DaMold: A data-mining platform for variant annotation and visualization in molecular diagnostics research.

Next-generation sequencing (NGS) has become a powerful and efficient tool for routine mutation screening in clinical research. As each NGS test yields hundreds of variants, the current challenge is to meaningfully interpret the data and select potential candidates. Analyzing each variant while manually investigating several relevant databases to collect specific information is a cumbersome and time-consuming process, and it requires expertise and familiarity with these databases. Thus, a tool that can seamlessly annotate variants with clinically relevant databases under one common interface would be of great help for variant annotation, cross-referencing, and visualization. This tool would allow variants to be processed in an automated and high-throughput manner and facilitate the investigation of variants in several genome browsers. Several analysis tools are available for raw sequencing-read processing and variant identification, but an automated variant filtering, annotation, cross-referencing, and visualization tool is still lacking. To fulfill these requirements, we developed DaMold, a Web-based, user-friendly tool that can filter and annotate variants and can access and compile information from 37 resources. It is easy to use, provides flexible input options, and accepts variants from NGS and Sanger sequencing as well as hotspots in VCF and BED formats. DaMold is available as an online application at http://damold.platomics.com/index.html, and as a Docker container and virtual machine at https://sourceforge.net/projects/damold/.

ClinQC: a tool for quality control and cleaning of Sanger and NGS data in clinical research.

BACKGROUND: Traditional Sanger sequencing has been used as a gold standard method for genetic testing in clinic to perform single gene test, which has been a cumbersome and expensive method to test several genes in heterogeneous disease such as cancer. With the advent of Next Generation Sequencing technologies, which produce data on unprecedented speed in a cost effective manner have overcome the limitation of Sanger sequencing. Therefore, for the efficient and affordable genetic testing, Next Generation Sequencing has been used as a complementary method with Sanger sequencing for disease causing mutation identification and confirmation in clinical research. However, in order to identify the potential disease causing mutations with great sensitivity and specificity it is essential to ensure high quality sequencing data. Therefore, integrated software tools are lacking which can analyze Sanger and NGS data together and eliminate platform specific sequencing errors, low quality reads and support the analysis of several sample/patients data set in a single run. RESULTS: We have developed ClinQC, a flexible and user-friendly pipeline for format conversion, quality control, trimming and filtering of raw sequencing data generated from Sanger sequencing and three NGS sequencing platforms including Illumina, 454 and Ion Torrent. First, ClinQC convert input read files from their native formats to a common FASTQ format and remove adapters, and PCR primers. Next, it split bar-coded samples, filter duplicates, contamination and low quality sequences and generates a QC report. ClinQC output high quality reads in FASTQ format with Sanger quality encoding, which can be directly used in down-stream analysis. It can analyze hundreds of sample/patients data in a single run and generate unified output files for both Sanger and NGS sequencing data. Our tool is expected to be very useful for quality control and format conversion of Sanger and NGS data to facilitate improved downstream analysis and mutation screening. CONCLUSIONS: ClinQC is a powerful and easy to handle pipeline for quality control and trimming in clinical research. ClinQC is written in Python with multiprocessing capability, run on all major operating systems and is available at https://sourceforge.net/projects/clinqc.

Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens.

BACKGROUND: The simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate. METHODS: Candidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients. RESULT: Methods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly. CONCLUSION: Protein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto-antibody signatures for diagnostic purposes.

RGG: a general GUI Framework for R scripts.

BACKGROUND: R is the leading open source statistics software with a vast number of biostatistical and bioinformatical analysis packages. To exploit the advantages of R, extensive scripting/programming skills are required. RESULTS: We have developed a software tool called R GUI Generator (RGG) which enables the easy generation of Graphical User Interfaces (GUIs) for the programming language R by adding a few Extensible Markup Language (XML) - tags. RGG consists of an XML-based GUI definition language and a Java-based GUI engine. GUIs are generated in runtime from defined GUI tags that are embedded into the R script. User-GUI input is returned to the R code and replaces the XML-tags. RGG files can be developed using any text editor. The current version of RGG is available as a stand-alone software (RGGRunner) and as a plug-in for JGR. CONCLUSION: RGG is a general GUI framework for R that has the potential to introduce R statistics (R packages, built-in functions and scripts) to users with limited programming skills and helps to bridge the gap between R developers and GUI-dependent users. RGG aims to abstract the GUI development from individual GUI toolkits by using an XML-based GUI definition language. Thus RGG can be easily integrated in any software. The RGG project further includes the development of a web-based repository for RGG-GUIs. RGG is an open source project licensed under the Lesser General Public License (LGPL) and can be downloaded freely at (http://rgg.r-forge.r-project.org).

Consensus genes of the literature to predict breast cancer recurrence.

BACKGROUND: Extensive efforts have been undertaken to discover genes relevant for breast cancer prognosis. Yet, in current opinion, with little overlap in findings. We aimed to reanalyze molecular prediction of breast cancer recurrence. METHODS: From 44 published gene lists relevant for breast cancer prognosis, we extracted 374 genes, which, besides other quality criteria, are recorded at least twice. From eight published microarray datasets, a single dataset of 1,067 breast cancer patients was created, using transformation to 'probability of expression' scale. For recurrence analysis, the Cox proportional hazards model was applied. RESULTS: The 374 genes, termed '374 Gene Set', are highly enriched in cell cycle genes. The '374 Gene Set' is significantly associated with breast cancer recurrence (p = 2 x 10(-12), log-rank test) in the meta set of 1,067 patients, showing an estimated Hazard Ratio of recurrence for the 'poor' prognosis group compared to the 'good' prognosis group of 2.03 (95% confidence interval, 1.66-2.48). Notably, the '374 Gene Set' is significantly associated with recurrence in untreated patients. In multivariate analysis, including the standard histopathological parameters, only tumor size and the '374 Gene Set' remain independent predictors of recurrence. External validation further confirmed the prognostic relevance of the gene set (253 patients, p = 0.001, log-rank test). CONCLUSIONS: The '374 Gene Set' comprises a molecular basis of metastatic breast cancer progression. Starting from this gene set it might be possible to construct a clinically relevant classifier, which then again needs to be validated.

Substantial variation in the hepatitis B surface antigen (HBsAg) in hepatitis B virus (HBV)-positive patients from South Africa: Reliable detection of HBV by the Elecsys HBsAg II assay.

BACKGROUND: It is essential that hepatitis B surface antigen (HBsAg) diagnostic assays reliably detect genetic diversity in the major hydrophilic region (MHR) of HBsAg to avoid false-negative results. Mutations in this domain display marked ethno-geographic variation and may lead to failure to diagnose hepatitis B virus (HBV) infection. OBJECTIVES: Evaluate diagnostic performance of the Elecsys® HBsAg II Qualitative assay in a cohort of South African HBV-positive blood donors. STUDY DESIGN: A total of 179 South African HBsAg- and HBV DNA > 100 IU/mL-positive blood donor samples were included. Samples were sequenced for genetic variation in HBsAg MHR using next-generation ultra-deep sequencing. HBsAg seropositivity was determined using the Roche Elecsys HBsAg II Qualitative assay. Mutation rates were compared between the first (amino acids 124-137) and second (amino acids 139-147) loops of the immunodominant MHR 'a' determinant region. Frequency of occult HBV infection-associated Y100C mutations was also determined. RESULTS: We observed a total of 279 MHR mutations (117 variants) in 102 (57%) samples, of which 91 were located in the 'a' determinant region. The major vaccine-induced escape mutation G145R was observed in two samples. All occult HBV infection-associated Y100C and common diagnostic and vaccine-escape-associated P120T, G145R, K122R, M133L, M133T, Q129H, G130N, and T126S mutations were reliably detected by the assay, which consistently detected the presence of HBsAg in all 179 samples including samples with 11 novel mutations. CONCLUSIONS: Despite substantial variation in HBsAg MHR, the Elecsys HBsAg II Qualitative assay robustly detects HBV infection in this South African cohort.

Frequency of hepatitis B surface antigen variants (HBsAg) in hepatitis B virus genotype B and C infected East- and Southeast Asian patients: Detection by the Elecsys® HBsAg II assay.

BACKGROUND: To avoid false negative results, hepatitis B surface antigen (HBsAg) assays need to detect samples with mutations in the immunodominant 'a' determinant region, which vary by ethnographic region. OBJECTIVE: We evaluated the prevalence and type of HBsAg mutations in a hepatitis B virus (HBV)-infected East- and Southeast Asian population, and the diagnostic performance of the Elecsys® HBsAg II Qualitative assay. STUDY DESIGN: We analyzed 898 samples from patients with HBV infection from four sites (China [Beijing and Guangzhou], Korea and Vietnam). HBsAg mutations were detected and sequenced using highly sensitive ultra-deep sequencing and compared between the first (amino acids 124-137) and second (amino acids 139-147) loops of the 'a' determinant region using the Elecsys® HBsAg II Qualitative assay. RESULTS: Overall, 237 distinct amino acid mutations in the major hydrophilic region were identified; mutations were present in 660 of 898 HBV-infected patient samples (73.5%). Within the pool of 237 distinct mutations, the majority of the amino acid mutations were found in HBV genotype C (64.8%). We identified 25 previously unknown distinct mutations, mostly prevalent in genotype C-infected Korean patients (n = 18) followed by Chinese (n = 12) patients. All 898 samples were correctly identified by the Elecsys® HBsAg II Qualitative assay. CONCLUSIONS: We observed 237 distinct (including 25 novel) mutations, demonstrating the complexity of HBsAg variants in HBV-infected East- and Southeast Asian patients. The Elecsys® HBsAg II Qualitative assay can reliably detect HBV-positive samples and is suitable for routine diagnostic use in East and Southeast Asia.

Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition.

BACKGROUND: Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult. RESULTS: A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of Enterobacteriaceae, non-fermenter and clinical relevant Candida species. The observed detection limits varied from 10 cells (e.g. E. coli) to 10(5) cells (S. aureus) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241). CONCLUSION: The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification, Validation and Annotation in Human Molecular Genetics.

Traditional Sanger sequencing as well as Next-Generation Sequencing have been used for the identification of disease causing mutations in human molecular research. The majority of currently available tools are developed for research and explorative purposes and often do not provide a complete, efficient, one-stop solution. As the focus of currently developed tools is mainly on NGS data analysis, no integrative solution for the analysis of Sanger data is provided and consequently a one-stop solution to analyze reads from both sequencing platforms is not available. We have therefore developed a new pipeline called MutAid to analyze and interpret raw sequencing data produced by Sanger or several NGS sequencing platforms. It performs format conversion, base calling, quality trimming, filtering, read mapping, variant calling, variant annotation and analysis of Sanger and NGS data under a single platform. It is capable of analyzing reads from multiple patients in a single run to create a list of potential disease causing base substitutions as well as insertions and deletions. MutAid has been developed for expert and non-expert users and supports four sequencing platforms including Sanger, Illumina, 454 and Ion Torrent. Furthermore, for NGS data analysis, five read mappers including BWA, TMAP, Bowtie, Bowtie2 and GSNAP and four variant callers including GATK-HaplotypeCaller, SAMTOOLS, Freebayes and VarScan2 pipelines are supported. MutAid is freely available at https://sourceforge.net/projects/mutaid.

MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics.

BACKGROUND: Bisulfite (BS) conversion-based and methylation-sensitive restriction enzyme (MSRE)-based PCR methods have been the most commonly used techniques for locus-specific DNA methylation analysis. However, both methods have advantages and limitations. Thus, an integrated approach would be extremely useful to quantify the DNA methylation status successfully with great sensitivity and specificity. Designing specific and optimized primers for target regions is the most critical and challenging step in obtaining the adequate DNA methylation results using PCR-based methods. Currently, no integrated, optimized, and high-throughput methylation-specific primer design software methods are available for both BS- and MSRE-based methods. Therefore an integrated, powerful, and easy-to-use methylation-specific primer design pipeline with great accuracy and success rate will be very useful. RESULTS: We have developed a new web-based pipeline, called MSP-HTPrimer, to design primers pairs for MSP, BSP, pyrosequencing, COBRA, and MSRE assays on both genomic strands. First, our pipeline converts all target sequences into bisulfite-treated templates for both forward and reverse strand and designs all possible primer pairs, followed by filtering for single nucleotide polymorphisms (SNPs) and known repeat regions. Next, each primer pairs are annotated with the upstream and downstream RefSeq genes, CpG island, and cut sites (for COBRA and MSRE). Finally, MSP-HTPrimer selects specific primers from both strands based on custom and user-defined hierarchical selection criteria. MSP-HTPrimer produces a primer pair summary output table in TXT and HTML format for display and UCSC custom tracks for resulting primer pairs in GTF format. CONCLUSIONS: MSP-HTPrimer is an integrated, web-based, and high-throughput pipeline and has no limitation on the number and size of target sequences and designs MSP, BSP, pyrosequencing, COBRA, and MSRE assays. It is the only pipeline, which automatically designs primers on both genomic strands to increase the success rate. It is a standalone web-based pipeline, which is fully configured within a virtual machine and thus can be readily used without any configuration. We have experimentally validated primer pairs designed by our pipeline and shown a very high success rate of primer pairs: out of 66 BSP primer pairs, 63 were successfully validated without any further optimization step and using the same qPCR conditions. The MSP-HTPrimer pipeline is freely available from http://sourceforge.net/p/msp-htprimer.

MSRE-HTPrimer: a high-throughput and genome-wide primer design pipeline optimized for epigenetic research.

BACKGROUND: Methylation-sensitive restriction enzymes-polymerase chain reaction (MSRE-PCR) has been used in epigenetic research to identify genome-wide and gene-specific DNA methylation. Currently, epigenome-wide discovery studies provide many candidate regions for which the MSREqPCR approach can be very effective to confirm the findings. MSREqPCR provides high multiplexing capabilities also when starting with limited amount of DNA-like cfDNA to validate many targets in a time- and cost-effective manner. Multiplex design is challenging and cumbersome to define specific primers in an effective manner, and no suitable software tools are freely available for high-throughput primer design in a time-effective manner and to automatically annotate the resulting primers with known SNPs, CpG, repeats, and RefSeq genes. Therefore a robust, powerful, high-throughput, optimized, and methylation-specific primer design tool with great accuracy will be very useful. RESULTS: We have developed a novel pipeline, called MSRE-HTPrimer, to design MSRE-PCR and genomic PCR primers pairs in a very efficient manner and with high success rate. First, our pipeline designs all possible PCR primer pairs and oligos, followed by filtering for SNPs loci and repeat regions. Next, each primer pair is annotated with the number of cut sites in primers and amplicons, upstream and downstream genes, and CpG islands loci. Finally, MSRE-HTPrimer selects resulting primer pairs for all target sequences based on a custom quality matrix defined by the user. MSRE-HTPrimer produces a table for all resulting primer pairs as well as a custom track in GTF file format for each target sequence to visualize it in UCSC genome browser. CONCLUSIONS: MSRE-HTPrimer, based on Primer3, is a high-throughput pipeline and has no limitation on the number and size of target sequences for primer design and provides full flexibility to customize it for specific requirements. It is a standalone web-based pipeline, which is fully configured within a virtual machine and thus can be readily used without any configuration. We have experimentally validated primer pairs designed by our pipeline and shown a very high success rate of primer pairs: out of 190 primer pairs, 71 % could be successfully validated. The MSRE-HTPrimer software is freely available from http://sourceforge.net/p/msrehtprimer/wiki/Virtual_Machine/ as a virtual machine.

Erratum to: MSRE-HTPrimer: a high-throughput and genome-wide primer design pipeline optimized for epigenetic research.

[This corrects the article DOI: 10.1186/s13148-016-0190-9.].

Analysis and Visualization Tool for Targeted Amplicon Bisulfite Sequencing on Ion Torrent Sequencers.

Targeted sequencing of PCR amplicons generated from bisulfite deaminated DNA is a flexible, cost-effective way to study methylation of a sample at single CpG resolution and perform subsequent multi-target, multi-sample comparisons. Currently, no platform specific protocol, support, or analysis solution is provided to perform targeted bisulfite sequencing on a Personal Genome Machine (PGM). Here, we present a novel tool, called TABSAT, for analyzing targeted bisulfite sequencing data generated on Ion Torrent sequencers. The workflow starts with raw sequencing data, performs quality assessment, and uses a tailored version of Bismark to map the reads to a reference genome. The pipeline visualizes results as lollipop plots and is able to deduce specific methylation-patterns present in a sample. The obtained profiles are then summarized and compared between samples. In order to assess the performance of the targeted bisulfite sequencing workflow, 48 samples were used to generate 53 different Bisulfite-Sequencing PCR amplicons from each sample, resulting in 2,544 amplicon targets. We obtained a mean coverage of 282X using 1,196,822 aligned reads. Next, we compared the sequencing results of these targets to the methylation level of the corresponding sites on an Illumina 450k methylation chip. The calculated average Pearson correlation coefficient of 0.91 confirms the sequencing results with one of the industry-leading CpG methylation platforms and shows that targeted amplicon bisulfite sequencing provides an accurate and cost-efficient method for DNA methylation studies, e.g., to provide platform-independent confirmation of Illumina Infinium 450k methylation data. TABSAT offers a novel way to analyze data generated by Ion Torrent instruments and can also be used with data from the Illumina MiSeq platform. It can be easily accessed via the Platomics platform, which offers a web-based graphical user interface along with sample and parameter storage. TABSAT is freely available under a GNU General Public License version 3.0 (GPLv3) at https://github.com/tadkeys/tabsat/ and http://demo.platomics.com/.

Methylation of ribosomal RNA by NSUN5 is a conserved mechanism modulating organismal lifespan.

Several pathways modulating longevity and stress resistance converge on translation by targeting ribosomal proteins or initiation factors, but whether this involves modifications of ribosomal RNA is unclear. Here, we show that reduced levels of the conserved RNA methyltransferase NSUN5 increase the lifespan and stress resistance in yeast, worms and flies. Rcm1, the yeast homologue of NSUN5, methylates C2278 within a conserved region of 25S rRNA. Loss of Rcm1 alters the structural conformation of the ribosome in close proximity to C2278, as well as translational fidelity, and favours recruitment of a distinct subset of oxidative stress-responsive mRNAs into polysomes. Thus, rather than merely being a static molecular machine executing translation, the ribosome exhibits functional diversity by modification of just a single rRNA nucleotide, resulting in an alteration of organismal physiological behaviour, and linking rRNA-mediated translational regulation to modulation of lifespan, and differential stress response.

Nothing special in the specialist? Draft genome sequence of Cryomyces antarcticus, the most extremophilic fungus from Antarctica.

The draft genome of the Antarctic endemic fungus Cryomyces antarcticus is presented. This rock inhabiting, microcolonial fungus is extremely stress tolerant and it is a model organism for exobiology and studies on stress resistance in Eukaryots. Since this fungus is a specialist in the most extreme environment of the Earth, the analysis of its genome is of important value for the understanding of fungal genome evolution and stress adaptation. A comparison with Neurospora crassa as well as with other microcolonial fungi shows that the fungus has a genome size of 24 Mbp, which is the average in the fungal kingdom. Although sexual reproduction was never observed in this fungus, 34 mating genes are present with protein homologs in the classes Eurotiomycetes, Sordariomycetes and Dothideomycetes. The first analysis of the draft genome did not reveal any significant deviations of this genome from comparative species and mesophilic hyphomycetes.

A survey of tools for the analysis of quantitative PCR (qPCR) data.

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

Double-layered nanoparticle stacks for surface enhanced infrared absorption spectroscopy.

We demonstrate that double-layered stacks of gold and insulator nanoparticles arranged on a flat gold surface dramatically enhance the sensitivity in absorption infrared microscopy. Through morphological variations of the nanoparticles, the frequency of the plasmon resonances can be tuned to match the frequency of the molecular vibration in the mid-infrared region. The results show that the nanostructures enhance the absorption signal of the molecules by a factor of up to ~2.2 × 10(6), while preserving their characteristic line-shape remarkably well.

BIFI: a Taverna plugin for a simplified and user-friendly workflow platform.

BACKGROUND: Heterogeneity in the features, input-output behaviour and user interface for available bioinformatics tools and services is still a bottleneck for both expert and non-expert users. Advancement in providing common interfaces over such tools and services are gaining interest among researchers. However, the lack of (meta-) information about input-output data and parameter prevents to provide automated and standardized solutions, which can assist users in setting the appropriate parameters. These limitations must be resolved especially in the workflow-based solution in order to ease the integration of software. FINDINGS: We report a Taverna Workbench plugin: the XworX BIFI (Beautiful Interfaces for Inputs) implemented as a solution for the aforementioned issues. BIFI provides a Graphical User Interface (GUI) definition language used to layout the user interface and to define parameter options for Taverna workflows. BIFI is also able to submit GUI Definition Files (GDF) directly or discover appropriate instances from a configured repository. In the absence of a GDF, BIFI generates a default interface. CONCLUSION: The Taverna Workbench is an open source software providing the ability to combine various services within a workflow. Nevertheless, users can supply input data to the workflow via a simple user interface providing only a text area to enter the input in text form. The workflow may contain meta-information in human readable form such as description text for the port and an example value. However, not all workflow ports are documented so well or have all the required information.BIFI uses custom user interface components for ports which give users feedback on the parameter data type or structure to be used for service execution and enables client-side data validations. Moreover, BIFI offers user interfaces that allow users to interactively construct workflow views and share them with the community, thus significantly increasing usability of heterogeneous, distributed service consumption.

Monitoring of technical variation in quantitative high-throughput datasets.

High-dimensional datasets can be confounded by variation from technical sources, such as batches. Undetected batch effects can have severe consequences for the validity of a study's conclusion(s). We evaluate high-throughput RNAseq and miRNAseq as well as DNA methylation and gene expression microarray datasets, mainly from the Cancer Genome Atlas (TCGA) project, in respect to technical and biological annotations. We observe technical bias in these datasets and discuss corrective interventions. We then suggest a general procedure to control study design, detect technical bias using linear regression of principal components, correct for batch effects, and re-evaluate principal components. This procedure is implemented in the R package swamp, and as graphical user interface software. In conclusion, high-throughput platforms that generate continuous measurements are sensitive to various forms of technical bias. For such data, monitoring of technical variation is an important analysis step.

DNA methylation testing and marker validation using PCR: diagnostic applications.

DNA methylation provides a fundamental epigenetic mechanism to establish and promote cell-specific gene-expression patterns, which are inherited by subsequent cell generations. Thus, the epigenome determines the differentiation into a cell lineage but can also program cells to become abnormal or malignant. In humans, different germline and somatic diseases have been linked to faulty DNA methylation. In this article, we will discuss the available PCR-based technologies to assess differences in DNA methylation levels mainly affecting 5-methylcytosine in the CpG dinucleotide context in hereditary syndromal and somatic pathological conditions. We will discuss some of the current diagnostic applications and provide an outlook on how DNA methylation-based biomarkers might provide novel tools for diagnosis, prognosis or patient stratification for diseases such as cancer.