Preprint

·2017 OPEN ACCESS

DepEst: an R package of important dependency estimators for gene network inference algorithms

Gökmen Altay YTU , Zeyneb Kurt YTU , Nejla Altay , Nizamettin Aydın YTU

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Gene network inference algorithms (GNI) are popular in bioinformatics area. In almost all GNI algorithms, the main process is to estimate the dependency (association) scores among the genes of the dataset. We present a bioinformatics tool, DepEst (Dependency Estimators), which is a powerful and flexible R package that includes 11 important dependency score estimators that can be used in almost all GNI Algorithms. DepEst is the first bioinformatics package that includes such a large number of estimators that runs both in parallel and serial. DepEst is currently available at https://github.com/altayg/Depest. Package access link, instructions, various workflows and example data sets are provided in the supplementary file.

Keywords

R package Estimator Dependency (UML) Inference Computer science Workflow Data mining Process (computing) Algorithm Statistics Artificial intelligence Mathematics Database Programming language

Subject Areas

Bioinformatics and Genomic Networks ·Molecular Biology ·Life Sciences
Gene expression and cancer classification ·Molecular Biology ·Life Sciences
Gene Regulatory Network Analysis ·Molecular Biology ·Life Sciences

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