A New Binning Method for Metagenomics by One-Dimensional Cellular Automata

More and more developed and inexpensive next-generation sequencing (NGS) technologies allow us to extract vast sequence data from a sample containing multiple species. Characterizing the taxonomic diversity for the planet-size data plays an important role in the metagenomic studies, while a crucial step for doing the study is thebinningprocess to group sequence reads from similar species or taxonomic classes. The metagenomic binning remains a challenge work because of not only the various read noises but also the tremendous data volume. In this work, we propose an unsupervised binning method for NGS reads based on the one-dimensional cellular automaton (1D-CA). Our binning method facilities to reduce the memory usage because 1D-CA costs only linear space. Experiments on synthetic dataset exhibit that our method is helpful to identify species of lower abundance compared to the proposed tool.

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Pharmacogenomics in Children: Advantages and Challenges of Next Generation Sequencing Applications

International Journal of Pediatrics ◽

10.1155/2013/136524 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

O. M. Vanakker ◽

A. De Paepe

Keyword(s):

Next Generation Sequencing ◽

Sequence Data ◽

Next Generation ◽

Clinical Implementation ◽

Ethical Aspects ◽

Number Of Genes ◽

Working Groups ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing ◽

Single Reaction

Pharmacogenetics is considered as a prime example of how personalized medicine nowadays can be put into practice. However, genotyping to guide pharmacological treatment is relatively uncommon in the routine clinical practice. Several reasons can be found why the application of pharmacogenetics is less than initially anticipated, which include the contradictory results obtained for certain variants and the lack of guidelines for clinical implementation. However, more reproducible results are being generated, and efforts have been made to establish working groups focussing on evidence-based clinical guidelines. For another pharmacogenetic hurdle, the speed by which a pharmacogenetic profile for a certain drug can be obtained in an individual patient, there has been a revolution in molecular genetics through the introduction of next generation sequencing (NGS), making it possible to sequence a large number of genes up to the complete genome in a single reaction. Besides the enthusiasm due to the tremendous increase of our sequencing capacities, several considerations need to be made regarding quality and interpretation of the sequence data as well as ethical aspects of this technology. This paper will focus on the different NGS applications that may be useful for pharmacogenomics in children and the challenges that they bring on.

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Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing

Biology ◽

10.3390/biology9090295 ◽

2020 ◽

Vol 9 (9) ◽

pp. 295

Author(s):

Girum Fitihamlak Ejigu ◽

Jaehee Jung

Keyword(s):

Next Generation Sequencing ◽

Genome Annotation ◽

Sequence Data ◽

Genetic Disorders ◽

Next Generation ◽

Functional Annotations ◽

General Aspects ◽

Tools And Techniques ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Next-Generation Sequencing (NGS) has made it easier to obtain genome-wide sequence data and it has shifted the research focus into genome annotation. The challenging tasks involved in annotation rely on the currently available tools and techniques to decode the information contained in nucleotide sequences. This information will improve our understanding of general aspects of life and evolution and improve our ability to diagnose genetic disorders. Here, we present a summary of both structural and functional annotations, as well as the associated comparative annotation tools and pipelines. We highlight visualization tools that immensely aid the annotation process and the contributions of the scientific community to the annotation. Further, we discuss quality-control practices and the need for re-annotation, and highlight the future of annotation.

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An archaeogenetic approach to identify the remains of the Hungarian Kings. Working Plan

Ephemeris Hungarologica ◽

10.53644/eh.2021.2.333 ◽

2021 ◽

Vol 1 (2) ◽

pp. 333-342

Author(s):

Gergely I. B. Varga ◽

Kitti Maár ◽

Alexandra Ginguta ◽

Bence Kovács ◽

Balázs Tihanyi ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genetic Analysis ◽

Genetic Information ◽

Sequence Data ◽

Rapid Development ◽

Personal Identification ◽

Library Preparation ◽

Working Plan ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

The Royal Basilica of Székesfehérvár was the burial place of fifteen Hungarian kings. Unfortunately, the anthropological findings excavated at the site of the Basilica were mixed up during the tumultuous centuries of Hungary, hence the royal remains still lie unidentified in a charnel-house. The appearance and rapid development of archaeogenetics now allows the personal identification of the royal skeletons from among the remains of the Basilica. The genetic information necessary for the identification of the Árpád dynasty members is accessible, while sequence data of the non-Árpádian kings’ relatives still need to be obtained by further genetic analysis. Here we provide an outline of the investigation for the identity of the royal skeletons: we sketch the process of sample preparation and DNA extraction, the steps of library preparation for next-generation sequencing (NGS) and give a brief report of the current progressions.

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SNP Mining in Functional Genes from Nonmodel Species by Next-Generation Sequencing: A Case of Flowering, Pre-Harvest Sprouting, and Dehydration Resistant Genes in Wheat

BioMed Research International ◽

10.1155/2016/3524908 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10

Author(s):

Zhong-Xu Chen ◽

Mei Deng ◽

Ji-Rui Wang

Keyword(s):

Next Generation Sequencing ◽

Sequence Data ◽

Low Cost ◽

Functional Genes ◽

Accurate Information ◽

Next Generation ◽

Polynomial Fitting ◽

Next Generation Sequencing Ngs ◽

Ngs Data ◽

Generation Sequencing

As plenty of nonmodel plants are without genomic sequences, the combination of molecular technologies and the next generation sequencing (NGS) platform has led to a new approach to study the genetic variations of these plants. Software GATK, SOAPsnp, samtools, and others are often used to deal with the NGS data. In this study, BLAST was applied to call SNPs from 16 mixed functional gene’s sequence data of polyploidy wheat. In total 1.2 million reads were obtained with the average of 7500 reads per genes. To get accurate information, 390,992 pair reads were successfully assembled before aligning to those functional genes. Standalone BLAST tools were used to map assembled sequence to functional genes, respectively. Polynomial fitting was applied to find the suitable minor allele frequency (MAF) threshold at 6% for assembled reads of each functional gene. SNPs accuracy form assembled reads, pretrimmed reads, and original reads were compared, which declared that SNPs mined from the assembled reads were more reliable than others. It was also demonstrated that mixed samples’ NGS sequences and then analysis by BLAST were an effective, low-cost, and accurate way to mine SNPs for nonmodel species. Assembled reads and polynomial fitting threshold were recommended for more accurate SNPs target.

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NGS Screening for Identification of Novel Pexophagy-Related Mutation in Arabidopsis thaliana

Proceedings ◽

10.3390/iecge-07155 ◽

2020 ◽

Vol 76 (1) ◽

pp. 7

Author(s):

Katarzyna Sieńko ◽

Kacper Żukowski ◽

Kenji Yamada ◽

Shino Goto-Yamada

Keyword(s):

Arabidopsis Thaliana ◽

Sequence Data ◽

Bioinformatic Analysis ◽

Mapping Method ◽

Eukaryotic Cells ◽

Causative Gene ◽

Biochemical Pathways ◽

Conventional Mapping ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Peroxisomes are the type of organelles in eukaryotic cells that are involved in different biochemical pathways depending on the type of cell. We have isolated a number of peroxisome unusual positioning (peup) mutants, which display the accumulation of abnormal peroxisomes, and demonstrated that autophagy is involved in removing damaged organelles. These peup mutants also show defects of other autophagy-related processes, such as the recovery from dark-senescence, and also failed to induce vacuole-related vesicle formations during microautophagy under nutrient deprivations. The aim of this study was to identify the causative gene of the peup33 mutant using next-generation sequencing (NGS) as a tool. Identification of mutations with NGS will allow us to save time compared to the conventional mapping method. Here, we present the workflow of the experiment, the procedure of bioinformatic analysis and the software applied to the sequence data produced by NGS.

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Catching SARS-CoV-2 by sequence hybridization: a comparative analysis

10.1101/2021.02.05.429917 ◽

2021 ◽

Author(s):

Alexandra Rehn ◽

Peter Braun ◽

Mandy Knüpfer ◽

Roman Wölfel ◽

Markus H. Antwerpen ◽

...

Keyword(s):

Sequence Data ◽

Full Length ◽

High Quality ◽

Essential Information ◽

Droplet Pcr ◽

Next Generation Sequencing Ngs ◽

Full Length Genome ◽

First Time ◽

Generation Sequencing ◽

New Mutations

AbstractControlling and monitoring the still ongoing SARS-CoV-2 pandemic regarding geographical distributions, evolution and emergence of new mutations of the SARS-CoV-2 virus is only possible due to continuous next-generation sequencing (NGS) and worldwide sequence data sharing. Efficient sequencing strategies enabling the retrieval of the maximum number of high quality, full-length genomes are hence indispensable. Here, we describe for the first time a combined approach of digital droplet PCR (ddPCR) and NGS to evaluate five commercially available sequence capture panels targeting SARS-CoV-2. In doing so, we were not only able to determine the most sensitive and specific capture panel, but to discriminate their mode of action and number of read pairs needed to recover a high quality full length genome. Thereby, we are providing essential information for all sequencing laboratories worldwide striving for maximizing the sequencing output and simultaneously minimizing time, costs and sequencing resources.

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CNNdel: Calling Structural Variations on Low Coverage Data Based on Convolutional Neural Networks

BioMed Research International ◽

10.1155/2017/6375059 ◽

2017 ◽

Vol 2017 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Jing Wang ◽

Cheng Ling ◽

Jingyang Gao

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Sequence Data ◽

High Sensitivity ◽

False Positives ◽

Detection Methods ◽

Structural Variations ◽

Next Generation Sequencing Ngs ◽

Low Coverage ◽

Generation Sequencing

Many structural variations (SVs) detection methods have been proposed due to the popularization of next-generation sequencing (NGS). These SV calling methods use different SV-property-dependent features; however, they all suffer from poor accuracy when running on low coverage sequences. The union of results from these tools achieves fairly high sensitivity but still produces low accuracy on low coverage sequence data. That is, these methods contain many false positives. In this paper, we present CNNdel, an approach for calling deletions from paired-end reads. CNNdel gathers SV candidates reported by multiple tools and then extracts features from aligned BAM files at the positions of candidates. With labeled feature-expressed candidates as a training set, CNNdel trains convolutional neural networks (CNNs) to distinguish true unlabeled candidates from false ones. Results show that CNNdel works well with NGS reads from 26 low coverage genomes of the 1000 Genomes Project. The paper demonstrates that convolutional neural networks can automatically assign the priority of SV features and reduce the false positives efficaciously.

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Exploring the Multidimensional Facets of Authoritarianism: Authoritarian Aggression and Social Dominance Orientation

Swiss Journal of Psychology ◽

10.1024/1421-0185.67.1.51 ◽

2008 ◽

Vol 67 (1) ◽

pp. 51-60 ◽

Cited By ~ 26

Author(s):

Stefano Passini

Keyword(s):

Social Dominance ◽

Factor Model ◽

Three Dimensional ◽

Social Dominance Orientation ◽

Model Fit ◽

Regression Analyses ◽

One Dimensional ◽

Confirmatory Factor ◽

The One ◽

Better Than

The relation between authoritarianism and social dominance orientation was analyzed, with authoritarianism measured using a three-dimensional scale. The implicit multidimensional structure (authoritarian submission, conventionalism, authoritarian aggression) of Altemeyer’s (1981, 1988) conceptualization of authoritarianism is inconsistent with its one-dimensional methodological operationalization. The dimensionality of authoritarianism was investigated using confirmatory factor analysis in a sample of 713 university students. As hypothesized, the three-factor model fit the data significantly better than the one-factor model. Regression analyses revealed that only authoritarian aggression was related to social dominance orientation. That is, only intolerance of deviance was related to high social dominance, whereas submissiveness was not.

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