Background: R is one of the renowned programming language which is an open source software developed by the scientific community to compute, analyze and visualize big data of any field including biomedical research for bioinformatics applications.Methods: Here, we outlined R allied packages and affiliated bioinformatics infrastructures e.g. Bioconductor and CRAN. Moreover, basic concepts of factor, vector, data matrix and whole transcriptome RNA-Seq data was analyzed and discussed. Particularly, differential expression workflow on simulated prostate cancer RNA-Seq data was performed through experimental design, data normalization, hypothesis testing and downstream investigations using EdgeR package. A few genes with ectopic expression were ...
Thesis (Master's)--University of Washington, 2016-06Kaposi’s Sarcoma-associated Herpesvirus (KSHV), ...
Abstract Background Gene set a...
International audienceFor facilitating the process of transcriptomics data, and to guarantee the rep...
Background: R is one of the renowned programming language which is an open source software developed...
Background: Gene set analysis (in a form of functionally related genes or pathways) has become the m...
Here we report a bio-statistical/informatics tool, ABioTrans, developed in R for gene expression ana...
The R programming language is approaching its 30th birthday, and in the last three decades it has ac...
SUMMARY: Bioclipse, a graphical workbench for the life sciences, provides functionality for managing...
Guide: a desktop application for analysing gene expression data Jarny Choi1,2 Background: Multiple c...
We describe a powerful and easy-to-use RNA-seq analysis pipeline that can be used for complete analy...
Abstract Background Microarray data are often used for patient classification and gene selection. An...
Standardizing and documenting computational analyses is necessary to ensure reproducible results. We...
Additional R script, source data files and figures associated with the paper. The following source ...
BACKGROUND: Multiplecompeting bioinformatics tools exist for next-generation sequencing data analysi...
<p>This book contains material from a workshop directed toward life scientists with little to no exp...
Thesis (Master's)--University of Washington, 2016-06Kaposi’s Sarcoma-associated Herpesvirus (KSHV), ...
Abstract Background Gene set a...
International audienceFor facilitating the process of transcriptomics data, and to guarantee the rep...
Background: R is one of the renowned programming language which is an open source software developed...
Background: Gene set analysis (in a form of functionally related genes or pathways) has become the m...
Here we report a bio-statistical/informatics tool, ABioTrans, developed in R for gene expression ana...
The R programming language is approaching its 30th birthday, and in the last three decades it has ac...
SUMMARY: Bioclipse, a graphical workbench for the life sciences, provides functionality for managing...
Guide: a desktop application for analysing gene expression data Jarny Choi1,2 Background: Multiple c...
We describe a powerful and easy-to-use RNA-seq analysis pipeline that can be used for complete analy...
Abstract Background Microarray data are often used for patient classification and gene selection. An...
Standardizing and documenting computational analyses is necessary to ensure reproducible results. We...
Additional R script, source data files and figures associated with the paper. The following source ...
BACKGROUND: Multiplecompeting bioinformatics tools exist for next-generation sequencing data analysi...
<p>This book contains material from a workshop directed toward life scientists with little to no exp...
Thesis (Master's)--University of Washington, 2016-06Kaposi’s Sarcoma-associated Herpesvirus (KSHV), ...
Abstract Background Gene set a...
International audienceFor facilitating the process of transcriptomics data, and to guarantee the rep...