Günther Specht

HaploGrep 2: mitochondrial haplogroup classification in the era of high-throughput sequencing

Mitochondrial DNA (mtDNA) profiles can be classified into phylogenetic clusters (haplogroups), which is of great relevance for evolutionary, forensic and medical genetics. With the extensive growth of the underlying phylogenetic tree summarizing the published mtDNA sequences, the manual process of haplogroup classification would be too time-consuming. The previously published classification tool HaploGrep provided an automatic way to address this issue. Here, we present the completely updated version HaploGrep 2 offering several advanced features, including a generic rule-based system for immediate quality control (QC). This allows detecting artificial recombinants and missing variants as well as annotating rare and phantom mutations. Furthermore, the handling of high-throughput data in form of VCF files is now directly supported. For data output, several graphical reports are generated in real time, such as a multiple sequence alignment format, a VCF format and extended haplogroup QC reports, all viewable directly within the application. In addition, HaploGrep 2 generates a publication-ready phylogenetic tree of all input samples encoded relative to the revised Cambridge Reference Sequence. Finally, new distance measures and optimizations of the algorithm increase accuracy and speed-up the application. HaploGrep 2 can be accessed freely and without any registration at http://haplogrep.uibk.ac.at.

Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

BackgroundThe MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions.ResultsHere we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized.ConclusionsOur results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available athttp://cloudgene.uibk.ac.at.

On the impact of text similarity functions on hashtag recommendations in microblogging environments

Microblogging applications such as Twitter are experiencing tremendous success. Microblog users utilize hashtags to categorize posted messages which aim at bringing order to the myriads of microblog messages. However, the percentage of messages incorporating hashtags is small and the used hashtags are very heterogeneous as hashtags may be chosen freely and may consist of any arbitrary combination of characters. This heterogeneity and the lack of use of hashtags lead to significant drawbacks in regards to the search functionality as messages are not categorized in a homogeneous way. In this paper, we present an approach for the recommendation of hashtags suitable for the message the user currently enters which aims at creating a more homogeneous set of hashtags. Furthermore, we present a detailed study on how the similarity measures used for the computation of recommendations influence the final set of recommended hashtags.

Using tag recommendations to homogenize folksonomies in microblogging environments

Microblogging applications such as Twitter are experiencing tremendous success. Twitter users use hashtags to categorize posted messages which aim at bringing order to the chaos of the Twittersphere. However, the percentage of messages including hashtags is very small and the used hashtags are very heterogeneous as hashtags may be chosen freely and may consist of any arbitrary combination of characters. This heterogeneity and the lack of use of hashtags lead to significant drawbacks in regards of the search functionality as messages are not categorized in a homogeneous way. In this paper we present an approach for the recommendation of hashtags suitable for the tweet the user currently enters which aims at creating a more homogeneous set of hashtags. Furthermore, users are encouraged to using hashtags as they are provided with suitable recommendations for hashtags.

Sorry, I was hacked: a classification of compromised twitter accounts

Online social networks like Facebook or Twitter have become powerful information diffusion platforms as they have attracted hundreds of millions of users. The possibility of reaching millions of users within these networks not only attracted standard users, but also cyber-criminals who abuse the networks by spreading spam. This is accomplished by either creating fake accounts, bots, cyborgs or by hacking and compromising accounts. Compromised accounts are subsequently used to spread spam in the name of their legitimate owner. This work sets out to investigate how Twitter users react to having their account hacked and how they deal with compromised accounts. We crawled a data set of tweets in which users state that their account was hacked and subsequently performed a supervised classification of these tweets based on the reaction and behavior of the respective user. We find that 27.30% of the analyzed Twitter users change to a new account once their account was hacked. 50.91% of all users either state that they were hacked or apologize for any unsolicited tweets or direct messages.

#nowplaying Music Dataset: Extracting Listening Behavior from Twitter

The extraction of information from online social networks has become popular in both industry and academia as these data sources allow for innovative applications. However, in the area of music recommender systems and music information retrieval, respective data is hardly exploited. In this paper, we present the #nowplaying dataset, which leverages social media for the creation of a diverse and constantly updated dataset, which describes the music listening behavior of users. For the creation of the dataset, we rely on Twitter, which is frequently facilitated for posting which music the respective user is currently listening to. From such tweets, we extract track and artist information and further metadata. The dataset currently comprises 49 million listening events, 144,011 artists, 1,346,203 tracks and 4,150,615 users which makes it considerably larger than existing datasets.

A Model–View–Controller extension for pervasive multi-client user interfaces

This paper addresses the implementation of pervasive Java Web applications using a development approach that is based on the Model–View–Controller (MVC) design pattern. We combine the MVC methodology with a hierarchical task-based state transition model in order to achieve the distinction between the task state and the view state of an application. More precisely, we propose to add a device-independent TaskStateBean and a device-specific ViewStateBean for each task state as an extension to the J2EE Service to Worker design pattern. Furthermore, we suggest representing the task state and view state transition models as finite state automata in two sets of XML files. This paper shows that the distinction between an application’s task state and view state is both intuitive and facilitates several, otherwise complex, tasks, such as changing devices “on the fly.”

Enhancing ECA Rules for Distributed Active Database Systems

ECA (event/condition/action) rules have been developed for central active database systems. In distributed active database systems the problem of inaccessibility of partial systems raises and thus the undecidability of ECA conditions referring to remote systems. This work proposes an enhancement of ECA rules for distributed active database systems to react also in the case of inaccessibility and undecidability. Therefore, the ECA evaluation will be enhanced to a strict function with the inaccessibility state O and a new alternative action AA enriches the classical ECA rules. The advantages and the usage of this approach are shown by an example of maintaining data consistency in distributed active database systems.

mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud

Next generation sequencing (NGS) allows investigating mitochondrial DNA (mtDNA) characteristics such as heteroplasmy (i.e. intra-individual sequence variation) to a higher level of detail. While several pipelines for analyzing heteroplasmies exist, issues in usability, accuracy of results and interpreting final data limit their usage. Here we present mtDNA-Server, a scalable web server for the analysis of mtDNA studies of any size with a special focus on usability as well as reliable identification and quantification of heteroplasmic variants. The mtDNA-Server workflow includes parallel read alignment, heteroplasmy detection, artefact or contamination identification, variant annotation as well as several quality control metrics, often neglected in current mtDNA NGS studies. All computational steps are parallelized with Hadoop MapReduce and executed graphically with Cloudgene. We validated the underlying heteroplasmy and contamination detection model by generating four artificial sample mix-ups on two different NGS devices. Our evaluation data shows that mtDNA-Server detects heteroplasmies and artificial recombinations down to the 1% level with perfect specificity and outperforms existing approaches regarding sensitivity. mtDNA-Server is currently able to analyze the 1000G Phase 3 data (n = 2,504) in less than 5 h and is freely accessible at https://mtdna-server.uibk.ac.at.

eCOMPAGT integrates mtDNA: import, validation and export of mitochondrial DNA profiles for population genetics, tumour dynamics and genotype-phenotype association studies

BackgroundMitochondrial DNA (mtDNA) is widely being used for population genetics, forensic DNA fingerprinting and clinical disease association studies. The recent past has uncovered severe problems with mtDNA genotyping, not only due to the genotyping method itself, but mainly to the post-lab transcription, storage and report of mtDNA genotypes.DescriptioneCOMPAGT, a system to store, administer and connect phenotype data to all kinds of genotype data is now enhanced by the possibility of storing mtDNA profiles and allowing their validation, linking to phenotypes and export as numerous formats. mtDNA profiles can be imported from different sequence evaluation programs, compared between evaluations and their haplogroup affiliations stored. Furthermore, eCOMPAGT has been improved in its sophisticated transparency (support of MySQL and Oracle), security aspects (by using database technology) and the option to import, manage and store genotypes derived from various genotyping methods (SNPlex, TaqMan, and STRs). It is a software solution designed for project management, laboratory work and the evaluation process all-in-one.ConclusionsThe extended mtDNA version of eCOMPAGT was designed to enable error-free post-laboratory data handling of human mtDNA profiles. This software is suited for small to medium-sized human genetic, forensic and clinical genetic laboratories. The direct support of MySQL and the improved database security options render eCOMPAGT a powerful tool to build an automated workflow architecture for several genotyping methods. eCOMPAGT is freely available at http://dbis-informatik.uibk.ac.at/ecompagt.