A comprehensive map of single-base polymorphisms in the hypervariable LPA kringle IV type 2 copy number variation region.

Lipoprotein (a) [Lp(a)] concentrations are among the strongest genetic risk factors for cardiovascular disease and present pronounced interethnic and interindividual differences. Approximately 90% of Lp(a) variance is controlled by the LPA gene, which contains a 5.6-kb-large copy number variation [kringle IV type 2 (KIV-2) repeat] that generates >40 protein isoforms. Variants within the KIV-2 region are not called in common sequencing projects, leaving up to 70% of the LPA coding region currently unaddressed. To completely assess the variability in LPA, we developed a sequencing strategy for this region and report here the first map of genetic variation in the KIV-2 region, a comprehensively evaluated ultradeep sequencing protocol, and an easy-to-use variant analysis pipeline. We sequenced 123 Central-European individuals and reanalyzed public data of 2,504 individuals from 26 populations. We found 14 different loss-of-function and splice-site mutations, as well as >100, partially even common, missense variants. Some coding variants were frequent in one population but absent in others. This provides novel candidates to explain the large ethnic and individual differences in Lp(a) concentrations. Importantly, our approach and pipeline are also applicable to other similar copy number variable regions, allowing access to regions that are not captured by common genome sequencing.

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.

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.

BACKGROUND: The 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. RESULTS: Here 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. CONCLUSIONS: Our 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 at http://cloudgene.uibk.ac.at.

HaploGrep: a fast and reliable algorithm for automatic classification of mitochondrial DNA haplogroups.

An ongoing source of controversy in mitochondrial DNA (mtDNA) research is based on the detection of numerous errors in mtDNA profiles that led to erroneous conclusions and false disease associations. Most of these controversies could be avoided if the samples' haplogroup status would be taken into consideration. Knowing the mtDNA haplogroup affiliation is a critical prerequisite for studying mechanisms of human evolution and discovering genes involved in complex diseases, and validating phylogenetic consistency using haplogroup classification is an important step in quality control. However, despite the availability of Phylotree, a regularly updated classification tree of global mtDNA variation, the process of haplogroup classification is still time-consuming and error-prone, as researchers have to manually compare the polymorphisms found in a population sample to those summarized in Phylotree, polymorphism by polymorphism, sample by sample. We present HaploGrep, a fast, reliable and straight-forward algorithm implemented in a Web application to determine the haplogroup affiliation of thousands of mtDNA profiles genotyped for the entire mtDNA or any part of it. HaploGrep uses the latest version of Phylotree and offers an all-in-one solution for quality assessment of mtDNA profiles in clinical genetics, population genetics and forensics. HaploGrep can be accessed freely at http://haplogrep.uibk.ac.at.

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

BACKGROUND: Mitochondrial 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. DESCRIPTION: eCOMPAGT, 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. CONCLUSIONS: The 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.

CONAN: copy number variation analysis software for genome-wide association studies.

BACKGROUND: Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs. RESULTS: CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data. CONCLUSIONS: CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at http://genepi-conan.i-med.ac.at.

eCOMPAGT -- efficient combination and management of phenotypes and genotypes for genetic epidemiology.

BACKGROUND: High-throughput genotyping and phenotyping projects of large epidemiological study populations require sophisticated laboratory information management systems. Most epidemiological studies include subject-related personal information, which needs to be handled with care by following data privacy protection guidelines. In addition, genotyping core facilities handling cooperative projects require a straightforward solution to monitor the status and financial resources of the different projects. DESCRIPTION: We developed a database system for an efficient combination and management of phenotypes and genotypes (eCOMPAGT) deriving from genetic epidemiological studies. eCOMPAGT securely stores and manages genotype and phenotype data and enables different user modes with different rights. Special attention was drawn on the import of data deriving from TaqMan and SNPlex genotyping assays. However, the database solution is adjustable to other genotyping systems by programming additional interfaces. Further important features are the scalability of the database and an export interface to statistical software. CONCLUSION: eCOMPAGT can store, administer and connect phenotype data with all kinds of genotype data and is available as a downloadable version at (http://dbis-informatik.uibk.ac.at/ecompagt).

SNPflow: a lightweight application for the processing, storing and automatic quality checking of genotyping assays.

Single nucleotide polymorphisms (SNPs) play a prominent role in modern genetics. Current genotyping technologies such as Sequenom iPLEX, ABI TaqMan and KBioscience KASPar made the genotyping of huge SNP sets in large populations straightforward and allow the generation of hundreds of thousands of genotypes even in medium sized labs. While data generation is straightforward, the subsequent data conversion, storage and quality control steps are time-consuming, error-prone and require extensive bioinformatic support. In order to ease this tedious process, we developed SNPflow. SNPflow is a lightweight, intuitive and easily deployable application, which processes genotype data from Sequenom MassARRAY (iPLEX) and ABI 7900HT (TaqMan, KASPar) systems and is extendible to other genotyping methods as well. SNPflow automatically converts the raw output files to ready-to-use genotype lists, calculates all standard quality control values such as call rate, expected and real amount of replicates, minor allele frequency, absolute number of discordant replicates, discordance rate and the p-value of the HWE test, checks the plausibility of the observed genotype frequencies by comparing them to HapMap/1000-Genomes, provides a module for the processing of SNPs, which allow sex determination for DNA quality control purposes and, finally, stores all data in a relational database. SNPflow runs on all common operating systems and comes as both stand-alone version and multi-user version for laboratory-wide use. The software, a user manual, screenshots and a screencast illustrating the main features are available at http://genepi-snpflow.i-med.ac.at.