A graphical, interactive and GPU-enabled workflow to process long-read sequencing data

Abstract Background Long-read sequencing has great promise in enabling portable, rapid molecular-assisted cancer diagnoses. A key challenge in democratizing long-read sequencing technology in the biomedical and clinical community is the lack of graphical bioinformatics software tools which can efficiently process the raw nanopore reads, support graphical output and interactive visualizations for interpretations of results. Another obstacle is that high performance software tools for long-read sequencing data analyses often leverage graphics processing units (GPU), which is challenging and time-consuming to configure, especially on the cloud. Results We present a graphical cloud-enabled workflow for fast, interactive analysis of nanopore sequencing data using GPUs. Users customize parameters, monitor execution and visualize results through an accessible graphical interface. The workflow and its components are completely containerized to ensure reproducibility and facilitate installation of the GPU-enabled software. We also provide an Amazon Machine Image (AMI) with all software and drivers pre-installed for GPU computing on the cloud. Most importantly, we demonstrate the potential of applying our software tools to reduce the turnaround time of cancer diagnostics by generating blood cancer (NB4, K562, ME1, 238 MV4;11) cell line Nanopore data using the Flongle adapter. We observe a 29x speedup and a 93x reduction in costs for the rate-limiting basecalling step in the analysis of blood cancer cell line data. Conclusions Our interactive and efficient software tools will make analyses of Nanopore data using GPU and cloud computing accessible to biomedical and clinical scientists, thus facilitating the adoption of cost effective, fast, portable and real-time long-read sequencing.

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Comparison of long-read sequencing technologies in interrogating bacteria and fly genomes

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab083 ◽

2021 ◽

Author(s):

Eric S Tvedte ◽

Mark Gasser ◽

Benjamin C Sparklin ◽

Jane Michalski ◽

Carl E Hjelmen ◽

...

Keyword(s):

Bacterial Genome ◽

Hybrid Approach ◽

Cost Effective ◽

Fruit Fly ◽

Drosophila Ananassae ◽

Whole Genome Sequencing Data ◽

Sequencing Data ◽

E Coli ◽

Hybrid Approaches ◽

Long Read

Abstract The newest generation of DNA sequencing technology is highlighted by the ability to generate sequence reads hundreds of kilobases in length. Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. We used whole-genome sequencing data produced by three PacBio protocols (Sequel II CLR, Sequel II HiFi, RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. In both organisms tested, Sequel II assemblies had the highest consensus accuracy, even after accounting for differences in sequencing throughput. ONT and PacBio CLR had the longest reads sequenced compared to PacBio RS II and HiFi, and genome contiguity was highest when assembling these datasets. ONT Rapid Sequencing libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assembly or polishing eukaryotic genome assemblies, and an ONT-Illumina hybrid approach would be more cost-effective for many users. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. The ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

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Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies

PeerJ ◽

10.7717/peerj.1839 ◽

2016 ◽

Vol 4 ◽

pp. e1839 ◽

Cited By ~ 57

Author(s):

Tom O. Delmont ◽

A. Murat Eren

Keyword(s):

High Throughput Sequencing ◽

Draft Genome ◽

Cost Effective ◽

Single Copy ◽

Eukaryotic Genome ◽

Sequencing Data ◽

Bacterial Genomes ◽

Long Read ◽

Domains Of Life ◽

Genome Assemblies

High-throughput sequencing provides a fast and cost-effective mean to recover genomes of organisms from all domains of life. However, adequate curation of the assembly results against potential contamination of non-target organisms requires advanced bioinformatics approaches and practices. Here, we re-analyzed the sequencing data generated for the tardigradeHypsibius dujardini,and created a holistic display of the eukaryotic genome assembly using DNA data originating from two groups and eleven sequencing libraries. By using bacterial single-copy genes, k-mer frequencies, and coverage values of scaffolds we could identify and characterize multiple near-complete bacterial genomes from the raw assembly, and curate a 182 Mbp draft genome forH. dujardinisupported by RNA-Seq data. Our results indicate that most contaminant scaffolds were assembled from Moleculo long-read libraries, and most of these contaminants have differed between library preparations. Our re-analysis shows that visualization and curation of eukaryotic genome assemblies can benefit from tools designed to address the needs of today’s microbiologists, who are constantly challenged by the difficulties associated with the identification of distinct microbial genomes in complex environmental metagenomes.

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Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies

10.7287/peerj.preprints.1695 ◽

2016 ◽

Author(s):

Tom O Delmont ◽

A. Murat Eren

Keyword(s):

High Throughput Sequencing ◽

Draft Genome ◽

Cost Effective ◽

Single Copy ◽

Eukaryotic Genome ◽

Metagenomic Data ◽

Sequencing Data ◽

Long Read ◽

Domains Of Life ◽

Genome Assemblies

High-throughput sequencing provides a fast and cost effective mean to recover genomes of organisms from all domains of life. However, adequate curation of the assembly results against potential contamination of non-target organisms requires advanced bioinformatics approaches and practices. Here, we re-analyzed the sequencing data generated for the tardigrade Hypsibius dujardini using approaches routinely employed by microbial ecologists who reconstruct bacterial and archaeal genomes from metagenomic data. We created a holistic display of the eukaryotic genome assembly using DNA data originating from two groups and eleven sequencing libraries. By using bacterial single-copy genes, k-mer frequencies, and coverage values of scaffolds we could identify and characterize multiple near-complete bacterial genomes, and curate a 182 Mbp draft genome for H. dujardini supported by RNA-Seq data. Our results indicate that most contaminant scaffolds were assembled from Moleculo long-read libraries, and most of these contaminants have differed between library preparations. Our re-analysis shows that visualization and curation of eukaryotic genome assemblies can benefit from tools designed to address the needs of today’s microbiologists, who are constantly challenged by the difficulties associated with the identification of distinct microbial genomes in complex environmental metagenomes.

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isoformant: A visual toolkit for reference-free long-read isoform analysis at single-read resolution

10.1101/2021.12.17.457386 ◽

2021 ◽

Author(s):

Daniel D Le ◽

Faye T Orcales ◽

William Stephenson

Keyword(s):

Region Of Interest ◽

Sequencing Data ◽

Consensus Sequences ◽

Interactive Analysis ◽

Isoform Diversity ◽

Oxford Nanopore ◽

Long Read ◽

Multiple Samples ◽

Read Distribution

isoformant is an analytical toolkit for isoform characterization of Oxford Nanopore Technologies (ONT) long-transcript sequencing data (i.e. direct RNA and cDNA). Deployment of these tools using Jupyter Notebook enables interactive analysis of user- defined region-of-interest (ROI), typically a gene. The core module of isoformant clus- ters sequencing reads by k-mer density to generate isoform consensus sequences without the requirement for a reference genome or prior annotations. The inclusion of differential isoform usage hypothesis testing based on read distribution among clusters enables com- parison across multiple samples. Here, as proof-of-principle, we demonstrate the utility of isoformant for analyzing isoform diversity of commercially-available isoform standard mixtures. isoformant is available here: https://github.com/danledinh/isoformant.

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Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies

10.7287/peerj.preprints.1695v1 ◽

2016 ◽

Cited By ~ 1

Author(s):

Tom O Delmont ◽

A. Murat Eren

Keyword(s):

High Throughput Sequencing ◽

Draft Genome ◽

Cost Effective ◽

Single Copy ◽

Eukaryotic Genome ◽

Metagenomic Data ◽

Sequencing Data ◽

Long Read ◽

Domains Of Life ◽

Genome Assemblies

High-throughput sequencing provides a fast and cost effective mean to recover genomes of organisms from all domains of life. However, adequate curation of the assembly results against potential contamination of non-target organisms requires advanced bioinformatics approaches and practices. Here, we re-analyzed the sequencing data generated for the tardigrade Hypsibius dujardini using approaches routinely employed by microbial ecologists who reconstruct bacterial and archaeal genomes from metagenomic data. We created a holistic display of the eukaryotic genome assembly using DNA data originating from two groups and eleven sequencing libraries. By using bacterial single-copy genes, k-mer frequencies, and coverage values of scaffolds we could identify and characterize multiple near-complete bacterial genomes, and curate a 182 Mbp draft genome for H. dujardini supported by RNA-Seq data. Our results indicate that most contaminant scaffolds were assembled from Moleculo long-read libraries, and most of these contaminants have differed between library preparations. Our re-analysis shows that visualization and curation of eukaryotic genome assemblies can benefit from tools designed to address the needs of today’s microbiologists, who are constantly challenged by the difficulties associated with the identification of distinct microbial genomes in complex environmental metagenomes.

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Comparison of long-read methods for sequencing and assembly of a plant genome

GigaScience ◽

10.1093/gigascience/giaa146 ◽

2020 ◽

Vol 9 (12) ◽

Author(s):

Valentine Murigneux ◽

Subash Kumar Rai ◽

Agnelo Furtado ◽

Timothy J C Bruxner ◽

Wei Tian ◽

...

Keyword(s):

De Novo ◽

Cost Effective ◽

Genome Project ◽

Plant Genome ◽

Sequencing Data ◽

Pacific Biosciences ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Long Read ◽

The Cost

Abstract Background Sequencing technologies have advanced to the point where it is possible to generate high-accuracy, haplotype-resolved, chromosome-scale assemblies. Several long-read sequencing technologies are available, and a growing number of algorithms have been developed to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology, as well as the most appropriate software for assembly and polishing. It is thus important to benchmark different approaches applied to the same sample. Results Here, we report a comparison of 3 long-read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION), and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of Pacific Biosciences and Nanopore reads. Results obtained from combining long-read technologies or short-read and long-read technologies are also presented. The assemblies were compared for contiguity, base accuracy, and completeness, as well as sequencing costs and DNA material requirements. Conclusions The 3 long-read technologies produced highly contiguous and complete genome assemblies of M. jansenii. At the time of sequencing, the cost associated with each method was significantly different, but continuous improvements in technologies have resulted in greater accuracy, increased throughput, and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies.

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Reference-free reconstruction and quantification of transcriptomes from Nanopore long-read sequencing

10.1101/2020.02.08.939942 ◽

2020 ◽

Author(s):

Ivan de la Rubia ◽

Joel A. Indi ◽

Silvia Carbonell-Sala ◽

Julien Lagarde ◽

M Mar Albà ◽

...

Keyword(s):

Single Molecule ◽

Reference Genome ◽

Simulated Data ◽

Cost Effective ◽

Dna Assembly ◽

Sequencing Data ◽

Consensus Sequences ◽

Sequencing Technologies ◽

Long Reads ◽

Long Read

AbstractSingle-molecule long-read sequencing with Nanopore provides an unprecedented opportunity to measure transcriptomes from any sample1–3. However, current analysis methods rely on the comparison with a reference genome or transcriptome2,4,5, or the use of multiple sequencing technologies6,7, thereby precluding cost-effective studies in species with no genome assembly available, in individuals underrepresented in the existing reference, and for the discovery of disease-specific transcripts not directly identifiable from a reference genome. Methods for DNA assembly8–10 cannot be directly transferred to transcriptomes since their consensus sequences lack the required interpretability for genes with multiple transcript isoforms. To address these challenges, we have developed RATTLE, the first tool to perform reference-free reconstruction and quantification of transcripts from Nanopore long reads. Using simulated data, isoform spike-ins, and sequencing data from tissues and cell lines, we demonstrate that RATTLE accurately determines transcript sequence and abundance, is comparable to reference-based methods, and shows saturation in the number of predicted transcripts with increasing number of input reads.

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Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis

10.1101/2020.01.07.897512 ◽

2020 ◽

Cited By ~ 3

Author(s):

Kristoffer Sahlin ◽

Botond Sipos ◽

Phillip L James ◽

Paul Medvedev

Keyword(s):

Error Correction ◽

Transcriptome Analysis ◽

Transcription Initiation ◽

Cost Effective ◽

Error Rates ◽

Computational Method ◽

Bias Error ◽

Sequencing Data ◽

Oxford Nanopore ◽

Long Read

AbstractOxford Nanopore (ONT) is a leading long-read technology which has been revolutionizing transcriptome analysis through its capacity to sequence the majority of transcripts from end-to-end. This has greatly increased our ability to study the diversity of transcription mechanisms such as transcription initiation, termination, and alternative splicing. However, ONT still suffers from high error rates which have thus far limited its scope to reference-based analyses. When a reference is not available or is not a viable option due to reference-bias, error correction is a crucial step towards the reconstruction of the sequenced transcripts and downstream sequence analysis of transcripts. In this paper, we present a novel computational method to error correct ONT cDNA sequencing data, called isONcorrect. IsONcorrect is able to jointly use all isoforms from a gene during error correction, thereby allowing it to correct reads at low sequencing depths. We are able to obtain a median accuracy of 98.9-99.6%, demonstrating the feasibility of applying cost-effective cDNA full transcript length sequencing for reference-free transcriptome analysis.

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Interactive analysis of Long-read RNA isoforms with Iso-Seq Browser

10.1101/102905 ◽

2017 ◽

Cited By ~ 5

Author(s):

Jingyuan Hu ◽

Prech Uapinyoying ◽

Jeremy Goecks

Keyword(s):

Rna Sequencing ◽

Visual Analytics ◽

Visual Analysis ◽

Sequencing Data ◽

Web Based ◽

Interactive Analysis ◽

Pacific Biosciences ◽

Long Read ◽

Gene Transcripts ◽

Gene Isoforms

AbstractBackgroundLong-read RNA sequencing, such as Pacific Biosciences’ Iso-Seq method, enables generation of sequencing reads that are 10 kilobases or even longer. These reads are ideal for discovering splice junctions and resolving full-length gene transcripts without time-consuming and error-prone techniques such as transcript assembly and junction inference.ResultsIso-Seq Browser is a Web-based visual analytics tool for long-read RNA sequencing data produced by Pacific Biosciences’ isoform sequencing (Iso-Seq) techniques. Key features of the Iso-Seq Browser are: 1) an exon-only web-based interface with zooming and exon highlighting for exploring reference gene transcripts and novel gene isoforms, 2) automated grouping of transcripts and isoforms by similarity, 3) many customization features for data exploration and creating publication ready figures, and 4) exporting selected isoforms into fasta files for further analysis. Iso-Seq Browser is written in Python using several scientific libraries. The application and analyses described in this paper are freely available to both academic and commercial users at https://github.com/goeckslab/isoseq-browserConclusionsIso-Seq Browser enables interactive genome-wide visual analysis of long RNA sequence reads. Through visualization, highlighting, clustering, and filtering of gene isoforms, ISB makes it simple to identify novel isoforms and novel isoform features such as exons, introns and untranslated regions.

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