7,295 research outputs found
Large-scale compression of genomic sequence databases with the Burrows-Wheeler transform
No full textCox AJ, Bauer MJ, Jakobi T, Rosone G. Large-scale compression of genomic sequence databases with the Burrows-Wheeler transform. Bioinformatics. 2012;28(11):1415-1419.MOTIVATION: The Burrows-Wheeler transform (BWT) is the foundation of many algorithms for compression and indexing of text data, but the cost of computing the BWT of very large string collections has prevented these techniques from being widely applied to the large sets of sequences often encountered as the outcome of DNA sequencing experiments. In previous work (Bauer et al. (2011)), we presented a novel algorithm that allows the BWT of human genome scale data to be computed on very moderate hardware, thus enabling us to investigate the BWT as a tool for the compression of such datasets. RESULTS: We first used simulated reads to explore the relationship between the level of compression and the error rate, the length of the reads and the level of sampling of the underlying genome and compare choices of second-stage compression algorithm.We demonstrate that compression may be greatly improved by a particular reordering of the sequences in the collection and give a novel 'implicit sorting' strategy that enables these benefits to be realised without the overhead of sorting the reads. With these techniques, a 45× coverage of real human genome sequence data compresses losslessly to under 0.5 bits per base, allowing the 135.3Gbp of sequence to fit into only 8.2Gbytes of space (trimming a small proportion of low-quality bases from the reads improves the compression still further).This is more than 4 times smaller than the size achieved by a standard BWT-based compressor (bzip2) on the untrimmed reads, but an important further advantage of our approach is that it facilitates the building of compressed full text indexes such as the FMindex (Ferragina and Manzini (2000)) on large-scale DNA sequence collections. AVAILABILITY: Code to construct the BWT and SAP-array on large genomic data sets is part of the BEETL library, available as a github respository at [email protected]:BEETL/BEETL.git. CONTACT: [email protected]
Lightweight algorithms for constructing and inverting the BWT of string collections
No full textRecent progress in the field of \{DNA\} sequencing motivates us to consider the problem of computing the Burrows–Wheeler transform (BWT) of a collection of strings. A human genome sequencing experiment might yield a billion or more sequences, each 100 characters in length. Such a dataset can now be generated in just a few days on a single sequencing machine. Many algorithms and data structures for compression and indexing of text have the \{BWT\} at their heart, and it would be of great interest to explore their applications to sequence collections such as these. However, computing the \{BWT\} for 100 billion characters or more of data remains a computational challenge. In this work we address this obstacle by presenting a methodology for computing the \{BWT\} of a string collection in a lightweight fashion. A first implementation of our algorithm needs O ( m log m ) bits of memory to process m strings, while a second variant makes additional use of external memory to achieve \{RAM\} usage that is constant with respect to m and negligible in size for a small alphabet such as DNA. The algorithms work on any number of strings and any size. We evaluate our algorithms on collections of up to 1 billion strings and compare their performance to other approaches on smaller datasets. We take further steps toward making the \{BWT\} a practical tool for processing string collections on this scale. First, we give two algorithms for recovering the strings in a collection from its BWT. Second, we show that if sequences are added to or removed from the collection, then the \{BWT\} of the original collection can be efficiently updated to obtain the \{BWT\} of the revised collection
Lightweight LCP construction for next-generation sequencing datasets
No full textThe advent of "next-generation" DNA sequencing (NGS) technologies has meant that collections of hundreds of millions of DNA sequences are now commonplace in bioinformatics. Knowing the longest common prefix array (LCP) of such a collection would facilitate the rapid computation of maximal exact matches, shortest unique substrings and shortest absent words. CPU-efficient algorithms for computing the LCP of a string have been described in the literature, but require the presence in RAM of large data structures. This prevents such methods from being feasible for NGS datasets. In this paper we propose the first lightweight method that simultaneously computes, via sequential scans, the LCP and BWT of very large collections of sequences. Computational results on collections as large as 800 million 100-mers demonstrate that our algorithm scales to the vast sequence collections encountered in human whole genome sequencing experiments
Lightweight LCP Construction for Next-Generation Sequencing Datasets
No full textThe advent of "next-generation" DNA sequencing (NGS) technologies has meant that collections of hundreds of millions of DNA sequences are now commonplace in bioinformatics. Knowing the longest common prefix array (LCP) of such a collection would facilitate the rapid computation of maximal exact matches, shortest unique substrings and shortest absent words. CPU-efficient algorithms for computing the LCP of a string have been described in the literature, but require the presence in RAM of large data structures. This prevents such methods from being feasible for NGS datasets.
In this paper we propose the first lightweight method that simultaneously computes, via sequential scans, the LCP and BWT of very large collections of sequences. Computational results on collections as large as 800 million 100-mers demonstrate that our algorithm scales to the vast sequence collections encountered in human whole genome sequencing experiments
Self-compression of 4.9 µm pulses to sub-40 fs with 2 mJ energy in Zinc Sulfide
No full textNonlinear self-compression of few-cycle multi-mJ pulses at 4.9 µm in ZnS is presented. 80 fs input pulses are compressed to 37 fs with 2.1 mJ energy at a 1 kHz repetition rate. © 2024 The Author(s
SPECIFIC HEAT OF HoYB2C
No full textThe magnetic superconductor HoNi2B2C was studied by specific heat measurements in magnetic fields up to 2 T. The specific heat jump Delta C due to the superconducting transition at (T) over bar(c) = 8.15 K is about 140 mJ/mol K. In the scope of the Abrikosov-Gor'kov pair-breaking theory, this value is in line with a Sommerfeld value of about 19 mJ/mol K-2 as observed for the non-magnetic superconductors YNi2B2C and LuNi2B2C
Pacto de classes do Plano Real
No full textTCC (graduação) - Universidade Federal de Santa Catarina. Centro Sócio-Econômico. Economia.Trata-se esse estudo de uma tentativa de compreender como se estrutura a atual configuração econômica e política da sociedade brasileira. Essa configuração se estabelece a partir de um pacto de classes que ficou conhecido como Plano Real. Envolvendo a burguesia nacional, aprofundando sua submissão ao capital internacional, em especial o capital financeiro, mas incluindo também parte da classe trabalhadora, esse pacto foi capaz de impedir um acirramento da luta de classes dentro do capitalismo brasileiro, garantindo o lucro das classes capitalista e o aprofundamento da superexploração da força de trabalho. Essa é a verdadeira essência do Plano Real, longe de ser apenas um plano de estabilização e controle da inflação. É isso que tentamos demonstrar com esse trabalho: a construção de um pacto de classes, que tem sua origem na própria estrutura do capitalismo dependente brasileiro, que se inicia no governo de Fernando Henrique Cardoso, mas continua nos governos petistas e se expressa na atual política econômica do governo Dilma
Correction to: Chamoun et al., Bacterial pathogenesis and interleukin-17: interconnecting mechanisms of immune regulation, host genetics, and microbial virulence that influence severity of infection
No full textChamoun MN, Blumenthal A, Sullivan MJ, Schembri MA, Ulett GC. 2018. Bacterial pathogenesis and interleukin-17: interconnecting mechanisms of immune regulation, host genetics, and microbial virulence that influence severity of infection. Critical Reviews in Microbiology. https://doi.org/10.1080/1040841X.2018.1426556.
When the above article was first published online, the below three corrections were missed.
The author ‘Antje Blumenthal’ was wrongly affiliated to the affiliation “cSchool of Chemistry and Molecular Biosciences, and Australian Infectious Disease Research Centre, The University of Queensland, Brisbane, Australia”. Now this affiliation has been removed for this author.
The affiliation ‘bTranslational Research Institute, The University of Queensland Diamantina Institute, Woolloongabba, Australia’ of the author ‘Antje Blumenthal’ should read ‘bThe University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia’.
In Table 3, the sentence ‘Benefit of manipulating IL-17 levels to improve immunization strategies M. tuberculosis’ should read “Benefit of manipulating IL-17 levels to improve immunization strategies against M. tuberculosis”.No Full Tex
Generation of 22-mJ, 2.0-ps Pulses from a 1-kHz Ho:YLF Regenerative Chirped Pulse Amplifier
No full textWe report a CW-pumped Ho:YLF regenerative amplifier (RA) delivering pulses with 22.5-mJ energy and 2.0-ps duration at 1 kHz. The RA emitting at 2051 nm is broadband-seeded and implemented in a chirped pulse amplification system. © 2024 The Author(s
The impact of extrahepatic disease among patients undergoing liver-directed therapy for neuroendocrine liver metastasis: A multi-institutional analysis
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