ClusTrack: Feature Extraction and Similarity Measures for Clustering of Genome-Wide Data Sets

Clustering is a popular technique for explorative analysis of data, as it can reveal subgroupings and similarities between data in an unsupervised manner. While clustering is routinely applied to gene expression data, there is a lack of appropriate general methodology for clustering of sequence-level genomic and epigenomic data, e.g. ChIP-based data. We here introduce a general methodology for clustering data sets of coordinates relative to a genome assembly, i.e. genomic tracks. By defining appropriate feature extraction approaches and similarity measures, we allow biologically meaningful clustering to be performed for genomic tracks using standard clustering algorithms. An implementation of the methodology is provided through a tool, ClusTrack, which allows fine-tuned clustering analyses to be specified through a web-based interface. We apply our methods to the clustering of occupancy of the H3K4me1 histone modification in samples from a range of different cell types. The majority of samples form meaningful subclusters, confirming that the definitions of features and similarity capture biological, rather than technical, variation between the genomic tracks. Input data and results are available, and can be reproduced, through a Galaxy Pages document at http://hyperbrowser.uio.no/hb/u/hb-superuser/p/clustrack. The clustering functionality is available as a Galaxy tool, under the menu option "Specialized analyzis of tracks", and the submenu option "Cluster tracks based on genome level similarity", at the Genomic HyperBrowser server: http://hyperbrowser.uio.no/hb/.     

Detecting Structure of Haplotypes and Local Ancestry

We present a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. This allows us to model two scales of linkage disequilibrium (one within a group of haplotypes and one between groups), thereby taking advantage of rich haplotype information to infer local ancestry of admixed individuals. Our method outperforms competing state-of-the-art methods, particularly for regions of small ancestral track lengths. Applying our method to Mexican samples in HapMap3, we found two regions on chromosomes 6 and 8 that show significant departure of local ancestry from the genome-wide average. A software package implementing the methods described in this article is freely available at http://bcm.edu/cnrc/mcmcmc.     

Detecting Local Haplotype Sharing and Haplotype Association

A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.     

Arctic Small Rodents Have Diverse Diets and Flexible Food Selection

The ecology of small rodent food selection is poorly understood, as mammalian herbivore food selection theory has mainly been developed by studying ungulates. Especially, the effect of food availability on food selection in natural habitats where a range of food items are available is unknown. We studied diets and selectivity of grey-sided voles (Myodes rufocanus) and tundra voles (Microtus oeconomus), key herbivores in European tundra ecosystems, using DNA metabarcoding, a novel method enabling taxonomically detailed diet studies. In order to cover the range of food availabilities present in the wild, we employed a large-scale study design for sampling data on food availability and vole diets. Both vole species had ingested a range of plant species and selected particularly forbs and grasses. Grey-sided voles also selected ericoid shrubs and tundra voles willows. Availability of a food item rarely affected its utilization directly, although seasonal changes of diets and selection suggest that these are positively correlated with availability. Moreover, diets and selectivity were affected by availability of alternative food items. These results show that the focal sub-arctic voles have diverse diets and flexible food preferences and rarely compensate low availability of a food item with increased searching effort. Diet diversity itself is likely to be an important trait and has previously been underrated owing to methodological constraints. We suggest that the roles of alternative food item availability and search time limitations for small rodent feeding ecology should be investigated.

Nomenclature

Annotated Checklist of the Panarctic Flora (PAF), Vascular plants. Available at: http://nhm2.uio.no/paf/, accessed 15.6.2012.     

Viral Quasispecies Assembly via Maximal Clique Enumeration

Virus populations can display high genetic diversity within individual hosts. The intra-host collection of viral haplotypes, called viral quasispecies, is an important determinant of virulence, pathogenesis, and treatment outcome. We present HaploClique, a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples. We develop a statistical model for paired-end reads accounting for mutations, insertions, and deletions. Using an iterative maximal clique enumeration approach, read pairs are assembled into haplotypes of increasing length, eventually enabling global haplotype assembly. The performance of our quasispecies assembly method is assessed on simulated data for varying population characteristics and sequencing technology parameters. Owing to its paired-end handling, HaploClique compares favorably to state-of-the-art haplotype inference methods. It can reconstruct error-free full-length haplotypes from low coverage samples and detect large insertions and deletions at low frequencies. We applied HaploClique to sequencing data derived from a clinical hepatitis C virus population of an infected patient and discovered a novel deletion of length 357±167 bp that was validated by two independent long-read sequencing experiments. HaploClique is available at https://github.com/armintoepfer/haploclique. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.     

ProADD: A database on Protein Aggregation Diseases

ProADD, a database for protein aggregation diseases, is developed to organize the data under a single platform to facilitate easy access for researchers. Diseases caused due to protein aggregation and the proteins involved in each of these diseases are integrated. The database helps in classification of proteins involved in the protein aggregation diseases based on sequence and structural analysis. Analysis of proteins can be done to mine patterns prevailing among the aggregating proteins.

Availability

http://bicmku.in/ProADD     

SDhaP: haplotype assembly for diploids and polyploids via semi-definite programming

Background

The goal of haplotype assembly is to infer haplotypes of an individual from a mixture of sequenced chromosome fragments. Limited lengths of paired-end sequencing reads and inserts render haplotype assembly computationally challenging; in fact, most of the problem formulations are known to be NP-hard. Dimensions (and, therefore, difficulty) of the haplotype assembly problems keep increasing as the sequencing technology advances and the length of reads and inserts grow. The computational challenges are even more pronounced in the case of polyploid haplotypes, whose assembly is considerably more difficult than in the case of diploids. Fast, accurate, and scalable methods for haplotype assembly of diploid and polyploid organisms are needed.

Results

We develop a novel framework for diploid/polyploid haplotype assembly from high-throughput sequencing data. The method formulates the haplotype assembly problem as a semi-definite program and exploits its special structure – namely, the low rank of the underlying solution – to solve it rapidly and with high accuracy. The developed framework is applicable to both diploid and polyploid species. The code for SDhaP is freely available at https://sourceforge.net/projects/sdhap.

Conclusion

Extensive benchmarking tests on both real and simulated data show that the proposed algorithms outperform several well-known haplotype assembly methods in terms of either accuracy or speed or both. Useful recommendations for coverages needed to achieve near-optimal solutions are also provided.     

FORMIDABEL: The Belgian Ants Database

FORMIDABEL is a database of Belgian Ants containing more than 27.000 occurrence records. These records originate from collections, field sampling and literature. The database gives information on 76 native and 9 introduced ant species found in Belgium. The collection records originated mainly from the ants collection in Royal Belgian Institute of Natural Sciences (RBINS), the ‘Gaspar’ Ants collection in Gembloux and the zoological collection of the University of Liège (ULG). The oldest occurrences date back from May 1866, the most recent refer to August 2012. FORMIDABEL is a work in progress and the database is updated twice a year.The latest version of the dataset is publicly and freely accessible through this url: http://ipt.biodiversity.be/resource.do?r=formidabel. The dataset is also retrievable via the GBIF data portal through this link: http://data.gbif.org/datasets/resource/14697A dedicated geo-portal, developed by the Belgian Biodiversity Platform is accessible at: http://www.formicidae-atlas.bePurpose: FORMIDABEL is a joint cooperation of the Flemish ants working group “Polyergus” (http://formicidae.be) and the Wallonian ants working group “FourmisWalBru” (http://fourmiswalbru.be). The original database was created in 2002 in the context of the preliminary red data book of Flemish Ants (Dekoninck et al. 2003). Later, in 2005, data from the Southern part of Belgium; Wallonia and Brussels were added. In 2012 this dataset was again updated for the creation of the first Belgian Ants Atlas (Figure 1) (Dekoninck et al. 2012). The main purpose of this atlas was to generate maps for all outdoor-living ant species in Belgium using an overlay of the standard Belgian ecoregions. By using this overlay for most species, we can discern a clear and often restricted distribution pattern in Belgium, mainly based on vegetation and soil types.Open in a separate windowFigure 1.www.formicidae-atlas.be     

Mammalian Mitochondrial ncRNA Database

Mammalian Mitochondrial ncRNA is a web-based database, which provides specific information on non-coding RNA in mammals. This database includes easy searching, comparing with BLAST and retrieving information on predicted structure and its function about mammalian ncRNAs.

Availability

The database is available for free at http://www.iitm.ac.in/bioinfo/mmndb/     

A database of natural products and chemical entities from marine habitat

Marine compound database consists of marine natural products and chemical entities, collected from various literature sources, which are known to possess bioactivity against human diseases. The database is constructed using html code. The 12 categories of 182 compounds are provided with the source, compound name, 2-dimensional structure, bioactivity and clinical trial information. The database is freely available online and can be accessed at http://www.progenebio.in/mcdb/index.htm     

GINDEL: Accurate Genotype Calling of Insertions and Deletions from Low Coverage Population Sequence Reads

Insertions and deletions (indels) are important types of structural variations. Obtaining accurate genotypes of indels may facilitate further genetic study. There are a few existing methods for calling indel genotypes from sequence reads. However, none of these tools can accurately call indel genotypes for indels of all lengths, especially for low coverage sequence data. In this paper, we present GINDEL, an approach for calling genotypes of both insertions and deletions from sequence reads. GINDEL uses a machine learning approach which combines multiple features extracted from next generation sequencing data. We test our approach on both simulated and real data and compare with existing tools, including Genome STRiP, Pindel and Clever-sv. Results show that GINDEL works well for deletions larger than 50 bp on both high and low coverage data. Also, GINDEL performs well for insertion genotyping on both simulated and real data. For comparison, Genome STRiP performs less well for shorter deletions (50–200 bp) on both simulated and real sequence data from the 1000 Genomes Project. Clever-sv performs well for intermediate deletions (200–1500 bp) but is less accurate when coverage is low. Pindel only works well for high coverage data, but does not perform well at low coverage. To summarize, we show that GINDEL not only can call genotypes of insertions and deletions (both short and long) for high and low coverage population sequence data, but also is more accurate and efficient than other approaches. The program GINDEL can be downloaded at: http://sourceforge.net/p/gindel     

HNHDb: A database on pattern based classification of HNH domains reveals functional relevance of sequence patterns and domain associations.

The HNH Database is a collection and sequence-based classification of HNH domain proteins. The database contains about 1913 HNH domain containing proteins, and is classified into 10 subsets based on the sequence pattern. Each of these subsets has unique signature sequences. We have shown a correlation between the subset combination and their domain association and function. Functional divergence of this domain may be due to the combination of these conserved patterns and the large variations in the non-conserved regions. HNHDb is freely available at http://bicmku.in:8081/hnh.     

PubstractHelper: A Web-based Text-Mining Tool for Marking Sentences in Abstracts from PubMed Using Multiple User-Defined Keywords

While a huge amount of information about biological literature can be obtained by searching the PubMed database, reading through all the titles and abstracts resulting from such a search for useful information is inefficient. Text mining makes it possible to increase this efficiency. Some websites use text mining to gather information from the PubMed database; however, they are database-oriented, using pre-defined search keywords while lacking a query interface for user-defined search inputs. We present the PubMed Abstract Reading Helper (PubstractHelper) website which combines text mining and reading assistance for an efficient PubMed search. PubstractHelper can accept a maximum of ten groups of keywords, within each group containing up to ten keywords. The principle behind the text-mining function of PubstractHelper is that keywords contained in the same sentence are likely to be related. PubstractHelper highlights sentences with co-occurring keywords in different colors. The user can download the PMID and the abstracts with color markings to be reviewed later. The PubstractHelper website can help users to identify relevant publications based on the presence of related keywords, which should be a handy tool for their research.

Availability

http://bio.yungyun.com.tw/ATM/PubstractHelper.aspx and http://holab.med.ncku.edu.tw/ATM/PubstractHelper.aspx     

CytokineDB: a database collecting biological information

Cytokines are subdivided in 12 sub-families and are described as multi-functional molecules that play an important biological activity in host defense system against pathogens, in homeostasis, tissue repair, cell growth and development. CytokineDB is an annotated database that collects biological information regarding the cytokines family in human and will be periodically updated by including new biological information. This database is freely available online and can be accessed at the URL: http://www.cro-m.eu/CytokineDB/     

Genomer — A Swiss Army Knife for Genome Scaffolding

The increasing accessibility and reduced costs of sequencing has made genome analysis accessible to more and more researchers. Yet there remains a steep learning curve in the subsequent computational steps required to process raw reads into a database-deposited genome sequence. Here we describe “Genomer,” a tool to simplify the manual tasks of finishing and uploading a genome sequence to a database. Genomer can format a genome scaffold into the common files required for submission to GenBank. This software also simplifies updating a genome scaffold by allowing a human-readable YAML format file to be edited instead of large sequence files. Genomer is written as a command line tool and is an effort to make the manual process of genome scaffolding more robust and reproducible. Extensive documentation and video tutorials are available at http://next.gs.     

MOABS: model based analysis of bisulfite sequencing data

Bisulfite sequencing (BS-seq) is the gold standard for studying genome-wide DNA methylation. We developed MOABS to increase the speed, accuracy, statistical power and biological relevance of BS-seq data analysis. MOABS detects differential methylation with 10-fold coverage at single-CpG resolution based on a Beta-Binomial hierarchical model and is capable of processing two billion reads in 24 CPU hours. Here, using simulated and real BS-seq data, we demonstrate that MOABS outperforms other leading algorithms, such as Fisher’s exact test and BSmooth. Furthermore, MOABS analysis can be easily extended to differential 5hmC analysis using RRBS and oxBS-seq. MOABS is available at http://code.google.com/p/moabs/.     

Large-Scale Event Extraction from Literature with Multi-Level Gene Normalization

Text mining for the life sciences aims to aid database curation, knowledge summarization and information retrieval through the automated processing of biomedical texts. To provide comprehensive coverage and enable full integration with existing biomolecular database records, it is crucial that text mining tools scale up to millions of articles and that their analyses can be unambiguously linked to information recorded in resources such as UniProt, KEGG, BioGRID and NCBI databases. In this study, we investigate how fully automated text mining of complex biomolecular events can be augmented with a normalization strategy that identifies biological concepts in text, mapping them to identifiers at varying levels of granularity, ranging from canonicalized symbols to unique gene and proteins and broad gene families. To this end, we have combined two state-of-the-art text mining components, previously evaluated on two community-wide challenges, and have extended and improved upon these methods by exploiting their complementary nature. Using these systems, we perform normalization and event extraction to create a large-scale resource that is publicly available, unique in semantic scope, and covers all 21.9 million PubMed abstracts and 460 thousand PubMed Central open access full-text articles. This dataset contains 40 million biomolecular events involving 76 million gene/protein mentions, linked to 122 thousand distinct genes from 5032 species across the full taxonomic tree. Detailed evaluations and analyses reveal promising results for application of this data in database and pathway curation efforts. The main software components used in this study are released under an open-source license. Further, the resulting dataset is freely accessible through a novel API, providing programmatic and customized access (http://www.evexdb.org/api/v001/). Finally, to allow for large-scale bioinformatic analyses, the entire resource is available for bulk download from http://evexdb.org/download/, under the Creative Commons – Attribution – Share Alike (CC BY-SA) license.     

PANADA: Protein Association Network Annotation,Determination and Analysis

Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/.     

GMEnzy: A Genetically Modified Enzybiotic Database

GMEs are genetically modified enzybiotics created through molecular engineering approaches to deal with the increasing problem of antibiotic resistance prevalence. We present a fully manually curated database, GMEnzy, which focuses on GMEs and their design strategies, production and purification methods, and biological activity data. GMEnzy collects and integrates all available GMEs and their related information into one web based database. Currently GMEnzy holds 186 GMEs from published literature. The GMEnzy interface is easy to use, and allows users to rapidly retrieve data according to desired search criteria. GMEnzy’s construction will increase the efficiency and convenience of improving these bioactive proteins for specific requirements, and will expand the arsenal available for researches to control drug-resistant pathogens. This database will prove valuable for researchers interested in genetically modified enzybiotics studies. GMEnzy is freely available on the Web at http://biotechlab.fudan.edu.cn/database/gmenzy/.