FastqCLS: a FASTQ Compressor for Long-read Sequencing via read reordering using a novel scoring model

Sequencing Analysis ◽

Sequencing Data ◽

File Size ◽

Scoring Model ◽

The Past ◽

Long Read ◽

Benchmark Datasets ◽

Processing Steps

Abstract Motivation Over the past decades, vast amounts of genome sequencing data have been produced, requiring an enormous level of storage capacity. The time and resources needed to store and transfer such data cause bottlenecks in genome sequencing analysis. To resolve this issue, various compression techniques have been proposed to reduce the size of original FASTQ raw sequencing data, but these remain suboptimal. Long-read sequencing has become dominant in genomics, whereas most existing compression methods focus on short-read sequencing only. Results We designed a compression algorithm based on read reordering using a novel scoring model for reducing FASTQ file size with no information loss. We integrated all data processing steps into a software package called FastqCLS and provided it as a Docker image for ease of installation and execution to help users easily install and run. We compared our method with existing major FASTQ compression tools using benchmark datasets. We also included new long-read sequencing data in this validation. As a result, FastqCLS outperformed in terms of compression ratios for storing long-read sequencing data. Availability and implementation FastqCLS can be downloaded from https://github.com/krlucete/FastqCLS Supplementary information Supplementary data are available at Bioinformatics online.

Using single-cell cytometry to illustrate integrated multi-perspective evaluation of clustering algorithms using Pareto fronts

Bioinformatics ◽

10.1093/bioinformatics/btab038 ◽

2021 ◽

Author(s):

Givanna H Putri ◽

Irena Koprinska ◽

Thomas M Ashhurst ◽

Nicholas J C King ◽

Mark N Read

Keyword(s):

Single Cell ◽

Performance Metrics ◽

Clustering Algorithms ◽

Latin Hypercube Sampling ◽

Sequencing Data ◽

Evaluation Protocol ◽

Benchmark Datasets ◽

Pareto Fronts ◽

Parameter Values

Abstract Motivation Many ‘automated gating’ algorithms now exist to cluster cytometry and single-cell sequencing data into discrete populations. Comparative algorithm evaluations on benchmark datasets rely either on a single performance metric, or a few metrics considered independently of one another. However, single metrics emphasize different aspects of clustering performance and do not rank clustering solutions in the same order. This underlies the lack of consensus between comparative studies regarding optimal clustering algorithms and undermines the translatability of results onto other non-benchmark datasets. Results We propose the Pareto fronts framework as an integrative evaluation protocol, wherein individual metrics are instead leveraged as complementary perspectives. Judged superior are algorithms that provide the best trade-off between the multiple metrics considered simultaneously. This yields a more comprehensive and complete view of clustering performance. Moreover, by broadly and systematically sampling algorithm parameter values using the Latin Hypercube sampling method, our evaluation protocol minimizes (un)fortunate parameter value selections as confounding factors. Furthermore, it reveals how meticulously each algorithm must be tuned in order to obtain good results, vital knowledge for users with novel data. We exemplify the protocol by conducting a comparative study between three clustering algorithms (ChronoClust, FlowSOM and Phenograph) using four common performance metrics applied across four cytometry benchmark datasets. To our knowledge, this is the first time Pareto fronts have been used to evaluate the performance of clustering algorithms in any application domain. Availability and implementation Implementation of our Pareto front methodology and all scripts and datasets to reproduce this article are available at https://github.com/ghar1821/ParetoBench. Supplementary information Supplementary data are available at Bioinformatics online.

Constructing a Reference Genome in a Single Lab: The Possibility to Use Oxford Nanopore Technology

Plants ◽

10.3390/plants8080270 ◽

2019 ◽

Vol 8 (8) ◽

pp. 270 ◽

Cited By ~ 4

Author(s):

Yun Gyeong Lee ◽

Sang Chul Choi ◽

Yuna Kang ◽

Kyeong Min Kim ◽

Chon-Sik Kang ◽

...

Keyword(s):

Plant Species ◽

Genome Sequencing ◽

Reference Genome ◽

Genome Structure ◽

Plant Genome ◽

Sequence Information ◽

Sequencing Analysis ◽

Oxford Nanopore ◽

A Genome ◽

The whole genome sequencing (WGS) has become a crucial tool in understanding genome structure and genetic variation. The MinION sequencing of Oxford Nanopore Technologies (ONT) is an excellent approach for performing WGS and it has advantages in comparison with other Next-Generation Sequencing (NGS): It is relatively inexpensive, portable, has simple library preparation, can be monitored in real-time, and has no theoretical limits on reading length. Sorghum bicolor (L.) Moench is diploid (2n = 2x = 20) with a genome size of about 730 Mb, and its genome sequence information is released in the Phytozome database. Therefore, sorghum can be used as a good reference. However, plant species have complex and large genomes when compared to animals or microorganisms. As a result, complete genome sequencing is difficult for plant species. MinION sequencing that produces long-reads can be an excellent tool for overcoming the weak assembly of short-reads generated from NGS by minimizing the generation of gaps or covering the repetitive sequence that appears on the plant genome. Here, we conducted the genome sequencing for S. bicolor cv. BTx623 while using the MinION platform and obtained 895,678 reads and 17.9 gigabytes (Gb) (ca. 25× coverage of reference) from long-read sequence data. A total of 6124 contigs (covering 45.9%) were generated from Canu, and a total of 2661 contigs (covering 50%) were generated from Minimap and Miniasm with a Racon through a de novo assembly using two different tools and mapped assembled contigs against the sorghum reference genome. Our results provide an optimal series of long-read sequencing analysis for plant species while using the MinION platform and a clue to determine the total sequencing scale for optimal coverage that is based on various genome sizes.

Cas9-Assisted Targeting of CHromosome segments (CATCH) for targeted nanopore sequencing and optical genome mapping

10.1101/110163 ◽

2017 ◽

Cited By ~ 5

Author(s):

Tslil Gabrieli ◽

Hila Sharim ◽

Yael Michaeli ◽

Yuval Ebenstein

Keyword(s):

Single Molecule ◽

Genome Mapping ◽

Single Point ◽

Read Length ◽

Whole Genome ◽

Sequencing Analysis ◽

Nanopore Sequencing ◽

Sequencing Data ◽

Whole Genome Analysis ◽

ABSTRACTVariations in the genetic code, from single point mutations to large structural or copy number alterations, influence susceptibility, onset, and progression of genetic diseases and tumor transformation. Next-generation sequencing analysis is unable to reliably capture aberrations larger than the typical sequencing read length of several hundred bases. Long-read, single-molecule sequencing methods such as SMRT and nanopore sequencing can address larger variations, but require costly whole genome analysis. Here we describe a method for isolation and enrichment of a large genomic region of interest for targeted analysis based on Cas9 excision of two sites flanking the target region and isolation of the excised DNA segment by pulsed field gel electrophoresis. The isolated target remains intact and is ideally suited for optical genome mapping and long-read sequencing at high coverage. In addition, analysis is performed directly on native genomic DNA that retains genetic and epigenetic composition without amplification bias. This method enables detection of mutations and structural variants as well as detailed analysis by generation of hybrid scaffolds composed of optical maps and sequencing data at a fraction of the cost of whole genome sequencing.

RNA sequencing data: hitchhiker's guide to expression analysis

10.7287/peerj.preprints.27283 ◽

2018 ◽

Author(s):

Koen Van Den Berge ◽

Katharina Hembach ◽

Charlotte Soneson ◽

Simone Tiberi ◽

Lieven Clement ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Large Scale ◽

Science Studies ◽

Rna Seq ◽

Sequencing Data ◽

Data Types ◽

The Past ◽

Long Read ◽

Statistical Approaches

Gene expression is the fundamental level at which the result of various genetic and regulatory programs are observable. The measurement of transcriptome-wide gene expression has convincingly switched from microarrays to sequencing in a matter of years. RNA sequencing (RNA-seq) provides a quantitative and open system for profiling transcriptional outcomes on a large scale and therefore facilitates a large diversity of applications, including basic science studies, but also agricultural or clinical situations. In the past 10 years or so, much has been learned about the characteristics of the RNA-seq datasets as well as the performance of the myriad of methods developed. In this review, we give an overall view of the developments in RNA-seq data analysis, including experimental design, with an explicit focus on quantification of gene expression and statistical approaches for differential expression. We also highlight emerging data types, such as single-cell RNA-seq and gene expression profiling using long-read technologies.

Whole-genome sequencing analysis of clozapine-induced myocarditis

10.1101/2021.07.26.21261157 ◽

2021 ◽

Author(s):

Ankita Narang ◽

Paul Lacaze ◽

Kathlyn Ronaldson ◽

John McNeil ◽

Mahesh Jayaram ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Genome Wide Association Study ◽

Copy Number Variants ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Analysis ◽

Sequencing Data ◽

Dna Variation ◽

Rare Genetic Variants

One of the concerns limiting the use of clozapine in schizophrenia treatment is the risk of rare but potentially fatal myocarditis. Our previous genome-wide association study and human leucocyte antigen analyses identified putative loci associated with clozapine-induced myocarditis. However, the contribution of DNA variation in cytochrome P450 genes, copy number variants and rare deleterious variants have not been investigated. We explored these unexplored classes of DNA variation using whole-genome sequencing data from 25 cases with clozapine-induced myocarditis and 25 demographically-matched clozapine-tolerant control subjects. We identified 15 genes based on rare variant gene-burden analysis (MLLT6, CADPS, TACC2, L3MBTL4, NPY, SLC25A21, PARVB, GPR179, ACAD9, NOL8, C5orf33, FAM127A, AFDN, SLC6A11, PXDN) nominally associated (p<0.05) with clozapine-induced myocarditis. Of these genes, 13 were expressed in human myocardial tissue. Although independent replication of these findings is required, our study provides preliminary insights into the potential role of rare genetic variants in susceptibility to clozapine-induced myocarditis.

Noise-cancelling repeat finder: uncovering tandem repeats in error-prone long-read sequencing data

Bioinformatics ◽

10.1093/bioinformatics/btz484 ◽

2019 ◽

Vol 35 (22) ◽

pp. 4809-4811 ◽

Cited By ~ 8

Author(s):

Robert S Harris ◽

Monika Cechova ◽

Kateryna D Makova

Keyword(s):

Tandem Repeats ◽

Error Rates ◽

Superior Performance ◽

Whole Genome Sequencing Data ◽

Dna Repeats ◽

Sequencing Data ◽

Heat Shock Stress ◽

Noise Cancelling ◽

Abstract Summary Tandem DNA repeats can be sequenced with long-read technologies, but cannot be accurately deciphered due to the lack of computational tools taking high error rates of these technologies into account. Here we introduce Noise-Cancelling Repeat Finder (NCRF) to uncover putative tandem repeats of specified motifs in noisy long reads produced by Pacific Biosciences and Oxford Nanopore sequencers. Using simulations, we validated the use of NCRF to locate tandem repeats with motifs of various lengths and demonstrated its superior performance as compared to two alternative tools. Using real human whole-genome sequencing data, NCRF identified long arrays of the (AATGG)n repeat involved in heat shock stress response. Availability and implementation NCRF is implemented in C, supported by several python scripts, and is available in bioconda and at https://github.com/makovalab-psu/NoiseCancellingRepeatFinder. Supplementary information Supplementary data are available at Bioinformatics online.

Translating Genomics to the Clinic: Implications of Cancer Heterogeneity

Clinical Chemistry ◽

10.1373/clinchem.2012.184580 ◽

2013 ◽

Vol 59 (1) ◽

pp. 127-137 ◽

Cited By ~ 13

Author(s):

Nardin Samuel ◽

Thomas J Hudson

Keyword(s):

Genome Sequencing ◽

Large Scale ◽

Clinical Decision Making ◽

Cancer Genomics ◽

Clinical Decision ◽

Sequencing Analysis ◽

Breast Cancers ◽

Sequencing Data ◽

Cancer Heterogeneity ◽

Cancer Genomes

BACKGROUND Sequencing of cancer genomes has become a pivotal method for uncovering and understanding the deregulated cellular processes driving tumor initiation and progression. Whole-genome sequencing is evolving toward becoming less costly and more feasible on a large scale; consequently, thousands of tumors are being analyzed with these technologies. Interpreting these data in the context of tumor complexity poses a challenge for cancer genomics. CONTENT The sequencing of large numbers of tumors has revealed novel insights into oncogenic mechanisms. In particular, we highlight the remarkable insight into the pathogenesis of breast cancers that has been gained through comprehensive and integrated sequencing analysis. The analysis and interpretation of sequencing data, however, must be considered in the context of heterogeneity within and among tumor samples. Only by adequately accounting for the underlying complexity of cancer genomes will the potential of genome sequencing be understood and subsequently translated into improved management of patients. SUMMARY The paradigm of personalized medicine holds promise if patient tumors are thoroughly studied as unique and heterogeneous entities and clinical decisions are made accordingly. Associated challenges will be ameliorated by continued collaborative efforts among research centers that coordinate the sharing of mutation, intervention, and outcomes data to assist in the interpretation of genomic data and to support clinical decision-making.

Phenotypic and genotypic features of the Mycobacterium tuberculosis lineage 1 subgroup in central Vietnam

Scientific Reports ◽

10.1038/s41598-021-92984-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Nguyen Thi Le Hang ◽

Minako Hijikata ◽

Shinji Maeda ◽

Akiko Miyabayashi ◽

Keiko Wakabayashi ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Pulmonary Tuberculosis ◽

Genome Sequencing ◽

Whole Genome ◽

Sequencing Data ◽

Distinctive Features ◽

Sequencing Platform ◽

Central Vietnam ◽

Smear Positive Pulmonary Tuberculosis ◽

AbstractMycobacterium tuberculosis (Mtb) has different features depending on different geographic areas. We collected Mtb strains from patients with smear-positive pulmonary tuberculosis in Da Nang, central Vietnam. Using a whole genome sequencing platform, including genome assembly complemented by long-read-sequencing data, genomic characteristics were studied. Of 181 Mtb isolates, predominant Vietnamese EAI4_VNM and EAI4-like spoligotypes (31.5%), ZERO strains (5.0%), and part of EAI5 (11.1%) were included in a lineage-1 (L1) sublineage, i.e., L1.1.1.1. These strains were found less often in younger people, and they genetically clustered less frequently than other modern strains. Patients infected with ZERO strains demonstrated less lung infiltration. A region in RD2bcg spanning six loci, i.e., PE_PGRS35, cfp21, Rv1985c, Rv1986, Rv1987, and erm(37), was deleted in EAI4_VNM, EAI4-like, and ZERO strains, whereas another 118 bp deletion in furA was specific only to ZERO strains. L1.1.1.1-sublineage-specific deletions in PE_PGRS4 and PE_PGRS22 were also identified. RD900, seen in ancestral lineages, was present in majority of the L1 members. All strains without IS6110 (5.0%) had the ZERO spoligo-pattern. Distinctive features of the ancestral L1 strains provide a basis for investigation of the modern versus ancestral Mtb lineages and allow consideration of countermeasures against this heterogeneous pathogen.

Accurate Haplotype-Resolved Assembly Reveals The Origin Of Structural Variants For Human Trios

Bioinformatics ◽

10.1093/bioinformatics/btab068 ◽

2021 ◽

Author(s):

Mengyang Xu ◽

Lidong Guo ◽

Xiao Du ◽

Lei Li ◽

Brock A Peters ◽

...

Keyword(s):

De Novo ◽

Substantial Improvement ◽

Sequencing Data ◽

Homologous Chromosomes ◽

Assembly Method ◽

Long Reads ◽

Long Read ◽

Second Generation Sequencing ◽

Generation Sequencing

Abstract Motivation Achieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging. Results To address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to co-barcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling co-barcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read based assembly method (TrioCanu) but with a significantly higher single-base accuracy (up to 99.99997% (Q65)). This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies. Availability The code of the analysis is available at https://github.com/BGI-Qingdao/HAST. Supplementary information Supplementary data are available at Bioinformatics online.