@article{1406,
  author = {Weihong Xu and Junhee Seok and Michael Mindrinos and Anthony Schweitzer and Hui Jiang and Julie Wilhelmy and Tyson Clark and Karen Kapur and Yi Xing and Malek Faham and John Storey and Lyle Moldawer and Ronald Maier V and Ronald Tompkins and Wing Wong and Ronald Davis and Wenzhong Xiao and Inflammation Program},
  title = {Human transcriptome array for high-throughput clinical studies.},
  abstract = {<p>A 6.9 million-feature oligonucleotide array of the human transcriptome [Glue Grant human transcriptome (GG-H array)] has been developed for high-throughput and cost-effective analyses in clinical studies. This array allows comprehensive examination of gene expression and genome-wide identification of alternative splicing as well as detection of coding SNPs and noncoding transcripts. The performance of the array was examined and compared with mRNA sequencing (RNA-Seq) results over multiple independent replicates of liver and muscle samples. Compared with RNA-Seq of 46 million uniquely mappable reads per replicate, the GG-H array is highly reproducible in estimating gene and exon abundance. Although both platforms detect similar expression changes at the gene level, the GG-H array is more sensitive at the exon level. Deeper sequencing is required to adequately cover low-abundance transcripts. The array has been implemented in a multicenter clinical program and has generated high-quality, reproducible data. Considering the clinical trial requirements of cost, sample availability, and throughput, the GG-H array has a wide range of applications. An emerging approach for large-scale clinical genomic studies is to first use RNA-Seq to the sufficient depth for the discovery of transcriptome elements relevant to the disease process followed by high-throughput and reliable screening of these elements on thousands of patient samples using custom-designed arrays.</p>
},
  year = {2011},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  volume = {108},
  pages = {3707-12},
  month = {03/2011},
  issn = {1091-6490},
  doi = {10.1073/pnas.1019753108},
  language = {eng},
}