This study evaluates the technical reproducibility of RNA-seq using the Illumina platform and compares it with gene expression arrays. The researchers sequenced liver and kidney RNA samples seven times and compared the results with Affymetrix array data. They found that Illumina sequencing data are highly reproducible with minimal technical variation, making a single sequencing run sufficient for many purposes. The information in a single Illumina sequencing lane is comparable to that in a single array for identifying differentially expressed genes, while allowing for additional analyses such as detecting low-expressed genes, alternative splice variants, and novel transcripts. A Poisson model was used to identify differentially expressed genes, which identified 30% more differentially expressed genes than array-based methods at the same false discovery rate. The study also demonstrated the potential of sequencing to identify alternative splice forms. The results showed that sequencing data are highly reproducible, with only a small proportion of genes showing clear deviations from the Poisson model. The study also found that sequencing data correlated well with array data, with a Spearman correlation of 0.73. The study concludes that Illumina sequencing is a promising technology for measuring mRNA expression and identifying differentially expressed genes, comparable and in some ways superior to existing array-based approaches. The study also highlights the potential of sequencing to detect novel exons and transcripts, and to identify alternative splice forms. The study suggests that sequencing-based approaches may be more effective than array-based approaches for certain types of gene expression studies. The study also notes that while sequencing data may have some systematic biases, these are largely consistent across lanes and runs. The study also found that sequencing data can be used to identify differentially expressed genes with high accuracy, and that the number of genes identified is comparable to that identified using three technical microarray replicates. The study concludes that Illumina sequencing is a promising technology for gene expression studies, and that it may become increasingly popular as sequencing costs decrease and data quality improves.This study evaluates the technical reproducibility of RNA-seq using the Illumina platform and compares it with gene expression arrays. The researchers sequenced liver and kidney RNA samples seven times and compared the results with Affymetrix array data. They found that Illumina sequencing data are highly reproducible with minimal technical variation, making a single sequencing run sufficient for many purposes. The information in a single Illumina sequencing lane is comparable to that in a single array for identifying differentially expressed genes, while allowing for additional analyses such as detecting low-expressed genes, alternative splice variants, and novel transcripts. A Poisson model was used to identify differentially expressed genes, which identified 30% more differentially expressed genes than array-based methods at the same false discovery rate. The study also demonstrated the potential of sequencing to identify alternative splice forms. The results showed that sequencing data are highly reproducible, with only a small proportion of genes showing clear deviations from the Poisson model. The study also found that sequencing data correlated well with array data, with a Spearman correlation of 0.73. The study concludes that Illumina sequencing is a promising technology for measuring mRNA expression and identifying differentially expressed genes, comparable and in some ways superior to existing array-based approaches. The study also highlights the potential of sequencing to detect novel exons and transcripts, and to identify alternative splice forms. The study suggests that sequencing-based approaches may be more effective than array-based approaches for certain types of gene expression studies. The study also notes that while sequencing data may have some systematic biases, these are largely consistent across lanes and runs. The study also found that sequencing data can be used to identify differentially expressed genes with high accuracy, and that the number of genes identified is comparable to that identified using three technical microarray replicates. The study concludes that Illumina sequencing is a promising technology for gene expression studies, and that it may become increasingly popular as sequencing costs decrease and data quality improves.