Menu

Asset Tag: bioinformatics

July 7, 2019

BreakSeek: a breakpoint-based algorithm for full spectral range INDEL detection.

Although recent developed algorithms have integrated multiple signals to improve sensitivity for insertion and deletion (INDEL) detection, they are far from being perfect and still have great limitations in detecting a full size range of INDELs. Here we present BreakSeek, a novel breakpoint-based algorithm, which can unbiasedly and efficiently detect both homozygous and heterozygous INDELs, ranging from several base pairs to over thousands of base pairs, with accurate breakpoint and heterozygosity rate estimations. Comprehensive evaluations on both simulated and real datasets revealed that BreakSeek outperformed other existing methods on both sensitivity and specificity in detecting both small and large INDELs, and uncovered a significant amount of novel INDELs that were missed before. In addition, by incorporating sophisticated statistic models, we for the first time investigated and demonstrated the importance of handling false and conflicting signals for multi-signal integrated methods.© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Read more
July 7, 2019

FinisherSC: a repeat-aware tool for upgrading de novo assembly using long reads.

We introduce FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance.The tool and data are available and will be maintained at http://kakitone.github.io/finishingTool/: dntse@stanford.eduSupplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Read more
July 7, 2019

Scalable multi whole-genome alignment using recursive exact matching

The emergence of third generation sequencing technologies has brought near perfect de-novo genome assembly within reach. This clears the way towards reference-free detection of genomic variations. In this paper, we introduce a novel concept for aligning whole-genomes which allows the alignment of multiple genomes. Alignments are constructed in a recursive manner, in which alignment decisions are statistically supported. Computational performance is achieved by splitting an initial indexing data structure into a multitude of smaller indices. We show that our method can be used to detect high resolution structural variations between two human genomes, and that it can be used to obtain a high quality multiple genome alignment of at least nineteen Mycobacterium tuberculosis genomes. An implementation of the outlined algorithm called REVEAL is available on: https://github.com/jasperlinthorst/REVEAL

Read more
July 7, 2019

GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments.

Genome assemblies generated with next-generation sequencing (NGS) reads usually contain a number of gaps. Several tools have recently been developed to close the gaps in these assemblies with NGS reads. Although these gap-closing tools efficiently close the gaps, they entail a high rate of misassembly at gap-closing sites.We have found that the assembly error rates caused by these tools are 20-500-fold higher than the rate of errors introduced into contigs by de novo assemblers. We here describe GMcloser, a tool that accurately closes these gaps with a preassembled contig set or a long read set (i.e. error-corrected PacBio reads). GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3-100-fold higher than those of other available tools, with similar efficiency.GMcloser and an accompanying tool (GMvalue) for evaluating the assembly and correcting misassemblies except SNPs and short indels in the assembly are available at https://sourceforge.net/projects/gmcloser/.shunichi.kosugi@riken.jpSupplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Read more
July 7, 2019

Hybrid de novo tandem repeat detection using short and long reads.

As one of the most studied genome rearrangements, tandem repeats have a considerable impact on genetic backgrounds of inherited diseases. Many methods designed for tandem repeat detection on reference sequences obtain high quality results. However, in the case of a de novo context, where no reference sequence is available, tandem repeat detection remains a difficult problem. The short reads obtained with the second-generation sequencing methods are not long enough to span regions that contain long repeats. This length limitation was tackled by the long reads obtained with the third-generation sequencing platforms such as Pacific Biosciences technologies. Nevertheless, the gain on the read length came with a significant increase of the error rate. The main objective of nowadays studies on long reads is to handle the high error rate up to 16%.In this paper we present MixTaR, the first de novo method for tandem repeat detection that combines the high-quality of short reads and the large length of long reads. Our hybrid algorithm uses the set of short reads for tandem repeat pattern detection based on a de Bruijn graph. These patterns are then validated using the long reads, and the tandem repeat sequences are constructed using local greedy assemblies.MixTaR is tested with both simulated and real reads from complex organisms. For a complete analysis of its robustness to errors, we use short and long reads with different error rates. The results are then analysed in terms of number of tandem repeats detected and the length of their patterns.Our method shows high precision and sensitivity. With low false positive rates even for highly erroneous reads, MixTaR is able to detect accurate tandem repeats with pattern lengths varying within a significant interval.

Read more
July 7, 2019

One Codex: A sensitive and accurate data platform for genomic microbial identification

High-throughput sequencing (HTS) is increasingly being used for broad applications of microbial characterization, such as microbial ecology, clinical diagnosis, and outbreak epidemiology. However, the analytical task of comparing short sequence reads against the known diversity of microbial life has proved to be computationally challenging. The One Codex data platform was created with the dual goals of analyzing microbial data against the largest possible collection of microbial reference genomes, as well as presenting those results in a format that is consumable by applied end-users. One Codex identifies microbial sequences using a “k-mer based” taxonomic classification algorithm through a web-based data platform, using a reference database that currently includes approximately 40,000 bacterial, viral, fungal, and protozoan genomes. In order to evaluate whether this classification method and associated database provided quantitatively different performance for microbial identification, we created a large and diverse evaluation dataset containing 50 million reads from 10,639 genomes, as well as sequences from six organisms novel species not be included in the reference databases of any of the tested classifiers. Quantitative evaluation of several published microbial detection methods shows that One Codex has the highest degree of sensitivity and specificity (AUC = 0.97, compared to 0.82-0.88 for other methods), both when detecting well-characterized species as well as newly sequenced, “taxonomically novel” organisms.

Read more
July 7, 2019

CHOgenome.org 2.0: Genome resources and website updates.

Chinese hamster ovary (CHO) cells are a major host cell line for the production of therapeutic proteins, and CHO cell and Chinese hamster (CH) genomes have recently been sequenced using next-generation sequencing methods. CHOgenome.org was launched in 2011 (version 1.0) to serve as a database repository and to provide bioinformatics tools for the CHO community. CHOgenome.org (version 1.0) maintained GenBank CHO-K1 genome data, identified CHO-omics literature, and provided a CHO-specific BLAST service. Recent major updates to CHOgenome.org (version 2.0) include new sequence and annotation databases for both CHO and CH genomes, a more user-friendly website, and new research tools, including a proteome browser and a genome viewer. CHO cell-line specific sequences and annotations facilitate cell line development opportunities, several of which are discussed. Moving forward, CHOgenome.org will host the increasing amount of CHO-omics data and continue to make useful bioinformatics tools available to the CHO community. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Read more
July 7, 2019

PAFFT: A new homology search algorithm for third-generation sequencers.

DNA sequencers that can conduct real-time sequencing from a single polymerase molecule are known as third-generation sequencers. Third-generation sequencers enable sequencing of reads that are several kilobases long. However, the raw data generated from third-generation sequencers are known to be error-prone. Because of sequencing errors, it is difficult to identify which genes are homologous to the reads obtained using third-generation sequencers. In this study, a new method for homology search algorithm, PAFFT, is developed. This method is the extension of the MAFFT algorithm which was used for multiple alignments. PAFFT detects global homology rather than local homology so that homologous regions can be detected even when the error rate of sequencing is high. PAFFT will boost application of third-generation sequencers. Copyright © 2015 Elsevier Inc. All rights reserved.

Read more
July 7, 2019

Jitterbug: somatic and germline transposon insertion detection at single-nucleotide resolution.

Transposable elements are major players in genome evolution. Transposon insertion polymorphisms can translate into phenotypic differences in plants and animals and are linked to different diseases including human cancer, making their characterization highly relevant to the study of genome evolution and genetic diseases. Here we present Jitterbug, a novel tool that identifies transposable element insertion sites at single-nucleotide resolution based on the pairedend mapping and clipped-read signatures produced by NGS alignments. Jitterbug can be easily integrated into existing NGS analysis pipelines, using the standard BAM format produced by frequently applied alignment tools (e.g. bwa, bowtie2), with no need to realign reads to a set of consensus transposon sequences. Jitterbug is highly sensitive and able to recall transposon insertions with a very high specificity, as demonstrated by benchmarks in the human and Arabidopsis genomes, and validation using long PacBio reads. In addition, Jitterbug estimates the zygosity of transposon insertions with high accuracy and can also identify somatic insertions. We demonstrate that Jitterbug can identify mosaic somatic transposon movement using sequenced tumor-normal sample pairs and allows for estimating the cancer cell fraction of clones containing a somatic TE insertion. We suggest that the independent methods we use to evaluate performance are a step towards creating a gold standard dataset for benchmarking structural variant prediction tools.

Read more
July 7, 2019

svviz: a read viewer for validating structural variants.

Visualizing read alignments is the most effective way to validate candidate structural variants (SVs) with existing data. We present svviz, a sequencing read visualizer for SVs that sorts and displays only reads relevant to a candidate SV. svviz works by searching input bam(s) for potentially relevant reads, realigning them against the inferred sequence of the putative variant allele as well as the reference allele and identifying reads that match one allele better than the other. Separate views of the two alleles are then displayed in a scrollable web browser view, enabling a more intuitive visualization of each allele, compared with the single reference genome-based view common to most current read browsers. The browser view facilitates examining the evidence for or against a putative variant, estimating zygosity, visualizing affected genomic annotations and manual refinement of breakpoints. svviz supports data from most modern sequencing platforms.svviz is implemented in python and freely available from http://svviz.github.io/. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

Read more
July 7, 2019

Contiguity: Contig adjacency graph construction and visualisation

Contiguity is interactive software for the visualization and manipulation of de novo genome assemblies. 14 Contiguity creates and displays information on contig adjacency which is contextualized by the 15 simultaneous display of a comparison between assembled contigs and reference sequence. Where 16 scaffolders allow unambiguous connections between contigs to be resolved into a single scaffold, 17 Contiguity allows the user to create all potential scaffolds in ambiguous regions of the genome. This 18 enables the resolution of novel sequence or structural variants from the assembly. In addition, 19 Contiguity provides a sequencing and assembly agnostic approach for the creation of contig adjacency 20 graphs. To maximize the number of contig adjacencies determined, Contiguity combines information 21 from read pair mappings, sequence overlap and De Bruijn graph exploration. We demonstrate how 22 highly sensitive graphs can be achieved using this method. Contig adjacency graphs allow the user to 23 visualize potential arrangements of contigs in unresolvable areas of the genome. By combining 24 adjacency information with comparative genomics, Contiguity provides an intuitive approach for 25 exploring and improving sequence assemblies. It is also useful in guiding manual closure of long read 26 sequence assemblies. Contiguity is an open source application, implemented using Python and the 27 Tkinter GUI package that can run on any Unix, OSX and Windows operating system. It has been 28 designed and optimized for bacterial assemblies. Contiguity is available at 29 http://mjsull.github.io/Contiguity .

Read more
July 7, 2019

Unique transposon landscapes are pervasive across Drosophila melanogaster genomes.

To understand how transposon landscapes (TLs) vary across animal genomes, we describe a new method called the Transposon Insertion and Depletion AnaLyzer (TIDAL) and a database of >300 TLs in Drosophila melanogaster (TIDAL-Fly). Our analysis reveals pervasive TL diversity across cell lines and fly strains, even for identically named sub-strains from different laboratories such as the ISO1 strain used for the reference genome sequence. On average, >500 novel insertions exist in every lab strain, inbred strains of the Drosophila Genetic Reference Panel (DGRP), and fly isolates in the Drosophila Genome Nexus (DGN). A minority (<25%) of transposon families comprise the majority (>70%) of TL diversity across fly strains. A sharp contrast between insertion and depletion patterns indicates that many transposons are unique to the ISO1 reference genome sequence. Although TL diversity from fly strains reaches asymptotic limits with increasing sequencing depth, rampant TL diversity causes unsaturated detection of TLs in pools of flies. Finally, we show novel transposon insertions negatively correlate with Piwi-interacting RNA (piRNA) levels for most transposon families, except for the highly-abundant roo retrotransposon. Our study provides a useful resource for Drosophila geneticists to understand how transposons create extensive genomic diversity in fly cell lines and strains.© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Read more
July 7, 2019

De novo assembly of Dekkera bruxellensis: a multi technology approach using short and long-read sequencing and optical mapping.

It remains a challenge to perform de novo assembly using next-generation sequencing (NGS). Despite the availability of multiple sequencing technologies and tools (e.g., assemblers) it is still difficult to assemble new genomes at chromosome resolution (i.e., one sequence per chromosome). Obtaining high quality draft assemblies is extremely important in the case of yeast genomes to better characterise major events in their evolutionary history. The aim of this work is two-fold: on the one hand we want to show how combining different and somewhat complementary technologies is key to improving assembly quality and correctness, and on the other hand we present a de novo assembly pipeline we believe to be beneficial to core facility bioinformaticians. To demonstrate both the effectiveness of combining technologies and the simplicity of the pipeline, here we present the results obtained using the Dekkera bruxellensis genome.In this work we used short-read Illumina data and long-read PacBio data combined with the extreme long-range information from OpGen optical maps in the task of de novo genome assembly and finishing. Moreover, we developed NouGAT, a semi-automated pipeline for read-preprocessing, de novo assembly and assembly evaluation, which was instrumental for this work.We obtained a high quality draft assembly of a yeast genome, resolved on a chromosomal level. Furthermore, this assembly was corrected for mis-assembly errors as demonstrated by resolving a large collapsed repeat and by receiving higher scores by assembly evaluation tools. With the inclusion of PacBio data we were able to fill about 5 % of the optical mapped genome not covered by the Illumina data.

Read more
July 7, 2019

Wham: Identifying structural variants of biological consequence.

Existing methods for identifying structural variants (SVs) from short read datasets are inaccurate. This complicates disease-gene identification and efforts to understand the consequences of genetic variation. In response, we have created Wham (Whole-genome Alignment Metrics) to provide a single, integrated framework for both structural variant calling and association testing, thereby bypassing many of the difficulties that currently frustrate attempts to employ SVs in association testing. Here we describe Wham, benchmark it against three other widely used SV identification tools-Lumpy, Delly and SoftSearch-and demonstrate Wham’s ability to identify and associate SVs with phenotypes using data from humans, domestic pigeons, and vaccinia virus. Wham and all associated software are covered under the MIT License and can be freely downloaded from github (https://github.com/zeeev/wham), with documentation on a wiki (http://zeeev.github.io/wham/). For community support please post questions to https://www.biostars.org/.

Read more
July 7, 2019

Evaluation and validation of assembling corrected PacBio long reads for microbial genome completion via hybrid approaches.

Despite the ever-increasing output of next-generation sequencing data along with developing assemblers, dozens to hundreds of gaps still exist in de novo microbial assemblies due to uneven coverage and large genomic repeats. Third-generation single-molecule, real-time (SMRT) sequencing technology avoids amplification artifacts and generates kilobase-long reads with the potential to complete microbial genome assembly. However, due to the low accuracy (~85%) of third-generation sequences, a considerable amount of long reads (>50X) are required for self-correction and for subsequent de novo assembly. Recently-developed hybrid approaches, using next-generation sequencing data and as few as 5X long reads, have been proposed to improve the completeness of microbial assembly. In this study we have evaluated the contemporary hybrid approaches and demonstrated that assembling corrected long reads (by runCA) produced the best assembly compared to long-read scaffolding (e.g., AHA, Cerulean and SSPACE-LongRead) and gap-filling (SPAdes). For generating corrected long reads, we further examined long-read correction tools, such as ECTools, LSC, LoRDEC, PBcR pipeline and proovread. We have demonstrated that three microbial genomes including Escherichia coli K12 MG1655, Meiothermus ruber DSM1279 and Pdeobacter heparinus DSM2366 were successfully hybrid assembled by runCA into near-perfect assemblies using ECTools-corrected long reads. In addition, we developed a tool, Patch, which implements corrected long reads and pre-assembled contigs as inputs, to enhance microbial genome assemblies. With the additional 20X long reads, short reads of S. cerevisiae W303 were hybrid assembled into 115 contigs using the verified strategy, ECTools + runCA. Patch was subsequently applied to upgrade the assembly to a 35-contig draft genome. Our evaluation of the hybrid approaches shows that assembling the ECTools-corrected long reads via runCA generates near complete microbial genomes, suggesting that genome assembly could benefit from re-analyzing the available hybrid datasets that were not assembled in an optimal fashion.

Read more

Subscribe for blog updates:

Talk with an expert

If you have a question, need to check the status of an order, or are interested in purchasing an instrument, we're here to help.