Computational methods for discovering structural variation with next-generation sequencing

By Paul Medvedev, M. Stanciu, Michael Brudno. Nature Methods, 2009

596 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/4dd42112bf3ec0e6ae0563499903a3f2bdc9a1a0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Molecular Biology

In Plant Science

Citations in the corpus

LUMPY: a probabilistic framework for structural variant discovery (2012, background): “spanning paired-end reads that align discordantly relative to each other (read-pair), and breakpoint-containing single reads that align in split fashion to discontiguous loci in the reference genome (split-read) [1,2].”
Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives (2013, methodology): “However, PEM is not applicable to insertion events larger than the average insert size of the genome library [16].”
The impact of next-generation sequencing on genomics (2011, background): “…detection software, which includes screening genomes for structural and single nucleotide variants and the differences between genomes (Li et al., 2009; Medvedev et al., 2009; Thusberg and Vihinen, 2009), are generally integrated with alignment and assembly processes and are listed in Table 4.”
High‐throughput DNA sequencing – concepts and limitations (2010, background): “Given the immense diversity, we have not discussed these applications in depth here; other reviews with a stronger focus on specific applications and data analysis are available [24, 82–88].”
Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing (2012, methodology): “We used paired-end and split-read mapping of whole-genome data (Banerji et al., 2012; Bass et al., 2011; Medvedev et al., 2009) to detect and map the breakpoints of 2,349 somatic rearrangements across 24WGScases.”
CONTRA: copy number analysis for targeted resequencing (2012, unknown): “Received on April 5, 2011; revised on February 27, 2012; accepted on March 23, 2012”
Sequence-specific error profile of Illumina sequencers (2011, background): “It may be possible to reproduce the genome structure by speculating the connectivity between contigs using paired-end information, if the gaps are short enough (35).”
Genome graphs and the evolution of genome inference (2017, background): “The fact that sequence graphs make it possible to align and model known structural variants in the same manner as other types of variation may obviate the need for separate algorithms from SNV callers (Medvedev et al. 2009).”
A survey of tools for variant analysis of next-generation genome sequencing data (2013, background): “These so-called paired-end or mate-pair reads provide additional information which can be used for enhancing mapping accuracy and identifying structural rearrangements [53].”
Repetitive DNA and next-generation sequencing: computational challenges and solutions (2011, methodology): “Whole-genome resequencing combined with new, highly efficient alignment software is being used to discover large numbers of SNPs and structural variants in previously sequenced genome”