DSK: <i>k</i>-mer counting with very low memory usage

Rizk, Guillaume; Lavenier, Dominique; Chikhi, Rayan

doi:10.1093/bioinformatics/btt020

Cited by 282 publications

(249 citation statements)

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“…First, starting from the full read set of Vc3 (40.3 million read pairs), reads were filtered according to their k-mer coverage to obtain only the reads originating from the targeted genome and thus avoid simultaneously assembling the whole nuclear pea aphid genome. Given that the targeted genome had an average read depth in Vc3 of around 600 × , only reads for which 68% of the length was covered by 31-mers present at least 100 times in the data set were retained, using readFilter (P Peterlongo et al, unpublished) a custom software based on k-mer counts performed by the DSK software (Rizk et al, 2013). Reads that could be mapped to the B. aphidicola or mitochondrial genomes were removed as their coverage levels would otherwise lead them to be retained in this read set.…”

Section: De Novo Assembly and Characterization Of An Aphid Symbiont Gmentioning

confidence: 99%

Whole-genome re-sequencing of non-model organisms: lessons from unmapped reads

et al. 2014

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Unmapped reads are often discarded from the analysis of whole-genome re-sequencing, but new biological information and insights can be uncovered through their analysis. In this paper, we investigate unmapped reads from the re-sequencing data of 33 pea aphid genomes from individuals specialized on different host plants. The unmapped reads for each individual were retrieved following mapping to the Acyrthosiphon pisum reference genome and its mitochondrial and symbiont genomes. These sets of unmapped reads were then cross-compared, revealing that a significant number of these unmapped sequences were conserved across individuals. Interestingly, sequences were most commonly shared between individuals adapted to the same host plant, suggesting that these sequences may contribute to the divergence between host plant specialized biotypes. Analysis of the contigs obtained from assembling the unmapped reads pooled by biotype allowed us to recover some divergent genomic regions previously excluded from analysis and to discover putative novel sequences of A. pisum and its symbionts. In conclusion, this study emphasizes the interest of the unmapped component of re-sequencing data sets and the potential loss of important information. We here propose strategies to aid the capture and interpretation of this information. Heredity (2015) 114, 494-501; doi:10.1038/hdy.2014.85; published online 1 October 2014 INTRODUCTION Next-generation sequencing and whole-genome re-sequencing is nowadays commonly used to identify genomic variants that underlie phenotypic variations, genetic diseases, adaptation or speciation in natural populations. Typically, the reads are mapped against a reference genome, and the genotypes (that is, single-nucleotide polymorphism (SNP) and structural variant calls) are based on these mapped reads (Altshuler et al., 2010;Nielsen et al., 2011). In addition to universal caveats regarding unknown insertions and/or genomic contamination, which can be overlooked in pure mapping approaches, non-model organisms may suffer from the poor quality of the nuclear reference genome and incomplete symbiont or organellar genomes. Moreover, mapping is constrained by the level of divergence between the reads and the available reference sequence (Sousa and Hey, 2013). The resulting ascertainment bias could be problematic, especially when studying adaptation or speciation processes, as genomic regions of interest are expected to display important levels of divergence. These different issues produce a non-negligible fraction of unmapped reads, whose sequences are generally disregarded in favor of the mapped reads in the subsequent steps of the analysis, despite potentially containing useful information. This study offers one strategy for mining the unmapped reads in order to extract the relevant biological knowledge, leading to advice and recommendations for other re-sequencing projects.We investigated this question in the context of a large-scale resequencing project on the pea aphid species complex. The pea aphid

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Section: De Novo Assembly and Characterization Of An Aphid Symbiont Gmentioning

confidence: 99%

Whole-genome re-sequencing of non-model organisms: lessons from unmapped reads

et al. 2014

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“…Разработано достаточное количество программных средств, предназначенных для подсчета числа k-меров в последовательностях: Jellyfish [8], BFCounter [9], DSK [10] и другие. Поскольку BFCounter не позволяет отслеживать k-меры, встречающиеся в единственном экземпляре, а DSK не смог корректно завершить свою работу на ряде входных данных, было принято решение использовать программу Jellyfish для подсчета числа встречаемости k-меров.…”

Section: подсчет числа уникальных K-меровunclassified

A new method of evaluating genome assemblies based on kmers frequencies

Romanenkov¹

2017

KIAM Prepr.

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Метод оценки качества сборки генома на основе частот k-меров Достаточно распространена ситуация, когда результаты применения геномных сборщиков или одного сборщика с разными параметрами существенно отличаются для одних и тех же входных данных, при этом в настоящее время не существует единой методики выбора наилучшей сборки. В данной работе предложен новый метод оценки качества геномной сборки организмов, для которых использование уже собранных геномов невозможно, с помощью анализа частот k-меров на основе программного средства Jellyfish. Предложенный метод устанавливает соответствие между набором коротких чтений, полученных в результате секвенирования, и собранным геномом, позволяя более точно оценивать результат геномной сборки. В результате проверки метода на различных сборках организма Encephalitozoon cuniculi fungus было установлено, что в большинстве случаев предложенная методика коррелирует с референс-зависимыми метриками и позволяет корректно определять лучшую сборку. При этом не была выявлена взаимосвязь между качеством сборки и стандартными метриками. Ключевые слова: частоты k-меров, сравнение геномных сборок, оценка качества геномной сборки, Encephalitozoon cuniculi fungus Kirill Vladimirovich RomanenkovA new method of evaluating genome assemblies based on kmers frequencies Running different genome assemblers or one genome assembler with different parameters on the same input data commonly leads to a great variety of results. However, there is no generally recognized method for choosing the best assembly. This article introduces a new reference-free method based on Jellyfish software for evaluating genome assembly by kmers frequencies analysis. The proposed method sets up a correspondence between short reads obtained from sequencer and assembled genome, which allows a more accurate genome assembly assessing. The method was validated on different assemblies of Encephalitozoon cuniculi fungus organism. It was found that in most cases it correlates with reference-dependent metrics and could correctly identify the best assembly. Furthermore, an interconnection between assembly quality and standard reference-free metrics was not observed.

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“…DSK [10] uses this method to make kmers partitioning in disk. To make the kmers disk partitioning is necessary to calculate the number of kmers, the number of iterations (ni) to cycle through the kmers and the number of partitions (np) to be created in disk.…”

Section: Kmers Distribution Through a Hash Functionmentioning

confidence: 99%

“…function with the use of DSK [10] for the kmer counting stage and the minimizers method through BCALM [12] for node simplification in the De Bruijn graph. Once the nodes are simplified and contigs generated EPGA2 joins the contigs in parallel [17].…”

Section: International Journal Of Bioscience Biochemistry and Bioinfmentioning

confidence: 99%

Disk Partition Techniques Assesment and Analysis Applied to Genomic Assemblers Based on Bruijn Graphs

Vera-Parra¹,

Medina-Daza²,

Rojas-Quintero³

2016

IJBBB

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Abstract:In this paper an assessment of several de-novo genomic assembler tools based on de Bruijn graph is made, with the purpose to measure the impact of the use of disk partitioning techniques regarding the computational requirements and generate a framework for bioinformatics researchers to let them identify advantages, disadvantages, bottlenecks and challenges of the assemblers using those techniques.Assessed assemblers using disk partitioning techniques were: Minia and EPGA, the assessed assemblers that do not use disk partitioning were: ABySS and SOAPDenovo2. The parameters measured were the following: occupied space in RAM, processing time, parallelization and disk read and write access. A dataset was used with 36,504,800 short reads corresponding to 14th human chromosome. The assessment was made for two kmers size: 31 and 55. The results obtained were the following: The tools based on disk partitioning techniques showed the less RAM use. The tools with more I/O transfer intensity were the ones using disk partitioning techniques. The techniques that achieved more parallelization were the ones using disk partitioning.

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DSK: k-mer counting with very low memory usage

Abstract: http://minia.genouest.org/dsk

Cited by 282 publications

References 2 publications

Whole-genome re-sequencing of non-model organisms: lessons from unmapped reads

Whole-genome re-sequencing of non-model organisms: lessons from unmapped reads

A new method of evaluating genome assemblies based on kmers frequencies

Disk Partition Techniques Assesment and Analysis Applied to Genomic Assemblers Based on Bruijn Graphs

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