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  • Oxford University Press  (23,705)
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  • 1
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    AVIA v2.0: annotation, visualization and impact analysis of genomic variants and genes (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-08
    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.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 2
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    MultiMeta: an R package for meta-analyzing multi-phenotype genome-wide association studies (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-08
    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.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 3
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    Decreased glycogen synthase kinase-3 levels and activity contribute to Huntington's disease (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-07
    Description: Huntington's disease (HD) is a hereditary neurodegenerative disorder characterized by brain atrophy particularly in striatum leading to personality changes, chorea and dementia. Glycogen synthase kinase-3 (GSK-3) is a serine/threonine kinase in the crossroad of many signaling pathways that is highly pleiotropic as it phosphorylates more than hundred substrates including structural, metabolic, and signaling proteins. Increased GSK-3 activity is believed to contribute to the pathogenesis of neurodegenerative diseases like Alzheimer's disease and GSK-3 inhibitors have been postulated as therapeutic agents for neurodegeneration. Regarding HD, GSK-3 inhibitors have shown beneficial effects in cell and invertebrate animal models but no evident efficacy in mouse models. Intriguingly, those studies were performed without interrogating GSK-3 level and activity in HD brain. Here we aim to explore the level and also the enzymatic activity of GSK-3 in the striatum and other less affected brain regions of HD patients and of the R6/1 mouse model to then elucidate the possible contribution of its alteration to HD pathogenesis by genetic manipulation in mice. We report a dramatic decrease in GSK-3 levels and activity in striatum and cortex of HD patients with similar results in the mouse model. Correction of the GSK-3 deficit in HD mice, by combining with transgenic mice with conditional GSK-3 expression, resulted in amelioration of their brain atrophy and behavioral motor and learning deficits. Thus, our results demonstrate that decreased brain GSK-3 contributes to HD neurological phenotype and open new therapeutic opportunities based on increasing GSK-3 activity or attenuating the harmful consequences of its decrease.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 4
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    Loss of MyD88 alters neuroinflammatory response and attenuates early Purkinje cell loss in a spinocerebellar ataxia type 6 mouse model (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-07
    Description: Spinocerebellar ataxia type 6 (SCA6) is dominantly inherited neurodegenerative disease, caused by an expansion of CAG repeat encoding a polyglutamine (PolyQ) tract in the Ca v 2.1 voltage-gated calcium channel. Its key pathological features include selective degeneration of the cerebellar Purkinje cells (PCs), a common target for PolyQ-induced toxicity in various SCAs. Mutant Ca v 2.1 confers toxicity primarily through a toxic gain-of-function mechanism; however, its molecular basis remains elusive. Here, we studied the cerebellar gene expression patterns of young Sca6 -MPI 118Q/118Q knockin (KI) mice, which expressed mutant Ca v 2.1 from an endogenous locus and recapitulated many phenotypic features of human SCA6. Transcriptional signatures in the MPI 118Q/118Q mice were distinct from those in the Sca1 154Q/2Q mice, a faithful SCA1 KI mouse model. Temporal expression profiles of the candidate genes revealed that the up-regulation of genes associated with microglial activation was initiated before PC degeneration and was augmented as the disease progressed. Histological analysis of the MPI 118Q/118Q cerebellum showed the predominance of M1-like pro-inflammatory microglia and it was concomitant with elevated expression levels of tumor necrosis factor, interleukin-6, Toll-like receptor (TLR) 2 and 7. Genetic ablation of MyD88, a major adaptor protein conveying TLR signaling, altered expression patterns of M1/M2 microglial phenotypic markers in the MPI 118Q/118Q cerebellum. More importantly, it ameliorated PC loss and partially rescued motor impairments in the early disease phase. These results suggest that early neuroinflammatory response may play an important role in the pathogenesis of SCA6 and its modulation could pave the way for slowing the disease progression during the early stage of the disease.
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    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 5
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    Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-08
    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.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 6
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    Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-08
    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.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 7
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    GS-align for glycan structure alignment and similarity measurement (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-08
    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.
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    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 8
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    Analysis of impedance-based cellular growth assays (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-08
    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.
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    Topics: Biology , Computer Science , Medicine
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  • 9
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    Data-dependent bucketing improves reference-free compression of sequencing reads (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-25
    Description: Motivation: The storage and transmission of high-throughput sequencing data consumes significant resources. As our capacity to produce such data continues to increase, this burden will only grow. One approach to reduce storage and transmission requirements is to compress this sequencing data. Results: We present a novel technique to boost the compression of sequencing that is based on the concept of bucketing similar reads so that they appear nearby in the file. We demonstrate that, by adopting a data-dependent bucketing scheme and employing a number of encoding ideas, we can achieve substantially better compression ratios than existing de novo sequence compression tools, including other bucketing and reordering schemes. Our method, Mince, achieves up to a 45% reduction in file sizes (28% on average) compared with existing state-of-the-art de novo compression schemes. Availability and implementation : Mince is written in C++11, is open source and has been made available under the GPLv3 license. It is available at http://www.cs.cmu.edu/~ckingsf/software/mince . Contact: carlk@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 10
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    Identification of C2H2-ZF binding preferences from ChIP-seq data using RCADE (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-25
    Description: : Current methods for motif discovery from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data often identify non-targeted transcription factor (TF) motifs, and are even further limited when peak sequences are similar due to common ancestry rather than common binding factors. The latter aspect particularly affects a large number of proteins from the Cys 2 His 2 zinc finger (C2H2-ZF) class of TFs, as their binding sites are often dominated by endogenous retroelements that have highly similar sequences. Here, we present recognition code-assisted discovery of regulatory elements (RCADE) for motif discovery from C2H2-ZF ChIP-seq data. RCADE combines predictions from a DNA recognition code of C2H2-ZFs with ChIP-seq data to identify models that represent the genuine DNA binding preferences of C2H2-ZF proteins. We show that RCADE is able to identify generalizable binding models even from peaks that are exclusively located within the repeat regions of the genome, where state-of-the-art motif finding approaches largely fail. Availability and implementation: RCADE is available as a webserver and also for download at http://rcade.ccbr.utoronto.ca/ . Supplementary information: Supplementary data are available at Bioinformatics online. Contact: t.hughes@utoronto.ca
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    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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