LUMPY: a probabilistic framework for structural variant discovery

Layer, Ryan M.; Chiang, Colby; Quinlan, Aaron R.; Hall, Ira M.

doi:10.1186/gb-2014-15-6-r84

Cited by 1,262 publications

(1,358 citation statements)

References 23 publications

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“…SV were identified from split reads and discordant pairs using lumpy v0.2.11 24 and CNV from read depth differences using CNVnator v0.3 25 as implemented in the SpeedSeq pipeline 0.0.3a. 26 In patients in whom a disease-causing variant in PKD1 or PKD2 could not be identified, seven additional genes (HNF1B, PKHD1, SEC63, PRKCSH, TSC1, TSC2, OFD1) that are also associated with a polycystic kidney phenotype were assessed for SNV and indel, and HNF1B was assessed for deletions.…”

Section: Methodsmentioning

confidence: 99%

Whole-genome sequencing overcomes pseudogene homology to diagnose autosomal dominant polycystic kidney disease

et al. 2016

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Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic kidney disorder and is due to diseasecausing variants in PKD1 or PKD2. Strong genotype-phenotype correlation exists although diagnostic sequencing is not part of routine clinical practice. This is because PKD1 bears 97.7% sequence similarity with six pseudogenes, requiring laborious and error-prone long-range PCR and Sanger sequencing to overcome. We hypothesised that whole-genome sequencing (WGS) would be able to overcome the problem of this sequence homology, because of 150 bp, paired-end reads and avoidance of capture bias that arises from targeted sequencing. We prospectively recruited a cohort of 28 unique pedigrees with ADPKD phenotype. Standard DNA extraction, library preparation and WGS were performed using Illumina HiSeq X and variants were classified following standard guidelines. Molecular diagnosis was made in 24 patients (86%), with 100% variant confirmation by current gold standard of long-range PCR and Sanger sequencing. We demonstrated unique alignment of sequencing reads over the pseudogene-homologous region. In addition to identifying function-affecting single-nucleotide variants and indels, we identified single-and multi-exon deletions affecting PKD1 and PKD2, which would have been challenging to identify using exome sequencing. We report the first use of WGS to diagnose ADPKD. This method overcomes pseudogene homology, provides uniform coverage, detects all variant types in a single test and is less labour-intensive than current techniques. This technique is translatable to a diagnostic setting, allows clinicians to make better-informed management decisions and has implications for other disease groups that are challenged by regions of confounding sequence homology.

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Section: Methodsmentioning

confidence: 99%

Whole-genome sequencing overcomes pseudogene homology to diagnose autosomal dominant polycystic kidney disease

et al. 2016

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“…followed by a probabilistic framework for detecting variants that incorporates multiple types of evidence (SI Materials and Methods, SI CNV in P. vivax and P. falciparum). A subset of P. falciparum md1 CNVs was confirmed using qPCR as described previously (1,94).…”

Section: Discussionmentioning

confidence: 99%

Selective sweep suggests transcriptional regulation may underlie Plasmodium vivax resilience to malaria control measures in Cambodia

Parobek

Lin

Saunders

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Cambodia, in which both Plasmodium vivax and Plasmodium falciparum are endemic, has been the focus of numerous malaria-control interventions, resulting in a marked decline in overall malaria incidence. Despite this decline, the number of P. vivax cases has actually increased. To understand better the factors underlying this resilience, we compared the genetic responses of the two species to recent selective pressures. We sequenced and studied the genomes of 70 P. vivax and 80 P. falciparum isolates collected between 2009 and 2013. We found that although P. falciparum has undergone population fracturing, the coendemic P. vivax population has grown undisrupted, resulting in a larger effective population size, no discernable population structure, and frequent multiclonal infections. Signatures of selection suggest recent, species-specific evolutionary differences. Particularly, in contrast to P. falciparum, P. vivax transcription factors, chromatin modifiers, and histone deacetylases have undergone strong directional selection, including a particularly strong selective sweep at an AP2 transcription factor. Together, our findings point to different population-level adaptive mechanisms used by P. vivax and P. falciparum parasites. Although population substructuring in P. falciparum has resulted in clonal outgrowths of resistant parasites, P. vivax may use a nuanced transcriptional regulatory approach to population maintenance, enabling it to preserve a larger, more diverse population better suited to facing selective threats. We conclude that transcriptional control may underlie P. vivax's resilience to malaria control measures. Novel strategies to target such processes are likely required to eradicate P. vivax and achieve malaria elimination.D uring the last decade, western Cambodia has been the focus of numerous and multimodal interventions to control the spread of artemisinin-resistant Plasmodium falciparum (1, 2). Such interventions, including increased vector control, increased surveillance, and improved access to quality artemisinin-combination therapy (ACT), would be expected to curtail coendemic Plasmodium vivax as well. However, even as P. falciparum infections in Cambodia decreased by 81% between 2009 and 2013, P. vivax cases have increased, making it the predominant species in the Mekong region (3-6). This scenario, repeated in Brazil and other areas of coendemicity, has led to growing awareness that P. vivax, although infecting the same populations and transmitted by the same mosquito vectors, will likely be the more challenging species to eradicate (6-9). In this study, we use population genomics to gain insight into the evolutionary factors underlying P. vivax's resilience to malaria control measures.Population genetic studies have previously hinted at the resilience of P. vivax populations in comparison with P. falciparum. Studies of microsatellites and highly variable antigens of sympatric P. vivax and P. falciparum populations in Southeast Asia and the Southwest Pacific have consistently shown P. viv...

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“…We compared the GRIDSS results to eight other tools (BreakDancer [Chen et al 2009], Pindel [Ye et al 2009], DELLY [Rausch et al 2012], Hydra-Multi , LUMPY [Layer et al 2014], Socrates , Cortex [Iqbal et al 2012], and Manta [Chen et al 2016]) (Supplemental Figs. S1, S2; see Supplemental Material for details).…”

Section: Performance On Simulated Datamentioning

confidence: 99%

“…First, GRIDSS was applied to short-read sequencing data from the NA12878 Illumina Platinum Genomes cell line (50× coverage PCR-free 2×100 bp, accession ERA172924), along with several other structural variant callers. Callers were evaluated against both curated validated call sets (Mills et al 2011;Layer et al 2014) and against PacBio and Illumina TruSeq Synthetic Long-Read technology (Moleculo) (Sudmant et al 2015). As previously (Mills et al 2011), only deletions longer than 50 bp were considered.…”

Section: Performance On Cell Line Datamentioning

confidence: 99%

“…SR methods find breakpoints by identifying split alignments in which part of the read aligns to either side of a genomic rearrangement, either through direct split read mapping by read aligner, realignment of soft clipped (SC) bases (unaligned bases in partially mapped reads), or split alignment of the unmapped (UM) read in one-ended anchored (OEA) read pairs (read pairs with only one read mapped) (Kidd et al 2008). These three forms of evidence can be combined in different ways; for example, DELLY combines DP and SR evidence (Rausch et al 2012), while LUMPY (Layer et al 2014) uses all three types.…”

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GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly

et al. 2017

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The identification of genomic rearrangements with high sensitivity and specificity using massively parallel sequencing remains a major challenge, particularly in precision medicine and cancer research. Here, we describe a new method for detecting rearrangements, GRIDSS (Genome Rearrangement IDentification Software Suite). GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based assembler. By combining assembly, split read, and read pair evidence using a probabilistic scoring, GRIDSS achieves high sensitivity and specificity on simulated, cell line, and patient tumor data, recently winning SV subchallenge #5 of the ICGC-TCGA DREAM8.5 Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods while matching or exceeding their sensitivity. GRIDSS identifies nontemplate sequence insertions, microhomologies, and large imperfect homologies, estimates a quality score for each breakpoint, stratifies calls into high or low confidence, and supports multisample analysis.

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LUMPY: a probabilistic framework for structural variant discovery

Cited by 1,262 publications

References 23 publications

Whole-genome sequencing overcomes pseudogene homology to diagnose autosomal dominant polycystic kidney disease

Whole-genome sequencing overcomes pseudogene homology to diagnose autosomal dominant polycystic kidney disease

Selective sweep suggests transcriptional regulation may underlie Plasmodium vivax resilience to malaria control measures in Cambodia

GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly

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