Tag: NGS data

PlasmidTron 0.4.1 – Assembling the cause of Phenotypes and Genotypes from NGS data

PlasmidTron 0.4.1

:: DESCRIPTION

PlasmidTron utilizes the phenotypic data normally available in bacterial population studies, such as antibiograms, virulence factors, or geographical information, to identify traits that are likely to be present on DNA that can randomly reassort across defined bacterial populations. It is also possible to use this methodology to associate unknown genes/sequences (e.g. plasmid backbones) with a specific molecular signature or marker (e.g. resistance gene presence or absence) using PlasmidTron. PlasmidTron uses a k-mer-based approach to identify reads associated with a phylogenetically unlinked phenotype.

::DEVELOPER

Pathogen Informatics, Wellcome Trust Sanger Institute

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

PlasmidTron

:: MORE INFORMATION

Citation

PlasmidTron: assembling the cause of phenotypes and genotypes from NGS data,
Andrew J Page, Alexander Wailan, Yan Shao, Kim Judge, Gordon Dougan, Elizabeth J. Klemm, Nicholas R. Thomson, Jacqueline A. Keane, 2018,
Microbial Genomics 4(3); doi: 10.1099/mgen.0.000164

CovEst 0.5.6 – Estimate coverage from NGS data without Assembly

CovEst 0.5.6

:: DESCRIPTION

CovEst estimates coverage and size of the genome from NGS data without assembly. It uses k-mer based statistics and works even with datasets with <1x coverage.

:: DEVELOPER

Computational Biology @ Comenius University in Bratislava

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

CovEst

:: 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.