SNPs that affect expression (eSNPs)

SNPs that affect expression (eSNPs) - not in protein-coding regions
http://www.nature.com/ng/journal/v43/n7/full/ng.859.html
http://en.wikipedia.org/wiki/Single-nucleotide_polymorphism

regulatory SNPs (rSNPs), or QTL (quantitative trait loci)

PhenoGen
http://www.ncbi.nlm.nih.gov/pubmed/17760997
http://phenogen.ucdenver.edu/PhenoGen/index.jsp

Review
http://www.ncbi.nlm.nih.gov/pubmed/18668207

Plant system (might reference human databases)
http://www.ncbi.nlm.nih.gov/pubmed/20964836

GeneNetwork (webqtl)
http://www.genenetwork.org/webqtl/main.py
http://www.genenetwork.org/tutorial/WebQTLTour/

GeneNetwork is a group of linked data sets and tools used to study complex networks of genes, molecules, and higher order gene function and phenotypes. GeneNetwork combines more than 25 years of legacy data generated by hundreds of scientists together with sequence data (SNPs) and massive transcriptome data sets (expression genetic or eQTL data sets). The quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. GeneNetwork can be used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Most of these population data sets are linked with dense genetic maps (genotypes) that can be used to locate the genetic modifiers that cause differences in expression and phenotypes, including disease susceptibility.

Users are welcome to enter their own private data directly into GeneNetwork to exploit the full range of analytic tools and to map modulators in a powerful environment. This combination of data and fast analytic functions enable users to study relations between sequence variants, molecular networks, and function.