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| @article{Rhoads2015,
abstract = {Single-molecule, real-time sequencing developed by Pacific BioSciences offers longer read lengths than the second-generation sequencing (SGS) technologies, making it well-suited for unsolved problems in genome, transcriptome, and epigenetics research. The highly-contiguous de novo assemblies using PacBio sequencing can close gaps in current reference assemblies and characterize structural variation (SV) in personal genomes. With longer reads, we can sequence through extended repetitive regions and detect mutations, many of which are associated with diseases. Moreover, PacBio transcriptome sequencing is advantageous for the identification of gene isoforms and facilitates reliable discoveries of novel genes and novel isoforms of annotated genes, due to its ability to sequence full-length transcripts or fragments with significant lengths. Additionally, PacBio's sequencing technique provides information that is useful for the direct detection of base modifications, such as methylation. In addition to using PacBio sequencing alone, many hybrid sequencing strategies have been developed to make use of more accurate short reads in conjunction with PacBio long reads. In general, hybrid sequencing strategies are more affordable and scalable especially for small-size laboratories than using PacBio Sequencing alone. The advent of PacBio sequencing has made available much information that could not be obtained via SGS alone.},
author = {Rhoads, Anthony and Au, Kin Fai},
doi = {10.1016/j.gpb.2015.08.002},
file = {:home/cecile/Publis/main.pdf:pdf},
isbn = {1672-0229},
issn = {22103244},
journal = {Genomics, Proteomics and Bioinformatics},
keywords = {3rd generation sequencing,De novo assembly,Gene isoform detection,Hybrid sequencing,Methylation,Third-generation sequencing,pacbio},
mendeley-tags = {3rd generation sequencing,pacbio},
number = {5},
pages = {278--289},
pmid = {26542840},
publisher = {Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China},
title = {{PacBio Sequencing and Its Applications}},
url = {http://dx.doi.org/10.1016/j.gpb.2015.08.002},
volume = {13},
year = {2015}
}
@article{Laver2015,
abstract = {The Oxford Nanopore Technologies (ONT) MinION is a new sequencing technology that potentially offers read lengths of tens of kilobases (kb) limited only by the length of DNA molecules presented to it. The device has a low capital cost, is by far the most portable DNA sequencer available, and can produce data in real-time. It has numerous prospective applications including improving genome sequence assemblies and resolution of repeat-rich regions. Before such a technology is widely adopted, it is important to assess its performance and limitations in respect of throughput and accuracy. In this study we assessed the performance of the MinION by re-sequencing three bacterial genomes, with very different nucleotide compositions ranging from 28.6{\%} to 70.7{\%}; the high G. +. C strain was underrepresented in the sequencing reads. We estimate the error rate of the MinION (after base calling) to be 38.2{\%}. Mean and median read lengths were 2. kb and 1. kb respectively, while the longest single read was 98. kb. The whole length of a 5. kb rRNA operon was covered by a single read. As the first nanopore-based single molecule sequencer available to researchers, the MinION is an exciting prospect; however, the current error rate limits its ability to compete with existing sequencing technologies, though we do show that MinION sequence reads can enhance contiguity of de novo assembly when used in conjunction with Illumina MiSeq data.},
author = {Laver, T. and Harrison, J. and O'Neill, P. A. and Moore, K. and Farbos, A. and Paszkiewicz, K. and Studholme, D. J.},
doi = {10.1016/j.bdq.2015.02.001},
file = {:home/cecile/Publis/laver2015.pdf:pdf},
issn = {22147535},
journal = {Biomolecular Detection and Quantification},
keywords = {DNA sequencing,MinION,Nanopore},
pages = {1--8},
pmid = {26753127},
publisher = {Elsevier GmbH},
title = {{Assessing the performance of the Oxford Nanopore Technologies MinION}},
url = {http://dx.doi.org/10.1016/j.bdq.2015.02.001},
volume = {3},
year = {2015}
}
@article{Gordon2016,
author = {{Gordon, David; Huddleston, John; Chaisson, Mark; Hill, Christopher; Kronenberg , Zev; Munson, Katherine; Malig, Maika; Raja, Archana; Fiddes, Ian; Hillier, LaDeana; Dunn, Christopher; Baker, Carl; Armstrong, Joel; Diekhans, Mark; Paten, Benedict; Shendure}, Evan},
file = {:home/cecile/Publis/aae0344.full.pdf:pdf},
keywords = {3rd generation sequencing,assemblage,pan-genome},
mendeley-tags = {3rd generation sequencing,pan-genome,assemblage},
title = {{Long-read sequence assembly of the gorilla genome}}
}
@article{Santos2016,
author = {Santos, Leonardo N. and Silva, Eduardo S. and Santos, Andr{\'{e}} S. and {De S{\'{a}}}, Pablo H. and Ramos, Rommel T. and Silva, Artur and Cooper, Philip J. and Barreto, Maur{\'{i}}cio L. and Loureiro, Sebasti{\~{a}}o and Pinheiro, Carina S. and Alcantara-Neves, Neuza M. and Pacheco, Luis G.C.},
doi = {10.1016/j.actatropica.2016.03.036},
file = {:home/cecile/Publis/1-s2.0-S0001706X16301474-main.pdf:pdf},
issn = {0001706X},
journal = {Acta Tropica},
keywords = {3rd generation sequencing,pan-genome,transcriptome},
mendeley-tags = {3rd generation sequencing,transcriptome,pan-genome},
pages = {132--141},
publisher = {Elsevier B.V.},
title = {{De novo assembly and characterization of the Trichuris trichiura adult worm transcriptome using Ion Torrent sequencing}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0001706X16301474},
volume = {159},
year = {2016}
}
@article{Hatem2013,
file = {:home/cecile/Publis/art{\%}3A10.1186{\%}2F1471-2105-14-184.pdf:pdf},
keywords = {benchmark,mapping,next-generation sequencing,sequence analysis,short sequence mapping,tools},
mendeley-tags = {mapping,tools},
title = {{Benchmarking short sequence mapping tools ˘ 2 ,}},
year = {2013}
}
@article{Fonseca2012a,
abstract = {MOTIVATION: A ubiquitous and fundamental step in high-throughput sequencing analysis is the alignment (mapping) of the generated reads to a reference sequence. To accomplish this task, numerous software tools have been proposed. Determining the mappers that are most suitable for a specific application is not trivial. RESULTS: This survey focuses on classifying mappers through a wide number of characteristics. The goal is to allow practitioners to compare the mappers more easily and find those that are most suitable for their specific problem.},
author = {Fonseca, Nuno A. and Rung, Johan and Brazma, Alvis and Marioni, John C.},
doi = {10.1093/bioinformatics/bts605},
file = {:home/cecile/Publis/Bioinformatics-2012-Fonseca-3169-77.pdf:pdf},
isbn = {1367-4811 (Electronic)$\backslash$r1367-4803 (Linking)},
issn = {13674803},
journal = {Bioinformatics},
keywords = {mapping,tools},
mendeley-tags = {mapping,tools},
number = {24},
pages = {3169--3177},
pmid = {23060614},
title = {{Tools for mapping high-throughput sequencing data}},
volume = {28},
year = {2012}
}
@article{Dai2012,
abstract = {UNLABELLED: As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.$\backslash$n$\backslash$nREVIEWERS: This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.},
author = {Dai, Lin and Gao, Xin and Guo, Yan and Xiao, Jingfa and Zhang, Zhang},
doi = {10.1186/1745-6150-7-43},
file = {:home/cecile/Publis/1745-6150-7-43.pdf:pdf},
isbn = {1745-6150},
issn = {1745-6150},
journal = {Biology direct},
keywords = {Access to Information,Computational Biology,Computational Biology: methods,Data Collection,Information Storage and Retrieval,Information Storage and Retrieval: classification,Information Storage and Retrieval: methods,Internet,Software,User-Computer Interface,cloud},
mendeley-tags = {cloud},
pages = {43; discussion 43},
pmid = {23190475},
title = {{Bioinformatics clouds for big data manipulation.}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3533974{\&}tool=pmcentrez{\&}rendertype=abstract},
volume = {7},
year = {2012}
} |
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