scholarly journals dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Gokhan Yavas ◽  
Huixiao Hong ◽  
Wenming Xiao
Keyword(s):  
Quality Assessment ◽  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Quality Score ◽  
De Novo Genome Assembly ◽  
Genome Assemblies ◽  
Reference Genomes ◽  
Better Than

Abstract Background Accurate de novo genome assembly has become reality with the advancements in sequencing technology. With the ever-increasing number of de novo genome assembly tools, assessing the quality of assemblies has become of great importance in genome research. Although many quality metrics have been proposed and software tools for calculating those metrics have been developed, the existing tools do not produce a unified measure to reflect the overall quality of an assembly. Results To address this issue, we developed the de novo Assembly Quality Evaluation Tool (dnAQET) that generates a unified metric for benchmarking the quality assessment of assemblies. Our framework first calculates individual quality scores for the scaffolds/contigs of an assembly by aligning them to a reference genome. Next, it computes a quality score for the assembly using its overall reference genome coverage, the quality score distribution of its scaffolds and the redundancy identified in it. Using synthetic assemblies randomly generated from the latest human genome build, various builds of the reference genomes for five organisms and six de novo assemblies for sample NA24385, we tested dnAQET to assess its capability for benchmarking quality evaluation of genome assemblies. For synthetic data, our quality score increased with decreasing number of misassemblies and redundancy and increasing average contig length and coverage, as expected. For genome builds, dnAQET quality score calculated for a more recent reference genome was better than the score for an older version. To compare with some of the most frequently used measures, 13 other quality measures were calculated. The quality score from dnAQET was found to be better than all other measures in terms of consistency with the known quality of the reference genomes, indicating that dnAQET is reliable for benchmarking quality assessment of de novo genome assemblies. Conclusions The dnAQET is a scalable framework designed to evaluate a de novo genome assembly based on the aggregated quality of its scaffolds (or contigs). Our results demonstrated that dnAQET quality score is reliable for benchmarking quality assessment of genome assemblies. The dnQAET can help researchers to identify the most suitable assembly tools and to select high quality assemblies generated.

scholarly journals EvalDNA: a machine learning-based tool for the comprehensive evaluation of mammalian genome assembly quality

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Madolyn L. MacDonald ◽  
Kelvin H. Lee
Keyword(s):  
Machine Learning ◽  
Quality Assessment ◽  
Genome Assembly ◽  
Reference Genome ◽  
Chinese Hamster ◽  
Mammalian Genome ◽  
Quality Score ◽  
Assessment Tools ◽  
Supervised Machine Learning ◽  
Genome Assemblies

Abstract Background To select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses supervised machine learning for the quality scoring of genome assemblies and does not require an existing reference genome for accuracy assessment. Results EvalDNA calculates a list of quality metrics from an assembled sequence and applies a model created from supervised machine learning methods to integrate various metrics into a comprehensive quality score. A well-tested, accurate model for scoring mammalian genome sequences is provided as part of EvalDNA. This random forest regression model evaluates an assembled sequence based on continuity, completeness, and accuracy, and was able to explain 86% of the variation in reference-based quality scores within the testing data. EvalDNA was applied to human chromosome 14 assemblies from the GAGE study to rank genome assemblers and to compare EvalDNA to two other quality evaluation tools. In addition, EvalDNA was used to evaluate several genome assemblies of the Chinese hamster genome to help establish a better reference genome for the biopharmaceutical manufacturing community. EvalDNA was also used to assess more recent human assemblies from the QUAST-LG study completed in 2018, and its ability to score bacterial genomes was examined through application on bacterial assemblies from the GAGE-B study. Conclusions EvalDNA enables scientists to easily identify the best available genome assembly for their organism of interest without requiring a reference assembly. EvalDNA sets itself apart from other quality assessment tools by producing a quality score that enables direct comparison among assemblies from different species.

scholarly journals A high-quality genome assembly from a single, field-collected spotted lanternfly (Lycorma delicatula) using the PacBio Sequel II system

GigaScience ◽  
2019 ◽  
Vol 8 (10) ◽  
Author(s):  
Sarah B Kingan ◽  
Julie Urban ◽  
Christine C Lambert ◽  
Primo Baybayan ◽  
Anna K Childers ◽  
...  
Keyword(s):  
Invasive Species ◽  
Genome Assembly ◽  
De Novo ◽  
Fragment Size ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Lycorma Delicatula ◽  
Long Read ◽  
Genome Assemblies ◽  
High Quality Genome

ABSTRACT Background A high-quality reference genome is an essential tool for applied and basic research on arthropods. Long-read sequencing technologies may be used to generate more complete and contiguous genome assemblies than alternate technologies; however, long-read methods have historically had greater input DNA requirements and higher costs than next-generation sequencing, which are barriers to their use on many samples. Here, we present a 2.3 Gb de novo genome assembly of a field-collected adult female spotted lanternfly (Lycorma delicatula) using a single Pacific Biosciences SMRT Cell. The spotted lanternfly is an invasive species recently discovered in the northeastern United States that threatens to damage economically important crop plants in the region. Results The DNA from 1 individual was used to make 1 standard, size-selected library with an average DNA fragment size of ∼20 kb. The library was run on 1 Sequel II SMRT Cell 8M, generating a total of 132 Gb of long-read sequences, of which 82 Gb were from unique library molecules, representing ∼36× coverage of the genome. The assembly had high contiguity (contig N50 length = 1.5 Mb), completeness, and sequence level accuracy as estimated by conserved gene set analysis (96.8% of conserved genes both complete and without frame shift errors). Furthermore, it was possible to segregate more than half of the diploid genome into the 2 separate haplotypes. The assembly also recovered 2 microbial symbiont genomes known to be associated with L. delicatula, each microbial genome being assembled into a single contig. Conclusions We demonstrate that field-collected arthropods can be used for the rapid generation of high-quality genome assemblies, an attractive approach for projects on emerging invasive species, disease vectors, or conservation efforts of endangered species.

scholarly journals Metassembler: Merging and optimizing de novo genome assemblies

2015 ◽  
Author(s):  
Alejandro Hernandez Wences ◽  
Michael Schatz
Keyword(s):  
Open Source ◽  
Genome Assembly ◽  
De Novo ◽  
A Genome ◽  
Genome Assemblies ◽  
Multiple Algorithms

Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence. We apply it to the four genomes from the Assemblathon competitions and show it consistently and substantially improves the contiguity and quality of each assembly. We also develop guidelines for metassembly by systematically evaluating 120 permutations of merging the top 5 assemblies of the first Assemblathon competition. The software is open-source at http://metassembler.sourceforge.net.

scholarly journals LongStitch: High-quality genome assembly correction and scaffolding using long reads

2021 ◽  
Author(s):  
Lauren Coombe ◽  
Janet X Li ◽  
Theodora Lo ◽  
Johnathan Wong ◽  
Vladimir Nikolic ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Draft Genome ◽  
Model Organisms ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Long Reads ◽  
Long Read ◽  
Genomic Regions ◽  
Genome Assemblies

Background Generating high-quality de novo genome assemblies is foundational to the genomics study of model and non-model organisms. In recent years, long-read sequencing has greatly benefited genome assembly and scaffolding, a process by which assembled sequences are ordered and oriented through the use of long-range information. Long reads are better able to span repetitive genomic regions compared to short reads, and thus have tremendous utility for resolving problematic regions and helping generate more complete draft assemblies. Here, we present LongStitch, a scalable pipeline that corrects and scaffolds draft genome assemblies exclusively using long reads. Results LongStitch incorporates multiple tools developed by our group and runs in up to three stages, which includes initial assembly correction (Tigmint-long), followed by two incremental scaffolding stages (ntLink and ARKS-long). Tigmint-long and ARKS-long are misassembly correction and scaffolding utilities, respectively, previously developed for linked reads, that we adapted for long reads. Here, we describe the LongStitch pipeline and introduce our new long-read scaffolder, ntLink, which utilizes lightweight minimizer mappings to join contigs. LongStitch was tested on short and long-read assemblies of three different human individuals using corresponding nanopore long-read data, and improves the contiguity of each assembly from 2.0-fold up to 304.6-fold (as measured by NGA50 length). Furthermore, LongStitch generates more contiguous and correct assemblies compared to state-of-the-art long-read scaffolder LRScaf in most tests, and consistently runs in under five hours using less than 23GB of RAM. Conclusions Due to its effectiveness and efficiency in improving draft assemblies using long reads, we expect LongStitch to benefit a wide variety of de novo genome assembly projects. The LongStitch pipeline is freely available at https://github.com/bcgsc/longstitch.

scholarly journals Pushing the limits of de novo genome assembly for complex prokaryotic genomes harboring very long, near identical repeats

2018 ◽  
Author(s):  
Michael Schmid ◽  
Daniel Frei ◽  
Andrea Patrignani ◽  
Ralph Schlapbach ◽  
Jürg E. Frey ◽  
...  
Keyword(s):  
Dark Matter ◽  
Genome Assembly ◽  
De Novo ◽  
Bacterial Genomes ◽  
De Novo Genome Assembly ◽  
Assembly Algorithm ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Prokaryotic Genomes ◽  
Genome Assemblies

AbstractGenerating a complete, de novo genome assembly for prokaryotes is often considered a solved problem. However, we here show that Pseudomonas koreensis P19E3 harbors multiple, near identical repeat pairs up to 70 kilobase pairs in length. Beyond long repeats, the P19E3 assembly was further complicated by a shufflon region. Its complex genome could not be de novo assembled with long reads produced by Pacific Biosciences’ technology, but required very long reads from the Oxford Nanopore Technology. Another important factor for a full genomic resolution was the choice of assembly algorithm.Importantly, a repeat analysis indicated that very complex bacterial genomes represent a general phenomenon beyond Pseudomonas. Roughly 10% of 9331 complete bacterial and a handful of 293 complete archaeal genomes represented this dark matter for de novo genome assembly of prokaryotes. Several of these dark matter genome assemblies contained repeats far beyond the resolution of the sequencing technology employed and likely contain errors, other genomes were closed employing labor-intense steps like cosmid libraries, primer walking or optical mapping. Using very long sequencing reads in combination with assemblers capable of resolving long, near identical repeats will bring most prokaryotic genomes within reach of fast and complete de novo genome assembly.

scholarly journals Parameter exploration improves the accuracy of long-read genome assembly

2021 ◽  
Author(s):  
Anurag Priyam ◽  
Alicja Witwicka ◽  
Anindita Brahma ◽  
Eckart Stolle ◽  
Yannick Wurm
Keyword(s):  
Genome Assembly ◽  
Reference Genome ◽  
Error Rates ◽  
Fine Tuning ◽  
Sequencing Error ◽  
High Quality ◽  
Long Read ◽  
Genome Assemblies ◽  
Error Profiles

Long-molecule sequencing is now routinely applied to generate high-quality reference genome assemblies. However, datasets differ in repeat composition, heterozygosity, read lengths and error profiles. The assembly parameters that provide the best results could thus differ across datasets. By integrating four complementary and biologically meaningful metrics, we show that simple fine-tuning of assembly parameters can substantially improve the quality of long-read genome assemblies. In particular, modifying estimates of sequencing error rates improves some metrics more than two-fold. We provide a flexible software, CompareGenomeQualities, that automates comparisons of assembly qualities for researchers wanting a straightforward mechanism for choosing among multiple assemblies.

scholarly journals The Bellerophon pipeline, improving de novo transcriptomes and removing chimeras

2018 ◽  
Author(s):  
Jesse Kerkvliet ◽  
Arthur de Fouchier ◽  
Michiel van Wijk ◽  
Astrid T. Groot
Keyword(s):  
Quality Control ◽  
Quality Assessment ◽  
Reference Genome ◽  
Assessment Tool ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Rna Seq ◽  
Quality Assessment Tool ◽  
Chimeric Sequences

AbstractTranscriptome quality control is an important step in RNA-seq experiments. However, the quality of de novo assembled transcriptomes is difficult to assess, due to the lack of reference genome to compare the assembly to. We developed a method to assess and improve the quality of de novo assembled transcriptomes by focusing on the removal of chimeric sequences. These chimeric sequences can be the result of faulty assembled contigs, merging two transcripts into one. The developed method is incorporated into a pipeline, that we named Bellerophon, which is broadly applicable and easy to use. Bellerophon first uses the quality-assessment tool TransRate to indicate the quality, after which it uses a Transcripts Per Million (TPM) filter to remove lowly expressed contigs and CD-HIT-EST to remove highly identical contigs. To validate the quality of this method, we performed three benchmark experiments: 1) a computational creation of chimeras, 2) identification of chimeric contigs in a transcriptome assembly, 3) a simulated RNAseq experiment using a known reference transcriptome. Overall, the Bellerophon pipeline was able to remove between 40 to 91.9% of the chimeras in transcriptome assemblies and removed more chimeric than non-chimeric contigs. Thus, the Bellerophon sequence of filtration steps is a broadly applicable solution to improve transcriptome assemblies.

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