2014
DOI: 10.1002/0471142905.hg0722s80
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Design of Large‐Insert Jumping Libraries for Structural Variant Detection Using Illumina Sequencing

Abstract: Next generation sequencing is an important and efficient tool for the identification of structural variation, particularly balanced chromosomal rearrangements because such events are not routinely detected by microarray and localization of altered regions by karyotype is imprecise. Indeed, the degree of resolution that can be obtained through next generation technologies enables elucidation of precise breakpoints and has facilitated the discovery of numerous pathogenic loci in human disease and congenital anom… Show more

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Cited by 28 publications
(37 citation statements)
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“…Customized sequencing libraries were constructed based on published protocols [16] and sequenced with paired-end 50-bp reads on an Illumina HiSeq2500. Library barcodes were demultiplexed with CASAVA v1.7.…”
Section: Methodsmentioning
confidence: 99%
“…Customized sequencing libraries were constructed based on published protocols [16] and sequenced with paired-end 50-bp reads on an Illumina HiSeq2500. Library barcodes were demultiplexed with CASAVA v1.7.…”
Section: Methodsmentioning
confidence: 99%
“…According to array CGH, complex translocation breakpoints in EGL312 and EGL356 border repetitive regions, so we performed Nextera mate-pair sequencing (Illumina) of 5-to 7-kb inserts. This approach is ideal for junctions in repetitive DNA because mate pairs span repeats and map to unique sequence (Kloosterman et al 2011;Talkowski et al 2011Talkowski et al , 2012Hanscom and Talkowski 2014). We identified discordant reads for one of two junctions expected in EGL312 and for three of four junctions expected in EGL356.…”
Section: Complex Translocations Between Two Chromosomesmentioning
confidence: 96%
“…8,[14][15][16][17] We generated jumping libraries according to published protocols with a median insert size of 3.75 kb, and subjects were sequenced to an average of 94.13 haploid physical coverage. 18 We performed analyses by integrating three algorithms that we customized for long-insert libraries: LUMPY, 19 cn.MOPS, 20 and our SV classifier. 8 These computational methods detect both anomalous read pairs that cluster in proximity to SV breakpoints and genomic intervals with aberrant sequencing depth indicating copy gain or loss.…”
mentioning
confidence: 99%