Spatial smoothing and hot spot detection for CGH data using the fused lasso

Tibshirani, Robert; Wang, Pei

doi:10.1093/biostatistics/kxm013

Cited by 307 publications

(301 citation statements)

References 9 publications

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“…The filtered sequencing data was then allocated to 20-kb sequencing bins with an average number of 30-35 reads per bin. To calculate the mean CNV variation, binned read counts at each genomic location were internally compared across a minimum of 15 sample data sets using the fused lasso smoothing algorithm [28]. Plots of log2 mean CNV (Y-axis) versus 20-kb bins (X-axis) were generated for each of the 24 chromosomes.…”

Section: Sequence Data Analysis and Derivation Of 24 Chromosome Profilesmentioning

confidence: 99%

Clinical application of next-generation sequencing in preimplantation genetic diagnosis cycles for Robertsonian and reciprocal translocations

Zhang

Liu

Wang

et al. 2016

J Assist Reprod Genet

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Purpose The purpose of this study was to apply nextgeneration sequencing (NGS) technology to identify chromosomally normal embryos for transfer in preimplantation genetic diagnosis (PGD) cycles for translocations. Methods A total of 21 translocation couples with a history of infertility and repeated miscarriage presented at our PGD clinic for 24-chromosome embryo testing using copy number variation sequencing (CNV-Seq).Results Testing of 98 embryo samples identified 68 aneuploid (69.4 %) and 30 (30.6 %) euploid embryos. Among the aneuploid embryos, the most common abnormalities were segmental translocation imbalances, followed by whole autosomal trisomies and monosomies, segmental imbalances of nontranslocation chromosomes, and mosaicism. In all unbalanced embryos resulting from reciprocal translocations, CNV-Seq precisely identified both segmental imbalances, extending from the predicted breakpoints to the chromosome termini. From the 21 PGD cycles, eight patients had all abnormal embryos and 13 patients had at least one normal/balanced and euploid embryo available for transfer. In nine intrauterine transfer cycles, seven healthy babies have been born. In four of the seven children tested at 18 weeks gestation, the karyotypes matched with the original PGD results. Conclusion In clinical PGD translocation cycles, CNV-Seq displayed the hallmarks of a comprehensive diagnostic technology for high-resolution 24-chromosome testing of embryos, capable of identifying true euploid embryos for transfer.

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Section: Sequence Data Analysis and Derivation Of 24 Chromosome Profilesmentioning

confidence: 99%

Clinical application of next-generation sequencing in preimplantation genetic diagnosis cycles for Robertsonian and reciprocal translocations

Zhang

Liu

Wang

et al. 2016

J Assist Reprod Genet

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“…Genomic segmentation was used to detect amplified and deleted segments with stringent parameters (Po0.0001, 420 markers, signal/noise X0.6, minimal region size ¼ 100 markers) To control for hyperfragmentation adjacent segments separated by o50 probes were combined into one single segment, and only segments 4100 probes were considered. Multiple hypothesis correction by Benjamini and Hochberg and by cghFLasso algorithm 21 was applied and FDR threshold was set at 0.05. Correspondence with gene expression was calculated by Spearman's (rank) correlation coefficient.…”

Section: Snp Arraymentioning

confidence: 99%

A molecular portrait of gastrointestinal stromal tumors: an integrative analysis of gene expression profiling and high-resolution genomic copy number

Astolfi

Nannini

Pantaleo

et al. 2010

Laboratory Investigation

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In addition to KIT and PDGFRA mutations, sequential accumulation of other genetic events is involved in the development and progression of gastrointestinal stromal tumors (GISTs). Until recently, the significance of these other alterations has not been thoroughly investigated. We report the first study that integrates gene expression profiling and high-resolution genomic copy number analyses in GIST. Fresh tissue specimens from 25 patients with GIST were collected, and gene expression profiling and high-resolution genomic copy number analyses were performed, using Affymetrix U133Plus and SNP array 6.0. We found that all 21 mutant GIST patients showed both macroscopic cytogenetic alterations and cryptic microdeletions or amplifications, whereas 75% (three of four) of wild-type patients with GIST did not show genomic imbalances. The most frequently observed chromosomal alterations in patients with mutant GIST included 14q complete or partial deletion (17 of 25), 1p deletion (14 of 25) and 22q deletion (10 of 25). Genetic targets of the chromosomal aberrations were selected by integrated analysis of copy number and gene expression data. We detected the involvement of known oncogenes and tumor suppressors including KRAS in chr 12p amplification and KIF1B, PPM1A, NF2 in chr 1p, 14q and 22p deletions, respectively. The genomic segment most frequently altered in mutated samples was the 14q23.1 region, which contains potentially novel tumor suppressors, including DAAM1, RTN1 and DACT1. siRNA-mediated RTN1 downregulation showed evidence for the potential role in GIST pathogenesis. The combination of gene expression profiling and high-resolution genomic copy number analysis offers a detailed molecular portrait of GISTs, providing an essential comprehensive knowledge necessary to guide the discovery of novel target genes involved in tumor development and progression.

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“…We note that closeness to the observed data is modeled by a quadratic term, whereas the prior assumptions are encoded in 1 -terms; thus the optimization problem is related to the LASSO (least absolute shrinkage and selection operator; Tibshirani (1996); Tibshirani and Wang (2007)). The main difference to the standard LASSO approaches is that we have several 1 terms with different weights in the objective function.…”

Section: Assumptionsmentioning

confidence: 99%

“…Our approach Our work follows the Bayesian paradigm as well, but (a) with more detailed prior assumptions (i.e., we do not use the beta-binomial model), and (b) using approximations that cast the maximum a-posteriori-estimation computational as a strictly convex optimization problem related to LASSO (least absolute shrinkage and selection operator) approaches (Tibshirani, 1996;Tibshirani and Wang, 2007). We estimate the (unknown) true group-specific methylation rate at each CpG by using both the available (small sample and low coverage) data and certain smoothness assumptions.…”

Section: Introductionmentioning

confidence: 99%

An optimization approach to detect differentially methylated regions from Whole Genome Bisulfite Sequencing data

Hesse

Schröder

Rahmann

2015

Preprint

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Whole genome bisulfite sequencing (WGBS) is the current method of choice to obtain the methylation status of each single CpG dinucleotide in a genome. The typical analysis asks for regions that are differentially methylated (DMRs) between samples of two classes, such as different cell types. However, even with current low sequencing costs, many studies need to cope with few samples and medium coverage to stay within budget. We present a method to conservatively estimate the methylation difference between the two classes. Starting from a Bayesian paradigm, we formulate an optimization problem related to LASSO approaches. We present a dynamic programming approach to efficiently compute the optimal solution and its implementation diffmer. We discuss the dependency of the resulting DMRs on the free parameters of our approach and compare the results to those obtained by other DMR discovery tools (BSmooth and RADMeth). We showcase that our method discovers DMRs that are missed by the other tools.

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Spatial smoothing and hot spot detection for CGH data using the fused lasso

Cited by 307 publications

References 9 publications

Clinical application of next-generation sequencing in preimplantation genetic diagnosis cycles for Robertsonian and reciprocal translocations

Clinical application of next-generation sequencing in preimplantation genetic diagnosis cycles for Robertsonian and reciprocal translocations

A molecular portrait of gastrointestinal stromal tumors: an integrative analysis of gene expression profiling and high-resolution genomic copy number

An optimization approach to detect differentially methylated regions from Whole Genome Bisulfite Sequencing data

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