PipeCraft: Flexible open‐source toolkit for bioinformatics analysis of custom high‐throughput amplicon sequencing data

High‐throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user‐friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable.     

A beginners guide to SNP calling from high-throughput DNA-sequencing data

High-throughput DNA sequencing (HTS) is of increasing importance in the life sciences. One of its most prominent applications is the sequencing of whole genomes or targeted regions of the genome such as all exonic regions (i.e., the exome). Here, the objective is the identification of genetic variants such as single nucleotide polymorphisms (SNPs). The extraction of SNPs from the raw genetic sequences involves many processing steps and the application of a diverse set of tools. We review the essential building blocks for a pipeline that calls SNPs from raw HTS data. The pipeline includes quality control, mapping of short reads to the reference genome, visualization and post-processing of the alignment including base quality recalibration. The final steps of the pipeline include the SNP calling procedure along with filtering of SNP candidates. The steps of this pipeline are accompanied by an analysis of a publicly available whole-exome sequencing dataset. To this end, we employ several alignment programs and SNP calling routines for highlighting the fact that the choice of the tools significantly affects the final results.     

Trace2PS and FSA2PS: two software toolkits for converting trace and fsa files to PostScript format

Background  

Due to the advanced techniques in sequencing and fragment analysis, DNA sequencers and analyzers produce vast amounts of data within short time. To administrate the large data volume conveniently, efficient data management systems are used in order to process and to store sequencers' or analyzers' data outcome. The inclusion of graphical reports in such systems is necessary to achieve a comprehensive view of the integrated data. However, the resulting data of sequencing and fragment analysis runs are stored in a proprietary format, the so-called trace or fsa format, which is only readable by programs provided by the instrument's vendor operating on the machine itself or by commercial tools designed for editing the respective data. To allow for a quick conversion of the proprietary data format into a commonly used one, toolkits are required that reach this aim and can be easily integrated into workflow systems.     

ChromaPipe: a pipeline for analysis, quality control and management for a DNA sequencing facility

Optimizing and monitoring the data flow in high-throughput sequencing facilities is important for data input and output, for tracking the status of results for the users of the facility, and to guarantee a good, high-quality service. In a multi-user system environment with different throughputs, each user wants to access his/her data easily, track his/her sequencing history, analyze sequences and their quality, and apply some basic post-sequencing analysis, without the necessity of installing further software. Recently, Fiocruz established such a core facility as a "technological platform". Infrastructure includes a 48-capillary 3730 DNA Sequence Analyzer (Applied Biosystems) and supporting equipment. The service includes running samples for large-scale users, performing DNA sequencing reactions and runs for medium and small users, and participation in partial or full genome projects. We implemented a workflow that fulfills these requirements for small and high throughput users. Our implementation also includes the monitoring of data for continuous quality improvement (reports by plate, month and user) by the sequencing staff. For the user, different analyses of the chromatograms, such as visualization of good quality regions, as well as processing, such as comparisons or assemblies, are available. So far, 180 users have made use of the service, generating 155,000 sequences, 35% of which were produced for the BCG Moreau-RJ genome project. The pipeline (named ChromaPipe for Chromatogram Pipeline) is available for download by the scientific community at the url http://bioinfo.pdtis.fiocruz.br/ChromaPipe/. The support for assembly is also configured as a web service: http://bioinfo.pdtis.fiocruz.br/Assembly/.     

CoBRA: Containerized Bioinformatics Workflow for Reproducible ChIP/ATAC-seq Analysis

Chromatin immunoprecipitation sequencing (ChIP-seq) and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) have become essential technologies to effectively measure protein–DNA interactions and chromatin accessibility. However, there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples, correction of copy number variations, and integration of new downstream analysis tools. Here we present Containerized Bioinformatics workflow for Reproducible ChIP/ATAC-seq Analysis (CoBRA), a modularized computational workflow which quantifies ChIP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses. CoBRA provides a comprehensive state-of-the-art ChIP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience. This enables researchers to gain rapid insight into protein–DNA interactions and chromatin accessibility through sample clustering, differential peak calling, motif enrichment, comparison of sites to a reference database, and pathway analysis. CoBRA is publicly available online at https://bitbucket.org/cfce/cobra     

Analysing diversity and community structures using PCR‐RFLP: a new software application

Restriction fragment length polymorphism tools is an R application which supports a complete workflow of polymerase chain reaction‐restriction fragment length polymorphism (PCR‐RFLP), dealing with the problems which accompany analysis when PCR‐RFLP is used in diversity studies. Large numbers of different RFLP samples obtained from multiple electrophoresis runs might lead to limitations or misidentifications due to the need for band matching in most existing software applications. Due to the common problem of variation in the density of bands (i.e. distances between bands or visual intensity) in the electropherograms, it is desirable to have options for handling samples with uncertain or faint bands. As a further step in the workflow, scientists often use DNA sequencing to identify individual genotypes, so that the use of specific software to combine these tasks might be helpful. With this background, we here present an application that supports a complete workflow, starting with the analysis of single species samples by PCR‐RFLP, to PCR‐RFLP genotype identification based on a reference data set and DNA sequencing followed by similarity analysis. RFLPtools is a freely available, platform‐independent application which provides analysis functions for DNA fragment molecular weights (e.g. by RFLP analysis), including similarity calculations without the need for band matching. As it is written for the statistical software R, other statistical analyses might also be easily applied.     

Harnessing the MinION: An example of how to establish long‐read sequencing in a laboratory using challenging plant tissue from Eucalyptus pauciflora

Long‐read sequencing technologies are transforming our ability to assemble highly complex genomes. Realizing their full potential is critically reliant on extracting high‐quality, high‐molecular‐weight (HMW) DNA from the organisms of interest. This is especially the case for the portable MinION sequencer which enables all laboratories to undertake their own genome sequencing projects, due to its low entry cost and minimal spatial footprint. One challenge of the MinION is that each group has to independently establish effective protocols for using the instrument, which can be time‐consuming and costly. Here, we present a workflow and protocols that enabled us to establish MinION sequencing in our own laboratories, based on optimizing DNA extraction from a challenging plant tissue as a case study. Following the workflow illustrated, we were able to reliably and repeatedly obtain >6.5 Gb of long‐read sequencing data with a mean read length of 13 kb and an N50 of 26 kb. Our protocols are open source and can be performed in any laboratory without special equipment. We also illustrate some more elaborate workflows which can increase mean and average read lengths if this is desired. We envision that our workflow for establishing MinION sequencing, including the illustration of potential pitfalls and suggestions of how to adapt it to other tissue types, will be useful to others who plan to establish long‐read sequencing in their own laboratories.     

ddrage: A data set generator to evaluate ddRADseq analysis software

High‐throughput sequencing makes it possible to evaluate thousands of genetic markers across genomes and populations. Reduced‐representation sequencing approaches, like double‐digest restriction site‐associated DNA sequencing (ddRADseq), are frequently applied to screen for genetic variation. In particular in nonmodel organisms where whole‐genome sequencing is not yet feasible, ddRADseq has become popular as it allows genomewide assessment of variation patterns even in the absence of other genomic resources. However, while many tools are available for the analysis of ddRADseq data, few options exist to simulate ddRADseq data in order to evaluate the accuracy of downstream tools. The available tools either focus on the optimization of ddRAD experiment design or do not provide the information necessary for a detailed evaluation of different ddRAD analysis tools. For this task, a ground truth, that is, the underlying information of all effects in the data set, is required. Therefore, we here present ddrage , the ddRA D Data Set Ge nerator, that allows both developers and users to evaluate their ddRAD analysis software. ddrage allows the user to adjust many parameters such as coverage and rates of mutations, sequencing errors or allelic dropouts, in order to generate a realistic simulated ddRADseq data set for given experimental scenarios and organisms. The simulated reads can be easily processed with available analysis software such as stacks or pyrad and evaluated against the underlying parameters used to generate the data to gauge the impact of different parameter values used during downstream data processing.     

SIMPLEX: Cloud-Enabled Pipeline for the Comprehensive Analysis of Exome Sequencing Data

In recent studies, exome sequencing has proven to be a successful screening tool for the identification of candidate genes causing rare genetic diseases. Although underlying targeted sequencing methods are well established, necessary data handling and focused, structured analysis still remain demanding tasks. Here, we present a cloud-enabled autonomous analysis pipeline, which comprises the complete exome analysis workflow. The pipeline combines several in-house developed and published applications to perform the following steps: (a) initial quality control, (b) intelligent data filtering and pre-processing, (c) sequence alignment to a reference genome, (d) SNP and DIP detection, (e) functional annotation of variants using different approaches, and (f) detailed report generation during various stages of the workflow. The pipeline connects the selected analysis steps, exposes all available parameters for customized usage, performs required data handling, and distributes computationally expensive tasks either on a dedicated high-performance computing infrastructure or on the Amazon cloud environment (EC2). The presented application has already been used in several research projects including studies to elucidate the role of rare genetic diseases. The pipeline is continuously tested and is publicly available under the GPL as a VirtualBox or Cloud image at http://simplex.i-med.ac.at; additional supplementary data is provided at http://www.icbi.at/exome.     

NARWHAL, a primary analysis pipeline for NGS data

The NARWHAL software pipeline has been developed to automate the primary analysis of Illumina sequencing data. This pipeline combines a new and flexible de-multiplexing tool with open-source aligners and automated quality assessment. The entire pipeline can be run using only one simple sample-sheet for diverse sequencing applications. NARWHAL creates a sample-oriented data structure and outperforms existing tools in speed. AVAILABILITY: https://trac.nbic.nl/narwhal/.     

Workflow for analysis of high mass accuracy salivary data set using MaxQuant and ProteinPilot search algorithm

LTQ Orbitrap data analyzed with ProteinPilot can be further improved by MaxQuant raw data processing, which utilizes precursor-level high mass accuracy data for peak processing and MGF creation. In particular, ProteinPilot results from MaxQuant-processed peaklists for Orbitrap data sets resulted in improved spectral utilization due to an improved peaklist quality with higher precision and high precursor mass accuracy (HPMA). The output and postsearch analysis tools of both workflows were utilized for previously unexplored features of a three-dimensional fractionated and hexapeptide library (ProteoMiner) treated whole saliva data set comprising 200 fractions. ProteinPilot's ability to simultaneously predict multiple modifications showed an advantage from ProteoMiner treatment for modified peptide identification. We demonstrate that complementary approaches in the analysis pipeline provide comprehensive results for the whole saliva data set acquired on an LTQ Orbitrap. Overall our results establish a workflow for improved protein identification from high mass accuracy data.     

Quantitative DNA methylation analysis based on four-dye trace data from direct sequencing of PCR amplificates

MOTIVATION: Methylation of cytosines in DNA plays an important role in the regulation of gene expression, and the analysis of methylation patterns is fundamental for the understanding of cell differentiation, aging processes, diseases and cancer development. Such analysis has been limited, because technologies for detailed and efficient high-throughput studies have not been available. We have developed a novel quantitative methylation analysis algorithm and workflow based on direct DNA sequencing of PCR products from bisulfite-treated DNA with high-throughput sequencing machines. This technology is a prerequisite for success of the Human Epigenome Project, the first large genome-wide sequencing study for DNA methylation in many different tissues. Methylation in tissue samples which are compositions of different cells is a quantitative information represented by cytosine/thymine proportions after bisulfite conversion of unmethylated cytosines to uracil and PCR. Calculation of quantitative methylation information from base proportions represented by different dye signals in four-dye sequencing trace files needs a specific algorithm handling imbalanced and overscaled signals, incomplete conversion, quality problems and basecaller artifacts. RESULTS: The algorithm we developed has several key properties: it analyzes trace files from PCR products of bisulfite-treated DNA sequenced directly on ABI machines; it yields quantitative methylation measurements for individual cytosine positions after alignment with genomic reference sequences, signal normalization and estimation of effectiveness of bisulfite treatment; it works in a fully automated pipeline including data quality monitoring; it is efficient and avoids the usual cost of multiple sequencing runs on subclones to estimate DNA methylation. The power of our new algorithm is demonstrated with data from two test systems based on mixtures with known base compositions and defined methylation. In addition, the applicability is proven by identifying CpGs that are differentially methylated in real tissue samples.     

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific molecular profiles of a tumor may predict responsiveness to therapeutic agents or provide knowledge about prognosis. At our institution a tumor genotyping program was established as part of routine clinical care, screening both hematologic and solid tumors for a wide spectrum of mutations using two next-generation sequencing (NGS) panels: a custom, 33 gene hematological malignancies panel for use with peripheral blood and bone marrow, and a commercially produced solid tumor panel for use with formalin-fixed paraffin-embedded tissue that targets 47 genes commonly mutated in cancer. Our workflow includes a pathologist review of the biopsy to ensure there is adequate amount of tumor for the assay followed by customized DNA extraction is performed on the specimen. Quality control of the specimen includes steps for quantity, quality and integrity and only after the extracted DNA passes these metrics an amplicon library is generated and sequenced. The resulting data is analyzed through an in-house bioinformatics pipeline and the variants are reviewed and interpreted for pathogenicity. Here we provide a snapshot of the utility of each panel using two clinical cases to provide insight into how a well-designed NGS workflow can contribute to optimizing clinical outcomes.