A Brief Overview of Multivariate Data Analysis in Biological Sciences

Abstract

Microarrays have been used to quantify the mRNA expression for different genes in different living beings. Recently RNA-seq be the major techniques for genome-wide assessment of transcriptomics data as it provides more accurate estimates of transcriptomics data than microarrays for either known or unknown transcripts in a larger dynamic range. To analyse the high-throughputs transcriptomics data as well as proteomics and metabolomics data, it’s very essential to know the proper statistical tools and software that are suitable for the respective design and data. Therefore, in this review an attempt has been made to discuss briefly some useful multivariate techniques to analyze and integrate multi-groups datasets as well as to choose appropriate models based on design and data with short description.