A New Human Transcriptome Array for Clinical Research

We have designed a comprehensive high-density oligonucleotide array of human transcriptome (GG-H1 array) for high-throughput, multiplexed, and cost effective analyses of patient samples for the biological basis of diseases. This array enables comprehensive examination of multiple mechanisms human cells use to regulate transcriptome in response to diseases including improved analysis of gene expression with completely updated gene annotations and carefully redesigned probes, genome-wide quantitation of gene isoforms and identification of alternative splicing, coding and UTR SNP detection and allele specific expression analysis, examination of non-coding transcription and antisense expression, and the analyses of small RNAs.

Since many of the components on the new array have not been systematically studied in human before, computational methods are not yet available. In this project, therefore, we propose to develop statistical methods and bioinformatic tools for the analyses of the new information, and conduct testing experiments in selected clinical problems to evaluate the contributions of different parts of transcriptome regulation in human health and disease.


  • Further developments of high density microarray and next-generation sequencing technologies will make increasing impact on medical research.
  • This project will develop computational methods and proof-of-principle biomedical studies using the new 6.9 million feature human transcriptome array.
  • The analysis results of proposed array studies and accompanied sequencing runs will also be the basis for further improving the design of the array. At a current cost of $400 per sample (including array and processing) and a throughput of hundreds samples per week in an average core, the array provides a high-throughput and cost effective method for clinical research.


  • Array design
  • Sample processing protocols
  • Array processing, analysis, and QC pipeline
  • Testing experiments on mRNA and small RNA
  • Array annotation database
  • Software for gene and alternative splicing analysis (JETTA) and visualization
  • Using exon and junction probes in alternative splicing and isoform analysis
  • Study of unannotated transcribed units


Wenzhong Xiao 
Weihong Xu
Junhee Seok
Michael Mindrinos
Erik Miller
Julie Wilhelmy
Ronald W. Davis

Dept. of Statistics, Stanford University

Yi Xing
Hui Jiang
Karen Kapur
Dave Hiller
Zhegqing Ouyang
Wing Wong

Depts. of Pathology & Genetics, Stanford University

Weng-Onn Lui
Andrew Z. Fire


Anyhony Schweitzer
Tyson Clark
Malek Faham
John Blume