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.     

Comparing High‐throughput Platforms for Sequencing the V4 Region of SSU‐rDNA in Environmental Microbial Eukaryotic Diversity Surveys

High‐throughput sequencing platforms are continuing to increase resulting read lengths, which is allowing for a deeper and more accurate depiction of environmental microbial diversity. With the nascent Reagent Kit v3, Illumina MiSeq now has the ability to sequence the eukaryotic hyper‐variable V4 region of the SSU‐rDNA locus with paired‐end reads. Using DNA collected from soils with analyses of strictly‐ and nearly identical amplicons, here we ask how the new Illumina MiSeq data compares with what we can obtain with Roche/454 GS FLX with regard to quantity and quality, presence and absence, and abundance perspectives. We show that there is an easy qualitative transition from the Roche/454 to the Illumina MiSeq platforms. The ease of this transition is more nuanced quantitatively for low‐abundant amplicons, although estimates of abundances are known to also vary within platforms.     

BIGpre: a quality assessment package for next-generation sequencing data

The emergence of next-generation sequencing (NGS) technologies has significantly improved sequencing throughput and reduced costs. However, the short read length, duplicate reads and massive volume of data make the data processing much more difficult and complicated than the first-generation sequencing technology. Although there are some software packages developed to assess the data quality, those packages either are not easily available to users or require bioinformatics skills and computer resources. Moreover, almost all the quality assessment software currently available didn’t taken into account the sequencing errors when dealing with the duplicate assessment in NGS data. Here, we present a new user-friendly quality assessment software package called BIGpre, which works for both Illumina and 454 platforms. BIGpre contains all the functions of other quality assessment software, such as the correlation between forward and reverse reads, read GC-content distribution, and base Ns quality. More importantly, BIGpre incorporates associated programs to detect and remove duplicate reads after taking sequencing errors into account and trimming low quality reads from raw data as well. BIGpre is primarily written in Perl and integrates graphical capability from the statistics package R. This package produces both tabular and graphical summaries of data quality for sequencing datasets from Illumina and 454 platforms. Processing hundreds of millions reads within minutes, this package provides immediate diagnostic information for user to manipulate sequencing data for downstream analyses. BIGpre is freely available at http://bigpre.sourceforge.net/.     

NGS QC Toolkit: a toolkit for quality control of next generation sequencing data

Next generation sequencing (NGS) technologies provide a high-throughput means to generate large amount of sequence data. However, quality control (QC) of sequence data generated from these technologies is extremely important for meaningful downstream analysis. Further, highly efficient and fast processing tools are required to handle the large volume of datasets. Here, we have developed an application, NGS QC Toolkit, for quality check and filtering of high-quality data. This toolkit is a standalone and open source application freely available at http://www.nipgr.res.in/ngsqctoolkit.html. All the tools in the application have been implemented in Perl programming language. The toolkit is comprised of user-friendly tools for QC of sequencing data generated using Roche 454 and Illumina platforms, and additional tools to aid QC (sequence format converter and trimming tools) and analysis (statistics tools). A variety of options have been provided to facilitate the QC at user-defined parameters. The toolkit is expected to be very useful for the QC of NGS data to facilitate better downstream analysis.     

Pollux: platform independent error correction of single and mixed genomes

Background

Second-generation sequencers generate millions of relatively short, but error-prone, reads. These errors make sequence assembly and other downstream projects more challenging. Correcting these errors improves the quality of assemblies and projects which benefit from error-free reads.

Results

We have developed a general-purpose error corrector that corrects errors introduced by Illumina, Ion Torrent, and Roche 454 sequencing technologies and can be applied to single- or mixed-genome data. In addition to correcting substitution errors, we locate and correct insertion, deletion, and homopolymer errors while remaining sensitive to low coverage areas of sequencing projects. Using published data sets, we correct 94% of Illumina MiSeq errors, 88% of Ion Torrent PGM errors, 85% of Roche 454 GS Junior errors. Introduced errors are 20 to 70 times more rare than successfully corrected errors. Furthermore, we show that the quality of assemblies improves when reads are corrected by our software.

Conclusions

Pollux is highly effective at correcting errors across platforms, and is consistently able to perform as well or better than currently available error correction software. Pollux provides general-purpose error correction and may be used in applications with or without assembly.     

Read length versus Depth of Coverage for Viral Quasispecies Reconstruction

Recent advancements of sequencing technology have opened up unprecedented opportunities in many application areas. Virus samples can now be sequenced efficiently with very deep coverage to infer the genetic diversity of the underlying virus populations. Several sequencing platforms with different underlying technologies and performance characteristics are available for viral diversity studies. Here, we investigate how the differences between two common platforms provided by 454/Roche and Illumina affect viral diversity estimation and the reconstruction of viral haplotypes. Using a mixture of ten HIV clones sequenced with both platforms and additional simulation experiments, we assessed the trade-off between sequencing coverage, read length, and error rate. For fixed costs, short Illumina reads can be generated at higher coverage and allow for detecting variants at lower frequencies. They can also be sufficient to assess the diversity of the sample if sequences are dissimilar enough, but, in general, assembly of full-length haplotypes is feasible only with the longer 454/Roche reads. The quantitative comparison highlights the advantages and disadvantages of both platforms and provides guidance for the design of viral diversity studies.     

高通量测序技术及其在微生物学研究中的应用

20世纪70年代发明的核酸测序技术为基因组学及其相关学科的发展做出了巨大贡献,本世纪初发展的以Illumina公司的HiSeq 2000,ABI公司的SOLID,和Roche公司的454技术为代表的高通量测序技术又为基因组学的发展注入了新活力.本文在阐述这些技术的基础上,着重讨论了新一代测序技术在微生物领域中的应用.     

Read count approach for DNA copy number variants detection

MOTIVATION: The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data. RESULTS: Here we face the many aspects that cover the detection of CNVs by using read count approach. We first study the characteristics and systematic biases of read count distributions, focusing on the normalization methods designed for removing these biases. Subsequently, we compare the algorithms designed to detect the boundaries of CNVs and we investigate the ability of read count data to predict the exact number of DNA copy. Finally, we review the tools publicly available for analysing read count data. To better understand the state of the art of read count approaches, we compare the performance of the three most widely used sequencing technologies (Illumina Genome Analyzer, Roche 454 and Life Technologies SOLiD) in all the analyses that we perform.     

Base-calling for next-generation sequencing platforms

Next-generation sequencing platforms are dramatically reducing the cost of DNA sequencing. With these technologies, bases are inferred from light intensity signals, a process commonly referred to as base-calling. Thus, understanding and improving the quality of sequence data generated using these approaches are of high interest. Recently, a number of papers have characterized the biases associated with base-calling and proposed methodological improvements. In this review, we summarize recent development of base-calling approaches for the Illumina and Roche 454 sequencing platforms.     

SRAdb: query and use public next-generation sequencing data from within R

Background

The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Illumina (Genome Analyzer, HiSeq, MiSeq, .etc), Roche 454 GS System, Applied Biosystems SOLiD System, Helicos Heliscope, PacBio RS, and others.

Results

SRAdb is an attempt to make queries of the metadata associated with SRA submission, study, sample, experiment and run more robust and precise, and make access to sequencing data in the SRA easier. We have parsed all the SRA metadata into a SQLite database that is routinely updated and can be easily distributed. The SRAdb R/Bioconductor package then utilizes this SQLite database for querying and accessing metadata. Full text search functionality makes querying metadata very flexible and powerful. Fastq files associated with query results can be downloaded easily for local analysis. The package also includes an interface from R to a popular genome browser, the Integrated Genomics Viewer.

Conclusions

SRAdb Bioconductor package provides a convenient and integrated framework to query and access SRA metadata quickly and powerfully from within R.     

Viral population analysis and minority-variant detection using short read next-generation sequencing

RNA viruses within infected individuals exist as a population of evolutionary-related variants. Owing to evolutionary change affecting the constitution of this population, the frequency and/or occurrence of individual viral variants can show marked or subtle fluctuations. Since the development of massively parallel sequencing platforms, such viral populations can now be investigated to unprecedented resolution. A critical problem with such analyses is the presence of sequencing-related errors that obscure the identification of true biological variants present at low frequency. Here, we report the development and assessment of the Quality Assessment of Short Read (QUASR) Pipeline (http://sourceforge.net/projects/quasr) specific for virus genome short read analysis that minimizes sequencing errors from multiple deep-sequencing platforms, and enables post-mapping analysis of the minority variants within the viral population. QUASR significantly reduces the error-related noise in deep-sequencing datasets, resulting in increased mapping accuracy and reduction of erroneous mutations. Using QUASR, we have determined influenza virus genome dynamics in sequential samples from an in vitro evolution of 2009 pandemic H1N1 (A/H1N1/09) influenza from samples sequenced on both the Roche 454 GSFLX and Illumina GAIIx platforms. Importantly, concordance between the 454 and Illumina sequencing allowed unambiguous minority-variant detection and accurate determination of virus population turnover in vitro.     

Solution-based targeted genomic enrichment for precious DNA samples

ABSTRACT: BACKGROUND: Solution-based targeted genomic enrichment (TGE) protocols permit selective sequencing of genomic regions of interest on a massively parallel scale. These protocols could be improved by: 1) modifying or eliminating time consuming steps; 2) increasing yield to reduce input DNA and excessive PCR cycling; and 3) enhancing reproducible. RESULTS: We developed a solution-based TGE method for downstream Illumina sequencing in a non-automated workflow, adding standard Illumina barcode indexes during the post-hybridization amplification to allow for sample pooling prior to sequencing. The method utilizes Agilent SureSelect baits, primers and hybridization reagents for the capture, off-the-shelf reagents for the library preparation steps, and adaptor oligonucleotides for Illumina paired-end sequencing purchased directly from an oligonucleotide manufacturing company. CONCLUSIONS: This solution-based TGE method for Illumina sequencing is optimized for small- or medium-sized laboratories and addresses the weaknesses of standard protocols by reducing the amount of input DNA required, increasing capture yield, optimizing efficiency, and improving reproducibility.     

A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE

We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as "noise" or "error") within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.     

Performance comparison of benchtop high-throughput sequencing platforms

Three benchtop high-throughput sequencing instruments are now available. The 454 GS Junior (Roche), MiSeq (Illumina) and Ion Torrent PGM (Life Technologies) are laser-printer sized and offer modest set-up and running costs. Each instrument can generate data required for a draft bacterial genome sequence in days, making them attractive for identifying and characterizing pathogens in the clinical setting. We compared the performance of these instruments by sequencing an isolate of Escherichia coli O104:H4, which caused an outbreak of food poisoning in Germany in 2011. The MiSeq had the highest throughput per run (1.6 Gb/run, 60 Mb/h) and lowest error rates. The 454 GS Junior generated the longest reads (up to 600 bases) and most contiguous assemblies but had the lowest throughput (70 Mb/run, 9 Mb/h). Run in 100-bp mode, the Ion Torrent PGM had the highest throughput (80–100 Mb/h). Unlike the MiSeq, the Ion Torrent PGM and 454 GS Junior both produced homopolymer-associated indel errors (1.5 and 0.38 errors per 100 bases, respectively).     

The genome of Yoka poxvirus

Yoka poxvirus was isolated almost four decades ago from a mosquito pool in the Central African Republic. Its classification as a poxvirus is based solely upon the morphology of virions visualized by electron microscopy. Here we describe sequencing of the Yoka poxvirus genome using a combination of Roche/454 and Illumina next-generation sequencing technologies. A single consensus contig of ～175 kb in length that encodes 186 predicted genes was generated. Multiple methods were used to show that Yoka poxvirus is most closely related to viruses in the Orthopoxvirus genus, but it is clearly distinct from previously described poxviruses. Collectively, the phylogenetic and genomic sequence analyses suggest that Yoka poxvirus is the prototype member of a new genus in the family Poxviridae.