pyGenomeTracks: reproducible plots for multivariate genomic datasets  | Zendy

Lucille LopezDelisle | Zendy; Leily Rabbani | Zendy; Joachim Wolff | Zendy; Vivek Bhardwaj | Zendy; Rolf Backofen | Zendy; Björn Grüning | Zendy; Fidel Ramírez | Zendy; Thomas Manke | Zendy

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pyGenomeTracks: reproducible plots for multivariate genomic datasets

Author(s) -

Lucille LopezDelisle,

Leily Rabbani,

Joachim Wolff,

Vivek Bhardwaj,

Rolf Backofen,

Björn Grüning,

Fidel Ramírez,

Thomas Manke

Publication year - 2020

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa692

Subject(s) - computer science , modular design , graphical user interface , software , interface (matter) , multivariate statistics , source code , line (geometry) , data mining , information retrieval , programming language , machine learning , operating system , geometry , mathematics , bubble , maximum bubble pressure method

Generating publication ready plots to display multiple genomic tracks can pose a serious challenge. Making desirable and accurate figures requires considerable effort. This is usually done by hand or using a vector graphic software.

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