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Publisher: Oxford University Press   (Total: 369 journals)

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Showing 1 - 200 of 369 Journals sorted alphabetically
Acta Biochimica et Biophysica Sinica     Hybrid Journal   (Followers: 6, SJR: 0.881, h-index: 38)
Adaptation     Hybrid Journal   (Followers: 8, SJR: 0.111, h-index: 4)
Aesthetic Surgery J.     Hybrid Journal   (Followers: 6, SJR: 1.538, h-index: 35)
African Affairs     Hybrid Journal   (Followers: 57, SJR: 1.512, h-index: 46)
Age and Ageing     Hybrid Journal   (Followers: 79, SJR: 1.611, h-index: 107)
Alcohol and Alcoholism     Hybrid Journal   (Followers: 14, SJR: 0.935, h-index: 80)
American Entomologist     Full-text available via subscription   (Followers: 5)
American Historical Review     Hybrid Journal   (Followers: 120, SJR: 0.652, h-index: 43)
American J. of Agricultural Economics     Hybrid Journal   (Followers: 41, SJR: 1.441, h-index: 77)
American J. of Epidemiology     Hybrid Journal   (Followers: 146, SJR: 3.047, h-index: 201)
American J. of Hypertension     Hybrid Journal   (Followers: 19, SJR: 1.397, h-index: 111)
American J. of Jurisprudence     Hybrid Journal   (Followers: 15)
American journal of legal history     Full-text available via subscription   (Followers: 4, SJR: 0.151, h-index: 7)
American Law and Economics Review     Hybrid Journal   (Followers: 26, SJR: 0.824, h-index: 23)
American Literary History     Hybrid Journal   (Followers: 12, SJR: 0.185, h-index: 22)
Analysis     Hybrid Journal   (Followers: 23)
Annals of Botany     Hybrid Journal   (Followers: 33, SJR: 1.912, h-index: 124)
Annals of Occupational Hygiene     Hybrid Journal   (Followers: 24, SJR: 0.837, h-index: 57)
Annals of Oncology     Hybrid Journal   (Followers: 48, SJR: 4.362, h-index: 173)
Annals of the Entomological Society of America     Full-text available via subscription   (Followers: 9, SJR: 0.642, h-index: 53)
Annals of Work Exposures and Health     Hybrid Journal  
AoB Plants     Open Access   (Followers: 4, SJR: 0.78, h-index: 10)
Applied Economic Perspectives and Policy     Hybrid Journal   (Followers: 18, SJR: 0.884, h-index: 31)
Applied Linguistics     Hybrid Journal   (Followers: 51, SJR: 1.749, h-index: 63)
Applied Mathematics Research eXpress     Hybrid Journal   (Followers: 1, SJR: 0.779, h-index: 11)
Arbitration Intl.     Full-text available via subscription   (Followers: 19)
Arbitration Law Reports and Review     Hybrid Journal   (Followers: 12)
Archives of Clinical Neuropsychology     Hybrid Journal   (Followers: 25, SJR: 0.96, h-index: 71)
Aristotelian Society Supplementary Volume     Hybrid Journal   (Followers: 2, SJR: 0.102, h-index: 20)
Arthropod Management Tests     Hybrid Journal   (Followers: 2)
Astronomy & Geophysics     Hybrid Journal   (Followers: 46, SJR: 0.144, h-index: 15)
Behavioral Ecology     Hybrid Journal   (Followers: 47, SJR: 1.698, h-index: 92)
Bioinformatics     Hybrid Journal   (Followers: 222, SJR: 4.643, h-index: 271)
Biology Methods and Protocols     Hybrid Journal  
Biology of Reproduction     Full-text available via subscription   (Followers: 10, SJR: 1.646, h-index: 149)
Biometrika     Hybrid Journal   (Followers: 18, SJR: 2.801, h-index: 90)
BioScience     Hybrid Journal   (Followers: 28, SJR: 2.374, h-index: 154)
Bioscience Horizons : The National Undergraduate Research J.     Open Access   (Followers: 1, SJR: 0.213, h-index: 9)
Biostatistics     Hybrid Journal   (Followers: 15, SJR: 1.955, h-index: 55)
BJA : British J. of Anaesthesia     Hybrid Journal   (Followers: 132, SJR: 2.314, h-index: 133)
BJA Education     Hybrid Journal   (Followers: 65, SJR: 0.272, h-index: 20)
Brain     Hybrid Journal   (Followers: 61, SJR: 6.097, h-index: 264)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 43, SJR: 4.086, h-index: 73)
Briefings in Functional Genomics     Hybrid Journal   (Followers: 4, SJR: 1.771, h-index: 50)
British J. for the Philosophy of Science     Hybrid Journal   (Followers: 32, SJR: 1.267, h-index: 38)
British J. of Aesthetics     Hybrid Journal   (Followers: 24, SJR: 0.217, h-index: 18)
British J. of Criminology     Hybrid Journal   (Followers: 489, SJR: 1.373, h-index: 62)
British J. of Social Work     Hybrid Journal   (Followers: 77, SJR: 0.771, h-index: 53)
British Medical Bulletin     Hybrid Journal   (Followers: 7, SJR: 1.391, h-index: 84)
British Yearbook of Intl. Law     Hybrid Journal   (Followers: 26)
Bulletin of the London Mathematical Society     Hybrid Journal   (Followers: 3, SJR: 1.474, h-index: 31)
Cambridge J. of Economics     Hybrid Journal   (Followers: 55, SJR: 0.957, h-index: 59)
Cambridge J. of Regions, Economy and Society     Hybrid Journal   (Followers: 9, SJR: 1.067, h-index: 22)
Cambridge Quarterly     Hybrid Journal   (Followers: 10, SJR: 0.1, h-index: 7)
Capital Markets Law J.     Hybrid Journal  
Carcinogenesis     Hybrid Journal   (Followers: 2, SJR: 2.439, h-index: 167)
Cardiovascular Research     Hybrid Journal   (Followers: 11, SJR: 2.897, h-index: 175)
Cerebral Cortex     Hybrid Journal   (Followers: 37, SJR: 4.827, h-index: 192)
CESifo Economic Studies     Hybrid Journal   (Followers: 15, SJR: 0.501, h-index: 19)
Chemical Senses     Hybrid Journal   (Followers: 1, SJR: 1.436, h-index: 76)
Children and Schools     Hybrid Journal   (Followers: 5, SJR: 0.211, h-index: 18)
Chinese J. of Comparative Law     Hybrid Journal   (Followers: 3)
Chinese J. of Intl. Law     Hybrid Journal   (Followers: 19, SJR: 0.737, h-index: 11)
Chinese J. of Intl. Politics     Hybrid Journal   (Followers: 8, SJR: 1.238, h-index: 15)
Christian Bioethics: Non-Ecumenical Studies in Medical Morality     Hybrid Journal   (Followers: 11, SJR: 0.191, h-index: 8)
Classical Receptions J.     Hybrid Journal   (Followers: 17, SJR: 0.1, h-index: 3)
Clinical Infectious Diseases     Hybrid Journal   (Followers: 58, SJR: 4.742, h-index: 261)
Clinical Kidney J.     Open Access   (Followers: 4, SJR: 0.338, h-index: 19)
Community Development J.     Hybrid Journal   (Followers: 23, SJR: 0.47, h-index: 28)
Computer J.     Hybrid Journal   (Followers: 8, SJR: 0.371, h-index: 47)
Conservation Physiology     Open Access   (Followers: 1)
Contemporary Women's Writing     Hybrid Journal   (Followers: 11, SJR: 0.111, h-index: 3)
Contributions to Political Economy     Hybrid Journal   (Followers: 6, SJR: 0.313, h-index: 10)
Critical Values     Full-text available via subscription  
Current Legal Problems     Hybrid Journal   (Followers: 25)
Current Zoology     Full-text available via subscription   (SJR: 0.999, h-index: 20)
Database : The J. of Biological Databases and Curation     Open Access   (Followers: 11, SJR: 1.068, h-index: 24)
Digital Scholarship in the Humanities     Hybrid Journal   (Followers: 12)
Diplomatic History     Hybrid Journal   (Followers: 18, SJR: 0.296, h-index: 22)
DNA Research     Open Access   (Followers: 4, SJR: 2.42, h-index: 77)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 2)
Early Music     Hybrid Journal   (Followers: 13, SJR: 0.124, h-index: 11)
Economic Policy     Hybrid Journal   (Followers: 47, SJR: 2.052, h-index: 52)
ELT J.     Hybrid Journal   (Followers: 25, SJR: 1.26, h-index: 23)
English Historical Review     Hybrid Journal   (Followers: 45, SJR: 0.311, h-index: 10)
English: J. of the English Association     Hybrid Journal   (Followers: 12, SJR: 0.144, h-index: 3)
Environmental Entomology     Full-text available via subscription   (Followers: 11, SJR: 0.791, h-index: 66)
Environmental Epigenetics     Open Access   (Followers: 1)
Environmental History     Hybrid Journal   (Followers: 25, SJR: 0.197, h-index: 25)
EP-Europace     Hybrid Journal   (Followers: 1, SJR: 2.201, h-index: 71)
Epidemiologic Reviews     Hybrid Journal   (Followers: 9, SJR: 3.917, h-index: 81)
ESHRE Monographs     Hybrid Journal  
Essays in Criticism     Hybrid Journal   (Followers: 15, SJR: 0.1, h-index: 6)
European Heart J.     Hybrid Journal   (Followers: 46, SJR: 6.997, h-index: 227)
European Heart J. - Cardiovascular Imaging     Hybrid Journal   (Followers: 9, SJR: 2.044, h-index: 58)
European Heart J. - Cardiovascular Pharmacotherapy     Full-text available via subscription   (Followers: 1)
European Heart J. - Quality of Care and Clinical Outcomes     Hybrid Journal  
European Heart J. Supplements     Hybrid Journal   (Followers: 8, SJR: 0.152, h-index: 31)
European J. of Cardio-Thoracic Surgery     Hybrid Journal   (Followers: 7, SJR: 1.568, h-index: 104)
European J. of Intl. Law     Hybrid Journal   (Followers: 141, SJR: 0.722, h-index: 38)
European J. of Orthodontics     Hybrid Journal   (Followers: 4, SJR: 1.09, h-index: 60)
European J. of Public Health     Hybrid Journal   (Followers: 22, SJR: 1.284, h-index: 64)
European Review of Agricultural Economics     Hybrid Journal   (Followers: 12, SJR: 1.549, h-index: 42)
European Review of Economic History     Hybrid Journal   (Followers: 25, SJR: 0.628, h-index: 24)
European Sociological Review     Hybrid Journal   (Followers: 37, SJR: 2.061, h-index: 53)
Evolution, Medicine, and Public Health     Open Access   (Followers: 11)
Family Practice     Hybrid Journal   (Followers: 13, SJR: 1.048, h-index: 77)
Fems Microbiology Ecology     Hybrid Journal   (Followers: 8, SJR: 1.687, h-index: 115)
Fems Microbiology Letters     Hybrid Journal   (Followers: 19, SJR: 1.126, h-index: 118)
Fems Microbiology Reviews     Hybrid Journal   (Followers: 24, SJR: 7.587, h-index: 150)
Fems Yeast Research     Hybrid Journal   (Followers: 13, SJR: 1.213, h-index: 66)
Foreign Policy Analysis     Hybrid Journal   (Followers: 21, SJR: 0.859, h-index: 10)
Forestry: An Intl. J. of Forest Research     Hybrid Journal   (Followers: 17, SJR: 0.903, h-index: 44)
Forum for Modern Language Studies     Hybrid Journal   (Followers: 6, SJR: 0.108, h-index: 6)
French History     Hybrid Journal   (Followers: 29, SJR: 0.123, h-index: 10)
French Studies     Hybrid Journal   (Followers: 19, SJR: 0.119, h-index: 7)
French Studies Bulletin     Hybrid Journal   (Followers: 10, SJR: 0.102, h-index: 3)
Gastroenterology Report     Open Access   (Followers: 2)
Genome Biology and Evolution     Open Access   (Followers: 10, SJR: 3.22, h-index: 39)
Geophysical J. Intl.     Hybrid Journal   (Followers: 31, SJR: 1.839, h-index: 119)
German History     Hybrid Journal   (Followers: 24, SJR: 0.437, h-index: 13)
GigaScience     Open Access   (Followers: 3)
Global Summitry     Hybrid Journal  
Glycobiology     Hybrid Journal   (Followers: 14, SJR: 1.692, h-index: 101)
Health and Social Work     Hybrid Journal   (Followers: 46, SJR: 0.505, h-index: 40)
Health Education Research     Hybrid Journal   (Followers: 12, SJR: 0.814, h-index: 80)
Health Policy and Planning     Hybrid Journal   (Followers: 21, SJR: 1.628, h-index: 66)
Health Promotion Intl.     Hybrid Journal   (Followers: 19, SJR: 0.664, h-index: 60)
History Workshop J.     Hybrid Journal   (Followers: 25, SJR: 0.313, h-index: 20)
Holocaust and Genocide Studies     Hybrid Journal   (Followers: 22, SJR: 0.115, h-index: 13)
Human Molecular Genetics     Hybrid Journal   (Followers: 10, SJR: 4.288, h-index: 233)
Human Reproduction     Hybrid Journal   (Followers: 74, SJR: 2.271, h-index: 179)
Human Reproduction Update     Hybrid Journal   (Followers: 15, SJR: 4.678, h-index: 128)
Human Rights Law Review     Hybrid Journal   (Followers: 60, SJR: 0.7, h-index: 21)
ICES J. of Marine Science: J. du Conseil     Hybrid Journal   (Followers: 53, SJR: 1.233, h-index: 88)
ICSID Review     Hybrid Journal   (Followers: 8)
ILAR J.     Hybrid Journal   (Followers: 1, SJR: 1.099, h-index: 51)
IMA J. of Applied Mathematics     Hybrid Journal   (SJR: 0.329, h-index: 26)
IMA J. of Management Mathematics     Hybrid Journal   (Followers: 2, SJR: 0.351, h-index: 20)
IMA J. of Mathematical Control and Information     Hybrid Journal   (Followers: 2, SJR: 0.661, h-index: 28)
IMA J. of Numerical Analysis - advance access     Hybrid Journal   (SJR: 2.032, h-index: 44)
Industrial and Corporate Change     Hybrid Journal   (Followers: 8, SJR: 1.37, h-index: 81)
Industrial Law J.     Hybrid Journal   (Followers: 29, SJR: 0.184, h-index: 15)
Information and Inference     Free  
Integrative and Comparative Biology     Hybrid Journal   (Followers: 7, SJR: 1.911, h-index: 90)
Interacting with Computers     Hybrid Journal   (Followers: 10, SJR: 0.529, h-index: 59)
Interactive CardioVascular and Thoracic Surgery     Hybrid Journal   (Followers: 4, SJR: 0.743, h-index: 35)
Intl. Data Privacy Law     Hybrid Journal   (Followers: 27)
Intl. Health     Hybrid Journal   (Followers: 4, SJR: 0.835, h-index: 15)
Intl. Immunology     Hybrid Journal   (Followers: 4, SJR: 1.613, h-index: 111)
Intl. J. for Quality in Health Care     Hybrid Journal   (Followers: 32, SJR: 1.593, h-index: 69)
Intl. J. of Constitutional Law     Hybrid Journal   (Followers: 50, SJR: 0.613, h-index: 19)
Intl. J. of Epidemiology     Hybrid Journal   (Followers: 115, SJR: 4.381, h-index: 145)
Intl. J. of Law and Information Technology     Hybrid Journal   (Followers: 3, SJR: 0.247, h-index: 8)
Intl. J. of Law, Policy and the Family     Hybrid Journal   (Followers: 18, SJR: 0.307, h-index: 15)
Intl. J. of Lexicography     Hybrid Journal   (Followers: 8, SJR: 0.404, h-index: 18)
Intl. J. of Low-Carbon Technologies     Open Access   (Followers: 1, SJR: 0.457, h-index: 12)
Intl. J. of Neuropsychopharmacology     Open Access   (Followers: 4, SJR: 1.69, h-index: 79)
Intl. J. of Public Opinion Research     Hybrid Journal   (Followers: 8, SJR: 0.906, h-index: 33)
Intl. J. of Refugee Law     Hybrid Journal   (Followers: 34, SJR: 0.231, h-index: 21)
Intl. J. of Transitional Justice     Hybrid Journal   (Followers: 13, SJR: 0.833, h-index: 12)
Intl. Mathematics Research Notices     Hybrid Journal   (Followers: 1, SJR: 2.052, h-index: 42)
Intl. Mathematics Research Surveys - advance access     Hybrid Journal  
Intl. Political Sociology     Hybrid Journal   (Followers: 24, SJR: 1.339, h-index: 19)
Intl. Relations of the Asia-Pacific     Hybrid Journal   (Followers: 17, SJR: 0.539, h-index: 17)
Intl. Studies Perspectives     Hybrid Journal   (Followers: 7, SJR: 0.998, h-index: 28)
Intl. Studies Quarterly     Hybrid Journal   (Followers: 33, SJR: 2.184, h-index: 68)
Intl. Studies Review     Hybrid Journal   (Followers: 17, SJR: 0.783, h-index: 38)
ISLE: Interdisciplinary Studies in Literature and Environment     Hybrid Journal   (Followers: 1, SJR: 0.155, h-index: 4)
ITNOW     Hybrid Journal   (Followers: 2, SJR: 0.102, h-index: 4)
J. of African Economies     Hybrid Journal   (Followers: 15, SJR: 0.647, h-index: 30)
J. of American History     Hybrid Journal   (Followers: 38, SJR: 0.286, h-index: 34)
J. of Analytical Toxicology     Hybrid Journal   (Followers: 13, SJR: 1.038, h-index: 60)
J. of Antimicrobial Chemotherapy     Hybrid Journal   (Followers: 20, SJR: 2.157, h-index: 149)
J. of Antitrust Enforcement     Hybrid Journal   (Followers: 1)
J. of Applied Poultry Research     Hybrid Journal   (Followers: 3, SJR: 0.563, h-index: 43)
J. of Biochemistry     Hybrid Journal   (Followers: 43, SJR: 1.341, h-index: 96)
J. of Chromatographic Science     Hybrid Journal   (Followers: 18, SJR: 0.448, h-index: 42)
J. of Church and State     Hybrid Journal   (Followers: 11, SJR: 0.167, h-index: 11)
J. of Competition Law and Economics     Hybrid Journal   (Followers: 34, SJR: 0.442, h-index: 16)
J. of Complex Networks     Hybrid Journal   (Followers: 1, SJR: 1.165, h-index: 5)
J. of Conflict and Security Law     Hybrid Journal   (Followers: 11, SJR: 0.196, h-index: 15)
J. of Consumer Research     Full-text available via subscription   (Followers: 38, SJR: 4.896, h-index: 121)
J. of Crohn's and Colitis     Hybrid Journal   (Followers: 9, SJR: 1.543, h-index: 37)
J. of Cybersecurity     Hybrid Journal   (Followers: 2)
J. of Deaf Studies and Deaf Education     Hybrid Journal   (Followers: 8, SJR: 0.69, h-index: 36)
J. of Design History     Hybrid Journal   (Followers: 15, SJR: 0.166, h-index: 14)
J. of Economic Entomology     Full-text available via subscription   (Followers: 6, SJR: 0.894, h-index: 76)
J. of Economic Geography     Hybrid Journal   (Followers: 32, SJR: 2.909, h-index: 69)
J. of Environmental Law     Hybrid Journal   (Followers: 25, SJR: 0.457, h-index: 20)
J. of European Competition Law & Practice     Hybrid Journal   (Followers: 19)
J. of Experimental Botany     Hybrid Journal   (Followers: 13, SJR: 2.798, h-index: 163)
J. of Financial Econometrics     Hybrid Journal   (Followers: 21, SJR: 1.314, h-index: 27)
J. of Global Security Studies     Hybrid Journal   (Followers: 2)
J. of Heredity     Hybrid Journal   (Followers: 3, SJR: 1.024, h-index: 76)
J. of Hindu Studies     Hybrid Journal   (Followers: 7, SJR: 0.186, h-index: 3)
J. of Hip Preservation Surgery     Open Access  
J. of Human Rights Practice     Hybrid Journal   (Followers: 21, SJR: 0.399, h-index: 10)
J. of Infectious Diseases     Hybrid Journal   (Followers: 39, SJR: 4, h-index: 209)
J. of Insect Science     Open Access   (Followers: 9, SJR: 0.388, h-index: 31)

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Journal Cover Bioinformatics
  [SJR: 4.643]   [H-I: 271]   [222 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1367-4803 - ISSN (Online) 1460-2059
   Published by Oxford University Press Homepage  [369 journals]
  • Virtual exploration of early stage atherosclerosis
    • Authors: Olivares AL; González Ballester MA, Noailly J.
      Abstract: Bioinformatics (2016) doi: 10.1093/bioinformatics/btw551
      PubDate: 2017-01-03
       
  • LAMSA: fast split read alignment with long approximate matches
    • Authors: Liu B; Gao Y, Wang Y.
      Abstract: Motivation: Read length is continuously increasing with the development of novel high-throughput sequencing technologies, which has enormous potentials on cutting-edge genomic studies. However, longer reads could more frequently span the breakpoints of structural variants (SVs) than that of shorter reads. This may greatly influence read alignment, since most state-of-the-art aligners are designed for handling relatively small variants in a co-linear alignment framework. Meanwhile, long read alignment is still not as efficient as that of short reads, which could be also a bottleneck for the upcoming wide application.Results: We propose long approximate matches-based split aligner (LAMSA), a novel split read alignment approach. It takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming-based split alignment approach to handle the large or non-co-linear variants. We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; meanwhile, it also has good ability to handle various categories of SVs.Availability and Implementation: LAMSA is available at https://github.com/hitbc/LAMSAContact: Ydwang@hit.edu.cnSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-25
       
  • Detecting subnetwork-level dynamic correlations
    • Authors: Yan Y; Qiu S, Jin Z, et al.
      Abstract: Motivation: The biological regulatory system is highly dynamic. The correlations between many functionally related genes change over different biological conditions. Finding dynamic relations on the existing biological network may reveal important regulatory mechanisms. Currently no method is available to detect subnetwork-level dynamic correlations systematically on the genome-scale network. Two major issues hampered the development. The first is gene expression profiling data usually do not contain time course measurements to facilitate the analysis of dynamic relations, which can be partially addressed by using certain genes as indicators of biological conditions. Secondly, it is unclear how to effectively delineate subnetworks, and define dynamic relations between them.Results: Here we propose a new method named LANDD (Liquid Association for Network Dynamics Detection) to find subnetworks that show substantial dynamic correlations, as defined by subnetwork A is concentrated with Liquid Association scouting genes for subnetwork B. The method produces easily interpretable results because of its focus on subnetworks that tend to comprise functionally related genes. Also, the collective behaviour of genes in a subnetwork is a much more reliable indicator of underlying biological conditions compared to using single genes as indicators. We conducted extensive simulations to validate the method’s ability to detect subnetwork-level dynamic correlations. Using a real gene expression dataset and the human protein-protein interaction network, we demonstrate the method links subnetworks of distinct biological processes, with both confirmed relations and plausible new functional implications. We also found signal transduction pathways tend to show extensive dynamic relations with other functional groups.Availability and Implementation: The R package is available at https://cran.r-project.org/web/packages/LANDD.Contacts:yunba@pcom.edu, jwlu33@hotmail.com or tianwei.yu@emory.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-25
       
  • cMapper: gene-centric connectivity mapper for EBI-RDF platform
    • Authors: Shoaib M; Ansari A, Ahn S.
      Abstract: Motivation: In this era of biological big data, data integration has become a common task and a challenge for biologists. The Resource Description Framework (RDF) was developed to enable interoperability of heterogeneous datasets. The EBI-RDF platform enables an efficient data integration of six independent biological databases using RDF technologies and shared ontologies. However, to take advantage of this platform, biologists need to be familiar with RDF technologies and SPARQL query language. To overcome this practical limitation of the EBI-RDF platform, we developed cMapper, a web-based tool that enables biologists to search the EBI-RDF databases in a gene-centric manner without a thorough knowledge of RDF and SPARQL.Results: cMapper allows biologists to search data entities in the EBI-RDF platform that are connected to genes or small molecules of interest in multiple biological contexts. The input to cMapper consists of a set of genes or small molecules, and the output are data entities in six independent EBI-RDF databases connected with the given genes or small molecules in the user's query. cMapper provides output to users in the form of a graph in which nodes represent data entities and the edges represent connections between data entities and inputted set of genes or small molecules. Furthermore, users can apply filters based on database, taxonomy, organ and pathways in order to focus on a core connectivity graph of their interest. Data entities from multiple databases are differentiated based on background colors. cMapper also enables users to investigate shared connections between genes or small molecules of interest. Users can view the output graph on a web browser or download it in either GraphML or JSON formats.Availability and Implementation: cMapper is available as a web application with an integrated MySQL database. The web application was developed using Java and deployed on Tomcat server. We developed the user interface using HTML5, JQuery and the Cytoscape Graph API. cMapper can be accessed at http://cmapper.ewostech.net. Readers can download the development manual from the website http://cmapper.ewostech.net/docs/cMapperDocumentation.pdf. Source Code is available at https://github.com/muhammadshoaib/cmapper.Contact:smahn@gachon.ac.krSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-25
       
  • An accessibility-incorporated method for accurate prediction of RNA–RNA
           interactions from sequence data
    • Authors: Kato Y; Mori T, Sato K, et al.
      Abstract: Motivation: RNA–RNA interactions via base pairing play a vital role in the post-transcriptional regulation of gene expression. Efficient identification of targets for such regulatory RNAs needs not only discriminative power for positive and negative RNA–RNA interacting sequence data but also accurate prediction of interaction sites from positive data. Recently, a few studies have incorporated interaction site accessibility into their prediction methods, indicating the enhancement of predictive performance on limited positive data.Results: Here we show the efficacy of our accessibility-based prediction model RactIPAce on newly compiled datasets. The first experiment in interaction site prediction shows that RactIPAce achieves the best predictive performance on the newly compiled dataset of experimentally verified interactions in the literature as compared with the state-of-the-art methods. In addition, the second experiment in discrimination between positive and negative interacting pairs reveals that the combination of accessibility-based methods including our approach can be effective to discern real interacting RNAs. Taking these into account, our prediction model can be effective to predict interaction sites after screening for real interacting RNAs, which will boost the functional analysis of regulatory RNAs.Availability and Implementation: The program RactIPAce along with data used in this work is available at https://github.com/satoken/ractip/releases/tag/v1.0.1.Contact: ykato@rna.med.osaka-u.ac.jp or shingo@i.kyoto-u.ac.jpSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-23
       
  • FBB: a fast Bayesian-bound tool to calibrate RNA-seq aligners
    • Authors: Rodriguez-Lujan I; Hasty J, Huerta R.
      Abstract: Motivation: Despite RNA-seq reads provide quality scores that represent the probability of calling a correct base, these values are not probabilistically integrated in most alignment algorithms. Based on the quality scores of the reads, we propose to calculate a lower bound of the probability of alignment of any fast alignment algorithm that generates SAM files. This bound is called Fast Bayesian Bound (FBB) and serves as a canonical reference to compare alignment results across different algorithms. This Bayesian Bound intends to provide additional support to the current state-of-the-art aligners, not to replace them.Results: We propose a feasible Bayesian bound that uses quality scores of the reads to align them to a genome of reference. Two theorems are provided to efficiently calculate the Bayesian bound that under some conditions becomes the equality. The algorithm reads the SAM files generated by the alignment algorithms using multiple command option values. The program options are mapped into the FBB reference values, and all the aligners can be compared respect to the same accuracy values provided by the FBB. Stranded paired read RNA-seq data was used for evaluation purposes. The errors of the alignments can be calculated based on the information contained in the distance between the pairs given by Theorem 2, and the alignments to the incorrect strand. Most of the algorithms (Bowtie, Bowtie 2, SHRiMP2, Soap 2, Novoalign) provide similar results with subtle variations.Availability and Implementation: Current version of the FBB software is provided at https://bitbucket.org/irenerodriguez/fbb.Contact:rhuerta@ucsd.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-23
       
  • A generative model for the behavior of RNA polymerase
    • Authors: Azofeifa JG; Dowell RD.
      Abstract: Motivation: Transcription by RNA polymerase is a highly dynamic process involving multiple distinct points of regulation. Nascent transcription assays are a relatively new set of high throughput techniques that measure the location of actively engaged RNA polymerase genome wide. Hence, nascent transcription is a rich source of information on the regulation of RNA polymerase activity. To fully dissect this data requires the development of stochastic models that can both deconvolve the stages of polymerase activity and identify significant changes in activity between experiments.Results: We present a generative, probabilistic model of RNA polymerase that fully describes loading, initiation, elongation and termination. We fit this model genome wide and profile the enzymatic activity of RNA polymerase across various loci and following experimental perturbation. We observe striking correlation of predicted loading events and regulatory chromatin marks. We provide principled statistics that compute probabilities reminiscent of traveler’s and divergent ratios. We finish with a systematic comparison of RNA Polymerase activity at promoter versus non-promoter associated loci.Availability and Implementation: Transcription Fit (Tfit) is a freely available, open source software package written in C/C ++ that requires GNU compilers 4.7.3 or greater. Tfit is available from GitHub (https://github.com/azofeifa/Tfit).Contact: robin.dowell@colorado.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-23
       
  • Robust classification of single-cell transcriptome data by nonnegative
           matrix factorization
    • Authors: Shao C; Höfer T.
      Abstract: Motivation: Single-cell transcriptome data provide unprecedented resolution to study heterogeneity in cell populations and present a challenge for unsupervised classification. Popular methods, like principal component analysis (PCA), often suffer from the high level of noise in the data.Results: Here we adapt Nonnegative Matrix Factorization (NMF) to study the problem of identifying subpopulations in single-cell transcriptome data. In contrast to the conventional gene-centered view of NMF, identifying metagenes, we used NMF in a cell-centered direction, identifying cell subtypes (‘metacells’). Using three different datasets (based on RT-qPCR and single cell RNA-seq data, respectively), we show that NMF outperforms PCA in identifying subpopulations in an accurate and robust way, without the need for prior feature selection; moreover, NMF successfully recovered the broad classes on a large dataset (thousands of single-cell transcriptomes), as identified by a computationally sophisticated method. NMF allows to identify feature genes in a direct, unbiased manner. We propose novel approaches for determining a biologically meaningful number of subpopulations based on minimizing the ambiguity of classification. In conclusion, our study shows that NMF is a robust, informative and simple method for the unsupervised learning of cell subtypes from single-cell gene expression data.Availability and Implementation:https://github.com/ccshao/nimfaContacts:c.shao@Dkfz-Heidelberg.de or t.hoefer@Dkfz-Heidelberg.deSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-23
       
  • AcCNET ( Ac cessory Genome C onstellation Net work): comparative genomics
           software for accessory genome analysis using bipartite networks
    • Authors: Lanza VF; Baquero F, de la Cruz F, et al.
      Abstract: AcCNET (Accessory genome Constellation Network) is a Perl application that aims to compare accessory genomes of a large number of genomic units, both at qualitative and quantitative levels. Using the proteomes extracted from the analysed genomes, AcCNET creates a bipartite network compatible with standard network analysis platforms. AcCNET allows merging phylogenetic and functional information about the concerned genomes, thus improving the capability of current methods of network analysis. The AcCNET bipartite network opens a new perspective to explore the pangenome of bacterial species, focusing on the accessory genome behind the idiosyncrasy of a particular strain and/or population.Availability and Implementation: AcCNET is available under GNU General Public License version 3.0 (GPLv3) from http://sourceforge.net/projects/accnetContact: valfernandez.vf@gmail.comSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-23
       
  • Improved methods for multi-trait fine mapping of pleiotropic risk loci
    • Authors: Kichaev G; Roytman M, Johnson R, et al.
      Abstract: Motivation: Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation.Results: In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90% of the causal variants from 23 SNPs per locus using a single trait to 12 SNPs when fine-mapping two traits simultaneously. Finally, we analyze summary association data from a large-scale GWAS of lipids and show that these improvements are largely sustained in real data.Availability and Implementation: The fastPAINTOR framework is implemented in the PAINTOR v3.0 package which is publicly available to the research community http://bogdan.bioinformatics.ucla.edu/software/paintorContact:gkichaev@ucla.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-22
       
  • LD Hub: a centralized database and web interface to perform LD score
           regression that maximizes the potential of summary level GWAS data for SNP
           heritability and genetic correlation analysis
    • Authors: Zheng J; Erzurumluoglu A, Elsworth BL, et al.
      Abstract: Motivation: LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously.Results: In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies.Availability and Implementation: The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/Contact:jie.zheng@bristol.ac.ukSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-22
       
  • Biospark: scalable analysis of large numerical datasets from biological
           simulations and experiments using Hadoop and Spark
    • Authors: Klein M; Sharma R, Bohrer CH, et al.
      Abstract: Summary: Data-parallel programming techniques can dramatically decrease the time needed to analyze large datasets. While these methods have provided significant improvements for sequencing-based analyses, other areas of biological informatics have not yet adopted them. Here, we introduce Biospark, a new framework for performing data-parallel analysis on large numerical datasets. Biospark builds upon the open source Hadoop and Spark projects, bringing domain-specific features for biology.Availability and Implementation: Source code is licensed under the Apache 2.0 open source license and is available at the project website: https://www.assembla.com/spaces/roberts-lab-public/wiki/BiosparkContact:eroberts@jhu.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-22
       
  • FoldAtlas: a repository for genome-wide RNA structure probing data
    • Authors: Norris M; Kwok C, Cheema J, et al.
      Abstract: Summary: Most RNA molecules form internal base pairs, leading to a folded secondary structure. Some of these structures have been demonstrated to be functionally significant. High-throughput RNA structure chemical probing methods generate millions of sequencing reads to provide structural constraints for RNA secondary structure prediction. At present, processed data from these experiments are difficult to access without computational expertise. Here we present FoldAtlas, a web interface for accessing raw and processed structural data across thousands of transcripts. FoldAtlas allows a researcher to easily locate, view, and retrieve probing data for a given RNA molecule. We also provide in silico and in vivo secondary structure predictions for comparison, visualized in the browser as circle plots and topology diagrams. Data currently integrated into FoldAtlas are from a new high-depth Structure-seq data analysis in Arabidopsis thaliana, released with this work.Availability and Implementation: The FoldAtlas website can be accessed at www.foldatlas.com. Source code is freely available at github.com/mnori/foldatlas under the MIT license. Raw reads data are available under the NCBI SRA accession SRP066985.Contact:yiliang.ding@jic.ac.uk or matthew.norris@jic.ac.uk.Supplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-22
       
  • Evolutionary conservation of Ebola virus proteins predicts important
           functions at residue level
    • Authors: Arslan A; van Noort V.
      Abstract: Motivation: The recent outbreak of Ebola virus disease (EVD) resulted in a large number of human deaths. Due to this devastation, the Ebola virus has attracted renewed interest as model for virus evolution. Recent literature on Ebola virus (EBOV) has contributed substantially to our understanding of the underlying genetics and its scope with reference to the 2014 outbreak. But no study yet, has focused on the conservation patterns of EBOV proteins.Results: We analyzed the evolution of functional regions of EBOV and highlight the function of conserved residues in protein activities. We apply an array of computational tools to dissect the functions of EBOV proteins in detail: (i) protein sequence conservation, (ii) protein–protein interactome analysis, (iii) structural modeling and (iv) kinase prediction. Our results suggest the presence of novel post-translational modifications in EBOV proteins and their role in the modulation of protein functions and protein interactions. Moreover, on the basis of the presence of ATM recognition motifs in all EBOV proteins we postulate a role of DNA damage response pathways and ATM kinase in EVD. The ATM kinase is put forward, for further evaluation, as novel potential therapeutic target.Availability and Implementation:http://www.biw.kuleuven.be/CSB/EBOV-PTMsContact:vera.vannoort@biw.kuleuven.beSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-21
       
  • PSSV: a novel pattern-based probabilistic approach for somatic structural
           variation identification
    • Authors: Chen X; Shi X, Hilakivi-Clarke L, et al.
      Abstract: Motivation: Whole genome DNA-sequencing (WGS) of paired tumor and normal samples has enabled the identification of somatic DNA changes in an unprecedented detail. Large-scale identification of somatic structural variations (SVs) for a specific cancer type will deepen our understanding of driver mechanisms in cancer progression. However, the limited number of WGS samples, insufficient read coverage, and the impurity of tumor samples that contain normal and neoplastic cells, limit reliable and accurate detection of somatic SVs.Results: We present a novel pattern-based probabilistic approach, PSSV, to identify somatic structural variations from WGS data. PSSV features a mixture model with hidden states representing different mutation patterns; PSSV can thus differentiate heterozygous and homozygous SVs in each sample, enabling the identification of those somatic SVs with heterozygous mutations in normal samples and homozygous mutations in tumor samples. Simulation studies demonstrate that PSSV outperforms existing tools. PSSV has been successfully applied to breast cancer data to identify somatic SVs of key factors associated with breast cancer development.Availability and Implementation: An R package of PSSV is available at http://www.cbil.ece.vt.edu/software.htm.Contact:xuan@vt.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-21
       
  • GeneEvolve: a fast and memory efficient forward-time simulator of
           realistic whole-genome sequence and SNP data
    • Authors: Tahmasbi R; Keller MC.
      Abstract: Motivation: Computer simulations are excellent tools for understanding the evolutionary and genetic consequences of complex processes that cannot be analytically predicted and for creating realistic genetic data. There are many software packages that simulate genetic data, but they are typically not fast or memory efficient enough to simulate realistic, individual-level genome-wide SNP/sequence data.Results:GeneEvolve is a user-friendly and efficient population genetics simulator that handles complex evolutionary and life history scenarios and generates individual-level phenotypes and realistic whole-genome sequence or SNP data. GeneEvolve runs forward-in-time, which allows it to provide a wide range of scenarios for mating systems, selection, population size and structure, migration, recombination and environmental effects. The software is designed to use as input data from real or previously simulated phased haplotypes, allowing it to mimic very closely the properties of real genomic data.Availability and Implementation:GeneEvolve is freely available at https://github.com/rtahmasbi/GeneEvolve.Contact:Rasool.Tahmasbi@Colorado.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-21
       
  • Tissue-specific pathway association analysis using genome-wide association
           study summaries
    • Authors: Wang W; Hao J, Zheng S, et al.
      Abstract: Motivation: Pathway association analysis has made great achievements in elucidating the genetic basis of human complex diseases. However, current pathway association analysis approaches fail to consider tissue-specificity.Results: We developed a tissue-specific pathway interaction enrichment analysis algorithm (TPIEA). TPIEA was applied to two large Caucasian and Chinese genome-wide association study summary datasets of bone mineral density (BMD). TPIEA identified several significant pathways for BMD [false discovery rate (FDR) 
      PubDate: 2016-09-20
       
  • Reference point insensitive molecular data analysis
    • Authors: Altenbuchinger MM; Rehberg TT, Zacharias HU, et al.
      Abstract: Motivation: In biomedicine, every molecular measurement is relative to a reference point, like a fixed aliquot of RNA extracted from a tissue, a defined number of blood cells, or a defined volume of biofluid. Reference points are often chosen for practical reasons. For example, we might want to assess the metabolome of a diseased organ but can only measure metabolites in blood or urine. In this case, the observable data only indirectly reflects the disease state. The statistical implications of these discrepancies in reference points have not yet been discussed.Results: Here, we show that reference point discrepancies compromise the performance of regression models like the LASSO. As an alternative, we suggest zero-sum regression for a reference point insensitive analysis. We show that zero-sum regression is superior to the LASSO in case of a poor choice of reference point both in simulations and in an application that integrates intestinal microbiome analysis with metabolomics. Moreover, we describe a novel coordinate descent based algorithm to fit zero-sum elastic nets.Availability and Implementation: The R-package “zeroSum” can be downloaded at https://github.com/rehbergT/zeroSum. Moreover, we provide all R-scripts and data used to produce the results of this manuscript as Supplementary MaterialSupplementary Material.Contact:Michael.Altenbuchinger@ukr.de, Thorsten.Rehberg@ukr.de and Rainer.Spang@ukr.deSupplementary information:Supplementary materialSupplementary material is available at Bioinformatics online.
      PubDate: 2016-09-15
       
  • BOSS: a novel scaffolding algorithm based on an optimized scaffold graph
    • Authors: Luo J; Wang J, Zhang Z, et al.
      Abstract: Motivation: While aiming to determine orientations and orders of fragmented contigs, scaffolding is an essential step of assembly pipelines and can make assembly results more complete. Most existing scaffolding tools adopt scaffold graph approaches. However, due to repetitive regions in genome, sequencing errors and uneven sequencing depth, constructing an accurate scaffold graph is still a challenge task.Results: In this paper, we present a novel algorithm (called BOSS), which employs paired reads for scaffolding. To construct a scaffold graph, BOSS utilizes the distribution of insert size to decide whether an edge between two vertices (contigs) should be added and how an edge should be weighed. Moreover, BOSS adopts an iterative strategy to detect spurious edges whose removal can guarantee no contradictions in the scaffold graph. Based on the scaffold graph constructed, BOSS employs a heuristic algorithm to sort vertices (contigs) and then generates scaffolds. The experimental results demonstrate that BOSS produces more satisfactory scaffolds, compared with other popular scaffolding tools on real sequencing data of four genomes.Availability and Implementation: BOSS is publicly available for download at https://github.com/bioinfomaticsCSU/BOSS.Contact:jxwang@mail.csu.edu.cnSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-14
       
  • Seeksv: an accurate tool for somatic structural variation and virus
           integration detection
    • Authors: Liang Y; Qiu K, Liao B, et al.
      Abstract: Motivation: Many forms of variations exist in the human genome including single nucleotide polymorphism, small insert/deletion (DEL) (indel) and structural variation (SV). Somatically acquired SV may regulate the expression of tumor-related genes and result in cell proliferation and uncontrolled growth, eventually inducing tumor formation. Virus integration with host genome sequence is a type of SV that causes the related gene instability and normal cells to transform into tumor cells. Cancer SVs and viral integration sites must be discovered in a genome-wide scale for clarifying the mechanism of tumor occurrence and development.Results: In this paper, we propose a new tool called seeksv to detect somatic SVs and viral integration events. Seeksv simultaneously uses split read signal, discordant paired-end read signal, read depth signal and the fragment with two ends unmapped. Seeksv can detect DEL, insertion, inversion and inter-chromosome transfer at single-nucleotide resolution. Different types of sequencing data, such as single-end sequencing data or paired-end sequencing data can accommodate to detect SV. Seeksv develops a rescue model for SV with breakpoints located in sequence homology regions. Results on simulated and real data from the 1000 Genomes Project and esophageal squamous cell carcinoma samples show that seeksv has higher efficiency and precision compared with other similar software in detecting SVs. For the discovery of hepatitis B virus integration sites from probe capture data, the verified experiments show that more than 90% viral integration sequences detected by seeksv are true.Availability and Implementation: seeksv is implemented in C ++ and can be downloaded from https://github.com/qkl871118/seeksv.Contact: dragonbw@163.comSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-14
       
  • IsotopicLabelling: an R package for the analysis of MS isotopic patterns
           of labelled analytes
    • Authors: Ferrazza R; Griffin JL, Guella G, et al.
      Abstract: Motivation: Labelling experiments in biology usually make use of isotopically enriched substrates, with the two most commonly employed isotopes for metabolism being 2H and 13C. At the end of the experiment some metabolites will have incorporated the labelling isotope, to a degree that depends on the metabolic turnover. In order to propose a meaningful biological interpretation, it is necessary to estimate the amount of labelling, and one possible route is to exploit the fact that MS isotopic patterns reflect the isotopic distributions.Results: We developed the IsotopicLabelling R package, a tool able to extract and analyze isotopic patterns from liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-MS (GC-MS) data relative to labelling experiments. This package estimates the isotopic abundance of the employed stable isotope (either 2H or 13C) within a specified list of analytes.Availability and Implementation: The IsotopicLabelling R package is freely available at https://github.com/RuggeroFerrazza/IsotopicLabelling.Contacts:r.ferrazza@unitn.itSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-14
       
  • DM-BLD: differential methylation detection using a hierarchical Bayesian
           model exploiting local dependency
    • Authors: Wang X; Gu J, Hilakivi-Clarke L, et al.
      Abstract: Motivation: The advent of high-throughput DNA methylation profiling techniques has enabled the possibility of accurate identification of differentially methylated genes for cancer research. The large number of measured loci facilitates whole genome methylation study, yet posing great challenges for differential methylation detection due to the high variability in tumor samples.Results: We have developed a novel probabilistic approach, differential methylation detection using a hierarchical Bayesian model exploiting local dependency (DM-BLD), to detect differentially methylated genes based on a Bayesian framework. The DM-BLD approach features a joint model to capture both the local dependency of measured loci and the dependency of methylation change in samples. Specifically, the local dependency is modeled by Leroux conditional autoregressive structure; the dependency of methylation changes is modeled by a discrete Markov random field. A hierarchical Bayesian model is developed to fully take into account the local dependency for differential analysis, in which differential states are embedded as hidden variables. Simulation studies demonstrate that DM-BLD outperforms existing methods for differential methylation detection, particularly when the methylation change is moderate and the variability of methylation in samples is high. DM-BLD has been applied to breast cancer data to identify important methylated genes (such as polycomb target genes and genes involved in transcription factor activity) associated with breast cancer recurrence.Availability and Implementation: A Matlab package of DM-BLD is available at http://www.cbil.ece.vt.edu/software.htm.Contact:Xuan@vt.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-11
       
  • ImmuneDB: a system for the analysis and exploration of high-throughput
           adaptive immune receptor sequencing data
    • Authors: Rosenfeld AM; Meng W, Luning Prak ET, et al.
      Abstract: Summary: As high-throughput sequencing of B cells becomes more common, the need for tools to analyze the large quantity of data also increases. This article introduces ImmuneDB, a system for analyzing vast amounts of heavy chain variable region sequences and exploring the resulting data. It can take as input raw FASTA/FASTQ data, identify genes, determine clones, construct lineages, as well as provide information such as selection pressure and mutation analysis. It uses an industry leading database, MySQL, to provide fast analysis and avoid the complexities of using error prone flat-files.Availability and Implementation: ImmuneDB is freely available at http://immunedb.comA demo of the ImmuneDB web interface is available at: http://immunedb.com/demoContact:Uh25@drexel.eduSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-11
       
  • D-VASim: an interactive virtual laboratory environment for the simulation
           and analysis of genetic circuits
    • Authors: Baig H; Madsen J.
      Abstract: Summary: Simulation and behavioral analysis of genetic circuits is a standard approach of functional verification prior to their physical implementation. Many software tools have been developed to perform in silico analysis for this purpose, but none of them allow users to interact with the model during runtime. The runtime interaction gives the user a feeling of being in the lab performing a real world experiment. In this work, we present a user-friendly software tool named D-VASim (Dynamic Virtual Analyzer and Simulator), which provides a virtual laboratory environment to simulate and analyze the behavior of genetic logic circuit models represented in an SBML (Systems Biology Markup Language). Hence, SBML models developed in other software environments can be analyzed and simulated in D-VASim. D-VASim offers deterministic as well as stochastic simulation; and differs from other software tools by being able to extract and validate the Boolean logic from the SBML model. D-VASim is also capable of analyzing the threshold value and propagation delay of a genetic circuit model.Availability and Implementation: D-VASim is available for Windows and Mac OS and can be downloaded from bda.compute.dtu.dk/downloads/.Contact:haba@dtu.dk, jama@dtu.dk
      PubDate: 2016-09-11
       
  • ReliableGenome: annotation of genomic regions with high/low variant
           calling concordance
    • Authors: Popitsch N; , Schuh A, et al.
      Abstract: Motivation: The increasing adoption of clinical whole-genome resequencing (WGS) demands for highly accurate and reproducible variant calling (VC) methods. The observed discordance between state-of-the-art VC pipelines, however, indicates that the current practice still suffers from non-negligible numbers of false positive and negative SNV and INDEL calls that were shown to be enriched among discordant calls but also in genomic regions with low sequence complexity.Results: Here, we describe our method ReliableGenome (RG) for partitioning genomes into high and low concordance regions with respect to a set of surveyed VC pipelines. Our method combines call sets derived by multiple pipelines from arbitrary numbers of datasets and interpolates expected concordance for genomic regions without data. By applying RG to 219 deep human WGS datasets, we demonstrate that VC concordance depends predominantly on genomic context rather than the actual sequencing data which manifests in high recurrence of regions that can/cannot be reliably genotyped by a single method. This enables the application of pre-computed regions to other data created with comparable sequencing technology and software. RG outperforms comparable efforts in predicting VC concordance and false positive calls in low-concordance regions which underlines its usefulness for variant filtering, annotation and prioritization. RG allows focusing resource-intensive algorithms (e.g. consensus calling methods) on the smaller, discordant share of the genome (20–30%) which might result in increased overall accuracy at reasonable costs. Our method and analysis of discordant calls may further be useful for development, benchmarking and optimization of VC algorithms and for the relative comparison of call sets between different studies/pipelines.Availability and Implementation: RG was implemented in Java, source code and binaries are freely available for non-commercial use at https://github.com/popitsch/wtchg-rg/.Contact:niko@wtchg.ox.ac.ukSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-07
       
  • tHapMix: simulating tumour samples through haplotype mixtures
    • Authors: Ivakhno S; Colombo C, Tanner S, et al.
      Abstract: Motivation: Large-scale rearrangements and copy number changes combined with different modes of clonal evolution create extensive somatic genome diversity, making it difficult to develop versatile and scalable variant calling tools and create well-calibrated benchmarks.Results: We developed a new simulation framework tHapMix that enables the creation of tumour samples with different ploidy, purity and polyclonality features. It easily scales to simulation of hundreds of somatic genomes, while re-use of real read data preserves noise and biases present in sequencing platforms. We further demonstrate tHapMix utility by creating a simulated set of 140 somatic genomes and showing how it can be used in training and testing of somatic copy number variant calling tools.Availability and implementation: tHapMix is distributed under an open source license and can be downloaded from https://github.com/Illumina/tHapMix.Contact:sivakhno@illumina.comSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-07
       
  • TRI_tool: a web-tool for prediction of protein–protein interactions in
           human transcriptional regulation
    • Authors: Perovic V; Sumonja N, Gemovic B, et al.
      Abstract: Summary: The TRI_tool, a sequence-based web tool for prediction of protein interactions in the human transcriptional regulation, is intended for biomedical investigators who work on understanding the regulation of gene expression. It has an improved predictive performance due to the training on updated, human specific, experimentally validated datasets. The TRI_tool is designed to test up to 100 potential interactions with no time delay and to report both probabilities and binarized predictions.Availability and Implementation:http://www.vin.bg.ac.rs/180/tools/tfpred.php.Contact:vladaper@vinca.rs; nevenav@vinca.rsSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-09-07
       
  • Cas-analyzer: an online tool for assessing genome editing results using
           NGS data
    • Authors: Park J; Lim K, Kim J, et al.
      Abstract: Summary: Genome editing with programmable nucleases has been widely adopted in research and medicine. Next generation sequencing (NGS) platforms are now widely used for measuring the frequencies of mutations induced by CRISPR-Cas9 and other programmable nucleases. Here, we present an online tool, Cas-Analyzer, a JavaScript-based implementation for NGS data analysis. Because Cas-Analyzer is completely used at a client-side web browser on-the-fly, there is no need to upload very large NGS datasets to a server, a time-consuming step in genome editing analysis. Currently, Cas-Analyzer supports various programmable nucleases, including single nucleases and paired nucleases.Availability and Implementation: Free access at http://www.rgenome.net/cas-analyzer/.Contact:sangsubae@hanyang.ac.kr or jskim01@snu.ac.krSupplementary information:Supplementary dataSupplementary data are available at Bioinformatics online.
      PubDate: 2016-08-24
       
 
 
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