Literature DB >> 19228802

Ultrasome: efficient aberration caller for copy number studies of ultra-high resolution.

Björn Nilsson1, Mikael Johansson, Fatima Al-Shahrour, Anne E Carpenter, Benjamin L Ebert.   

Abstract

MOTIVATION: Multimillion-probe microarrays allow detection of gains and losses of chromosomal material at unprecedented resolution. However, the data generated by these arrays are several-fold larger than data from earlier platforms, creating a need for efficient analysis tools that scale robustly with data size.
RESULTS: We developed a new aberration caller, Ultrasome, that delineates genomic changes-of-interest with dramatically improved efficiency. Ultrasome shows near-linear computational complexity and processes latest generation copy number arrays about 10,000 times faster than standard methods with preserved analytic accuracy.

Mesh:

Year:  2009        PMID: 19228802     DOI: 10.1093/bioinformatics/btp091

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

Review 1.  SNP array analysis in hematologic malignancies: avoiding false discoveries.

Authors:  Stefan Heinrichs; Cheng Li; A Thomas Look
Journal:  Blood       Date:  2010-03-19       Impact factor: 22.113

2.  A novel approach to DNA copy number data segmentation.

Authors:  Siling Wang; Yuhang Wang; Yang Xie; Guanghua Xiao
Journal:  J Bioinform Comput Biol       Date:  2011-02       Impact factor: 1.122

3.  Multisample aCGH data analysis via total variation and spectral regularization.

Authors:  Xiaowei Zhou; Can Yang; Xiang Wan; Hongyu Zhao; Weichuan Yu
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2013 Jan-Feb       Impact factor: 3.710

4.  CMDS: a population-based method for identifying recurrent DNA copy number aberrations in cancer from high-resolution data.

Authors:  Qunyuan Zhang; Li Ding; David E Larson; Daniel C Koboldt; Michael D McLellan; Ken Chen; Xiaoqi Shi; Aldi Kraja; Elaine R Mardis; Richard K Wilson; Ingrid B Borecki; Michael A Province
Journal:  Bioinformatics       Date:  2009-12-23       Impact factor: 6.937

5.  Predictive genes in adjacent normal tissue are preferentially altered by sCNV during tumorigenesis in liver cancer and may rate limiting.

Authors:  John R Lamb; Chunsheng Zhang; Tao Xie; Kai Wang; Bin Zhang; Ke Hao; Eugene Chudin; Hunter B Fraser; Joshua Millstein; Mark Ferguson; Christine Suver; Irena Ivanovska; Martin Scott; Ulrike Philippar; Dimple Bansal; Zhan Zhang; Julja Burchard; Ryan Smith; Danielle Greenawalt; Michele Cleary; Jonathan Derry; Andrey Loboda; James Watters; Ronnie T P Poon; Sheung T Fan; Chun Yeung; Nikki P Y Lee; Justin Guinney; Cliona Molony; Valur Emilsson; Carolyn Buser-Doepner; Jun Zhu; Stephen Friend; Mao Mao; Peter M Shaw; Hongyue Dai; John M Luk; Eric E Schadt
Journal:  PLoS One       Date:  2011-07-05       Impact factor: 3.240

6.  GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.

Authors:  Craig H Mermel; Steven E Schumacher; Barbara Hill; Matthew L Meyerson; Rameen Beroukhim; Gad Getz
Journal:  Genome Biol       Date:  2011-04-28       Impact factor: 13.583

7.  Parsimonious higher-order hidden Markov models for improved array-CGH analysis with applications to Arabidopsis thaliana.

Authors:  Michael Seifert; André Gohr; Marc Strickert; Ivo Grosse
Journal:  PLoS Comput Biol       Date:  2012-01-12       Impact factor: 4.475

8.  Deletion of ribosomal protein genes is a common vulnerability in human cancer, especially in concert with TP53 mutations.

Authors:  Ram Ajore; David Raiser; Marie McConkey; Magnus Jöud; Bernd Boidol; Brenton Mar; Gordon Saksena; David M Weinstock; Scott Armstrong; Steven R Ellis; Benjamin L Ebert; Björn Nilsson
Journal:  EMBO Mol Med       Date:  2017-04       Impact factor: 12.137

9.  VEGAWES: variational segmentation on whole exome sequencing for copy number detection.

Authors:  Samreen Anjum; Sandro Morganella; Fulvio D'Angelo; Antonio Iavarone; Michele Ceccarelli
Journal:  BMC Bioinformatics       Date:  2015-09-29       Impact factor: 3.169

10.  iSeg: an efficient algorithm for segmentation of genomic and epigenomic data.

Authors:  Senthil B Girimurugan; Yuhang Liu; Pei-Yau Lung; Daniel L Vera; Jonathan H Dennis; Hank W Bass; Jinfeng Zhang
Journal:  BMC Bioinformatics       Date:  2018-04-11       Impact factor: 3.169

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