Tag: CNV

BubbleTree 2.14.0 – CNV Analysis in groups of Tumor Samples

BubbleTree 2.14.0

:: DESCRIPTION

BubbleTree is a framework to characterize the tumor clonality using next generation sequencing (NGS) data.

::DEVELOPER

Wei Zhu <zhuw at medimmune.com>, Michael Kuziora <kuzioram at medimmune.com>, Todd Creasy <creasyt at medimmune.com>, Brandon Higgs <higgsb at medimmune.com>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux/ MacOsX
  • R/BioConductor

:: DOWNLOAD

 BubbleTree

:: MORE INFORMATION

Citation

BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality using next generation sequencing data.
Zhu W, Kuziora M, Creasy T, Lai Z, Morehouse C, Guo X, Sebastian Y, Shen D, Huang J, Dry JR, Xue F, Jiang L, Yao Y, Higgs BW.
Nucleic Acids Res. 2015 Nov 17. pii: gkv1102

cnv2wiggle – Convert CNV Details to wig and generate a BED file

cnv2wiggle

:: DESCRIPTION

The cnv2wiggle perl script will create a bed track for ploidy segments different from 2 and a gwiggle plot of the relative coverae. These files can be opened in IGV. This script doesn’t include hypervariable regions

::DEVELOPER

Complete Genomics, Inc.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ MacOsX
  • Perl

:: DOWNLOAD

 cnv2wiggle

:: MORE INFORMATION

CNViewer 2.1 – Analysis and Comparison of Copy Number Variation (CNV)

CNViewer 2.1

:: DESCRIPTION

CNViewer is a user-friendly tool for analysis and comparison of Copy Number Variation (CNV). It presents several functionalities such as add sensitive (usually clinical/phenotypic) data, export module, selection of genomic region of interest and supports three methods to input data.

::DEVELOPER

Cintia C. Palu

:: SCREENSHOTS

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 CNViewer

:: MORE INFORMATION

CNAseg 1.0 – Identify CNVs in cancer from NGS data

CNAseg 1.0

:: DESCRIPTION

CNAseg is a novel framework for the identification of CNA events that uses flowcell-to-flowcell variability to estimate the false positive rate and the depth of coverage to finalize copy number calls. HMMseg uses the Skellam distribution to compare read depth in tumour and control samples, which allows the use of smaller window sizes for copy number estimation and leads to greater sensitivity in pinpointing breakpoints for small CNAs.

::DEVELOPER

Sergii Ivakhno

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 CNAseg

:: MORE INFORMATION

Citation:

Bioinformatics. 2010 Dec 15;26(24):3051-8. Epub 2010 Oct 21.
CNAseg–a novel framework for identification of copy number changes in cancer from second-generation sequencing data.
Ivakhno S, Royce T, Cox AJ, Evers DJ, Cheetham RK, Tavaré S.

QuantiSNP 2.3 – Copy Number Variation (CNV) Detection

QuantiSNP 2.3

:: DESCRIPTION

QuantiSNP is an analytical tool for the analysis of copy number variation using whole genome SNP genotyping data. In its first implementation it was developed for data arising from Illumina® platforms

::DEVELOPER

QuantiSNP Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Perl
  • matlab

:: DOWNLOAD

 QuantiSNP

:: MORE INFORMATION

Reference:

Nucleic Acids Res. 2007;35(6):2013-25. Epub 2007 Mar 6.
QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data.
Colella S, Yau C, Taylor JM, Mirza G, Butler H, Clouston P, Bassett AS, Seller A, Holmes CC, Ragoussis J.

CNVEM 0.710 – Infer Carrier Status of CNVs in Large Samples from SNP Genotyping Data

CNVEM 0.710

:: DESCRIPTION

CNVEM is a Bayesian Expectation-Maximization algorithm that infers carrier status of CNVs in large samples from SNP genotyping data, such as are available in genome-wide association studies. Using Bayesian computations the program calculates the posterior probability for carrier status of known CNV in each individual of a sample by jointly analyzing genotype information and hybridization intensity. Signal intensity is modeled as a mixture of normal distributions, allowing for locus-specific and allele-specific distributions. Using an expectation maximization algorithm, these distributions are estimated and then used to infer the carrier status of each individual the boundaries of the CNV.

::DEVELOPER

Sebastian Zöllner @ the Center for Statistical Genetics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  Windows / MacOsX
  • C Complier

:: DOWNLOAD

 CNVEM

:: MORE INFORMATION

If you use CNVEM please e-mail szoellne@umich.edu or fill out the registration form.