Your browser doesn't support javascript.
loading
CoMut: visualizing integrated molecular information with comutation plots.
Crowdis, Jett; He, Meng Xiao; Reardon, Brendan; Van Allen, Eliezer M.
Afiliação
  • Crowdis J; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
  • He MX; Cancer Program, Broad Institute of Harvard and MIT, Cambridge, 02142 MA, USA.
  • Reardon B; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
  • Van Allen EM; Cancer Program, Broad Institute of Harvard and MIT, Cambridge, 02142 MA, USA.
Bioinformatics ; 36(15): 4348-4349, 2020 08 01.
Article em En | MEDLINE | ID: mdl-32502231
ABSTRACT
MOTIVATION Large-scale sequencing studies have created a need to succinctly visualize genomic characteristics of patient cohorts linked to widely variable phenotypic information. This is often done by visualizing the co-occurrence of variants with comutation plots. Current tools lack the ability to create highly customizable and publication quality comutation plots from arbitrary user data.

RESULTS:

We developed CoMut, a stand-alone, object-oriented Python package that creates comutation plots from arbitrary input data, including categorical data, continuous data, bar graphs, side bar graphs and data that describes relationships between samples. AVAILABILITY AND IMPLEMENTATION The CoMut package is open source and is available at https//github.com/vanallenlab/comut under the MIT License, along with documentation and examples. A no installation, easy-to-use implementation is available on Google Colab (see GitHub).
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Genômica Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Genômica Idioma: En Ano de publicação: 2020 Tipo de documento: Article