Machine learning interface for RNA-Seq data


Zararsiz G., Goksuluk D., Korkmaz S., ELDEM V., Duru I. P., Unver T., ...More

Other, pp.1-10, 2014

  • Publication Type: Other Publication / Other
  • Publication Date: 2014
  • Page Numbers: pp.1-10
  • Istanbul University Affiliated: Yes

Abstract

MLSeq package provides several algorithms including support vector machines (SVM), bag- ging support vector machines (bagSVM), random forest (RF) and classification and regression trees (CART) to classify sequencing data. To achieve this, MLSeq package requires a count table, which contains the number of reads mapped to each transcript for each sample. This kind of count data can be obtained from RNA-Seq experiments, also from other sequencing experiments such as DNA or ChIP-sequencing. This vignette is presented to guide researchers how to use this package.