Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60077344%3A_____%2F10%3A00347465" target="_blank" >RIV/60077344:_____/10:00347465 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data

Popis výsledku v původním jazyce

We adapted a graph-based approach for similarity-based partitioning of whole genome 454 sequence reads in order to build clusters made of the reads derived from individual repeat families. The information about cluster sizes was utilized for assessing the proportion and composition of repeats in the genomes of two model species,differing in genome size and 454 sequencing coverage. Moreover, statistical analysis and visual inspection of the topology of the cluster graphs using a newly developed program tool, SeqGrapheR, were shown to be helpful in distinguishing basic types of repeats and investigating sequence variability within repeat families. Repetitive regions of plant genomes can be efficiently characterized by the presented graph-based analysis and the graph representation of repeats can be further used to assess the variability and evolutionary divergence of repeat families, discover and characterize novel elements, and aid in subsequent assembly of their consensus sequences

Název v anglickém jazyce

Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data

Popis výsledku anglicky

We adapted a graph-based approach for similarity-based partitioning of whole genome 454 sequence reads in order to build clusters made of the reads derived from individual repeat families. The information about cluster sizes was utilized for assessing the proportion and composition of repeats in the genomes of two model species,differing in genome size and 454 sequencing coverage. Moreover, statistical analysis and visual inspection of the topology of the cluster graphs using a newly developed program tool, SeqGrapheR, were shown to be helpful in distinguishing basic types of repeats and investigating sequence variability within repeat families. Repetitive regions of plant genomes can be efficiently characterized by the presented graph-based analysis and the graph representation of repeats can be further used to assess the variability and evolutionary divergence of repeat families, discover and characterize novel elements, and aid in subsequent assembly of their consensus sequences

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

EB - Genetika a molekulární biologie

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

B M C Bioinformatics

ISSN

1471-2105

e-ISSN

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Svazek periodika

11

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

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Kód UT WoS článku

000281440900001

EID výsledku v databázi Scopus

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