High-throughput sequencing is emerging as an attractive alternative to microar- rays for genotyping, analysis of methylation patterns, and identication of tran- scription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify dierentially expressed genes with existing array technologies. Bioconductor provides tools for the analysis and comprehension of higme. Developers for genomic based drug discoveries and its development play a huge role in high throughput ge- nomics Bioconductor is an open development project, meaning that all develop- ers from the scientic community are able to contribute software. Listed below are helpful links which will guide developers at dierent stages of their package. H-throughput genomic data.Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1211 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images .It is expected that emerging digital gene expression (DGE) technologies will overtake Microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcriptor exon are signicantly different across experimental conditions. Edger is a Bioconductor software package for examining dierential expression of replicated count data. An over dispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of over dispersion across transcripts, improving the reliability of Inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated[1]. The software may have other applications beyond sequencing data, such as proteome peptide count data.