http://www.iaeme.com/IJCET/index.asp 36 editor@iaeme.com International Journal of Computer Engineering & Technology (IJCET) Volume 8, Issue 6, Nov-Dec 2017, pp. 36–44, Article ID: IJCET_08_06_004 Available online at http://www.iaeme.com/ijcet/issues.asp?JType=IJCET&VType=8&IType=6 Journal Impact Factor (2016): 9.3590(Calculated by GISI) www.jifactor.com ISSN Print: 0976-6367 and ISSN Online: 0976–6375 © IAEME Publication A REVIEW OF GENE EXPRESSION ANALYSIS ON MICROARRAY DATASETS OF BREAST CELLS USING R LANGUAGE Chandra Sekhar K, K Satyanarayana Raju, M. Venkata Subba Rao, P Subba Raju Assistant Professor, Information Technology, SRKR Engineering College, Chinna Amiram Bhimavaram-534204, India ABSTRACT The capability of Affymetrix microarrays in genomics applications allows us to sense and investigate complex data. Using the obtainable techniques on Affymetrix microarray data we analyze diverse changes in genes of breast cancer cells in the effect of estrogen on them. By observance our spotlight on expression arrays, we also do processing like quality assessment and normalization. Hybridization computes of given trial data we explore the fundamental analysis issues for Affymetrix Genechips using which we assess gene expression using several perfect matches and mismatch probes determined in the different regions of the transcript. The Summarization and Normalization of the Affymetrix data are completed using Quantile Normalization and after that data is processed using the RMA. M-A plots which are a way of identifying the data whether it is normalized or not is applied. Affymetrix microarrays are a viable platform offered for wide sort of genomics applications resembling gene expression profiling, SNP genotyping, Chip-Chip analysis in diverse class. Affymetrix differs from other array technologies, because of the use of numerous short (25 mer) probes to measure hybridization. Key words: Gene Expression, Hybridization, Quantile Normalization, Nucleotides, Microarray, Estrogen. Cite this Article: Chandra Sekhar K, K Satyanarayana Raju, M. Venkata Subba Rao, P Subba Raju, A Review of Gene Expression Analysis On Microarray Datasets of Breast Cells Using R Language. International Journal of Computer Engineering & Technology, 8(6), 2017, pp. 36–44. http://www.iaeme.com/ijcet/issues.asp?JType=IJCET&VType=8&IType=6 1. INTRODUCTION Microarray Data Analysis is used for gene expression analysis [1]. Microarray technology [1] can be used to monitor genome-wide expression levels of genes in a given organism. A microarray is a glass slide resting on to which DNA molecules rigid in an orderly manner at specific locations are called Spots. All spot may hold a many million copies of indistinguishable DNA molecules that distinctively correspond to a gene. The DNA in a spot can either be