Program for Mapping Expression Quantitative Trait Loci (eQTL) and Data Archives of eQTL in Global Populations

 

 

Hsin-Chou Yang1,2, Chien-Wei Lin1, Chia-Wei Chen1, and James J Chen3

 

1Institute of Statistical Science, Academia Sinica, Taipei, Taiwan

2School of Public Health, National Defense Medical Center, Taipei, Taiwan

3School National Center for Toxicological Research, Food and Drug Administration, Little Rock, Arkansas, USA

 

 

 

Introduction:

In our eQTL mapping study, transcript expression levels of genes (transcript-level gene; T-gene) are correlated with single nucleotide polymorphisms (SNPs) on a gene (sequence-level gene; S-gene) via a method of gene-based partial least squares (PLS). This website provides two useful tools: (1) a SAS macro for eQTL mapping using a PLS method and an illustrative example, and (2) three eQTL data archives including gene-based eQTL and SNP-based eQTL for four HapMap II populations (YRI, CEU, CHB, and JPT).

 

Download of a SAS macro and an illustrative example:

Program: [SAS macro]

Example: [gene expression file and genotype file]

 

Data archives:

Contents of the three data files are illustrated as follows:

·       Archive 1: This Excel file provides a summary table of the regulatory S-genes (g-eQTL) for each T-gene from our gene-based PLS analysis by populations. [File, Description]

·       Archive 2: This Excel file provides a summary table of T-genes regulated by each S-gene from our gene-based PLS analysis by populations. [File, Description]

·       Archive 3: This Excel file provides a summary table of T-genes regulated by each eQTL from our SNP-based PLS analysis by populations. [File, Description]

 

Citation:

Hsin-Chou Yang, Chien-Wei Lin, Chia-Wei Chen, and James J Chen (2014/04). Applying Genome-Wide Gene-Based Expression Quantitative Trait Loci Mapping to Study Population Ancestry and Pharmacogenetics. BMC Genomics 15, 319. (http://www.biomedcentral.com/1471-2164/15/319)

 

Contact:

Please kindly acknowledge if you have downloaded the data. We will inform you the update of our databases. Any questions, comments and suggestions on our databases are welcome. Please send your feedback to hsinchou@stat.sinica.edu.tw.