologies are advancing methods for measuring proliferation of adherent cell cultures non-invasively and in real time. The analysis of the resulting data has so far been hampered by inappropriate computational methods and the lack of systematic data to evaluate the characteristics of the assay. Results: We used a commercially available system for impedance-based growth measurement (xCELLigence) and compared the reported cell index with data from microscopy. We found that the measured signal correlates linearly with the cell number throughout the time of an experiment with sufficient accuracy in subconfluent cell cultures. The resulting growth curves for various colon cancer cells could be well described with the empirical Richards growth model, which allows for extracting quantitative parameters (such as characteristic cycle times). We found that frequently used readouts like the cell index at a specific time or the area under the growth curve cannot be used to faithfully characterize growth inhibition. We propose to calculate the average growth rate of selected time intervals to accurately estimate time-dependent IC50 values of drugs from growth curves. Contact: nils.bluethgen@charite.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: The merger of formerly isolated lineages is hypothesized to occur in vertebrates under certain conditions. However, despite many demonstrated instances of introgression between taxa in secondary contact, examples of lineage mergers are rare. Preliminary mtDNA sequencing of a Malagasy passerine, Xanthomixis zosterops (Passeriformes: Bernieridae), indicated a possible instance of merging lineages. We tested the hypothesis that X . zosterops lineages are merging by comparing mtDNA sequence and microsatellite data, as well as mtDNA sequence data from host-specific feather lice in the genus Myrsidea (Phthiraptera: Menoponidae). Xanthomixis zosterops comprises four deeply divergent, broadly sympatric, cryptic mtDNA clades that likely began diverging approximately 3.6 million years ago. Despite this level of divergence, the microsatellite data indicate that the X . zosterops mtDNA clades are virtually panmictic. Three major phylogroups of Myrsidea were found, supporting previous allopatry of the X . zosterops clades. In combination, the datasets from X . zosterops and its Myrsidea document a potential merger of previously allopatric lineages that likely date to the Pliocene. This represents the first report of sympatric apparent hybridization among more than two terrestrial vertebrate lineages. Further, the mtDNA phylogeographic pattern of X . zosterops , namely the syntopy of more than two deeply divergent cryptic clades, appears to be a novel scenario among vertebrates. We highlight the value of gathering multiple types of data in phylogeographic studies to contribute to the study of vertebrate speciation. Xanthomixis zosterops comprises four deeply divergent, broadly sympatric, cryptic mtDNA clades that likely began diverging approximately 3.6 million years ago. Despite this level of divergence, microsatellite data indicate that the X . zosterops mtDNA clades are virtually panmictic. The presence of three distinct phylogroups of host-specific Myrsidea lice on X . zosterops support previous allopatry and potential lineage merger of the X . zosterops clades.

Description: Sexual signals are important in attracting and choosing mates; however, these signals and their associated preferences are often costly and frequently lost. Despite the prevalence of signaling system loss in many taxa, the factors leading to signal loss remain poorly understood. Here, we test the hypothesis that complexity in signal loss scenarios is due to the context-dependent nature of the many factors affecting signal loss itself. Using the Avida digital life platform, we evolved 50 replicates of ~250 lineages, each with a unique combination of parameters, including whether signaling is obligate or facultative; genetic linkage between signaling and receiving genes; population size; and strength of preference for signals. Each of these factors ostensibly plays a crucial role in signal loss, but was found to do so only under specific conditions. Under obligate signaling, genetic linkage, but not population size, influenced signal loss; under facultative signaling, genetic linkage does not have significant influence. Somewhat surprisingly, only a total loss of preference in the obligate signaling populations led to total signal loss, indicating that even a modest amount of preference is enough to maintain signaling systems. Strength of preference proved to be the strongest single force preventing signal loss, as it consistently overcame the potential effects of drift within our study. Our findings suggest that signaling loss is often dependent on not just preference for signals, population size, and genetic linkage, but also whether signals are required to initiate mating. These data provide an understanding of the factors (and their interactions) that may facilitate the maintenance of sexual signals. Sexual signals are important in attracting and choosing mates; however, these signals and their associated preferences are often costly and frequently lost. Here we used the Avida digital life platform to explore the conditions (population size, genetic linkage, strength of preference, and requirement of signal to initial mating) under which signal loss occurs. Our findings suggest that (1) signaling loss is often dependent on not just preference for signals, population size, and genetic linkage, but also whether signals are required to initiate mating, and (2) complete signal loss may be harder to obtain that previously thought.