FastMap 2.0

FastMap 2.0: Fast Association Mapping in Heterozygous Populations

Daniel M. Gatti, Andrey A. Shabalin, Myroslav Sypa, Tieu-Chong Lam, Fred A. Wright, Andrew B. Nobel, and Ivan Rusyn

Abstract

Gene expression association mapping involves the calculation of millions of genotype to phenotype correlations, which requires considerable computational resources. We have developed FastMap 2.0, which has a user friendly graphical interface, to perform fast association mapping in heterozygous populations on a standard desktop computer.

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Download tutorial

Download user manual

Installation instructions

Source code

Sample data

Heterozygous data

Right Click the link to the Gene expression file and select "Save As" from the options.

Right Click the link to the SNP file and select "Save As" from the options.

Homozygous data

Right Click the link to the Gene expression file and select "Save As" from the options.

Right Click the link to the SNP file and select "Save As" from the options.

HAPMAP data

Right Click the link to the Gene expression file and select "Save As" from the options.

Right Click the link to the SNP files folder (archived, please unarchive in order to use) and select "Save As" from the options.

Transposed PLINK data

Right Click the link to the Gene expression file and select "Save As" from the options.

Right Click the link to the TFAM file and select "Save As" from the options.

Right Click the link to the TPED file and select "Save As" from the options.

FastMap: Fast eQTL mapping in homozygous populations

Daniel M. Gatti, Andrey A. Shabalin, Tieu-Chong Lam, Fred A. Wright, Ivan Rusyn and Andrew B. Nobel

Publication: FastMap: Fast eQTL mapping in homozygous populations. Bioinformatics 4: 482-489.

Abstract

Motivation: Gene expression Quantitative Trait Locus (eQTL) mapping measures the association between transcript expression and genotype in order to find genomic locations likely to regulate transcript expression. The availability of both gene expression and high-density genotype data has improved our ability to perform eQTL mapping in inbred mouse and other homozygous populations. However, existing eQTL mapping software does not scale well when the number of transcripts and markers are on the order of 105 and 105–106, respectively.

Results: We propose a new method, FastMap, for fast and efficient eQTL mapping in homozygous inbred populations with binary allele calls. FastMap exploits the discrete nature and structure of the measured single nucleotide polymorphisms (SNPs). In particular, SNPs are organized into a Hamming distance-based tree that minimizes the number of arithmetic operations required to calculate the association of a SNP by making use of the association of its parent SNP in the tree. FastMap's tree can be used to perform both single marker mapping and haplotype association mapping over an m-SNP window. These performance enhancements also permit permutation-based significance testing.

Supplementary information: Supplementary data are available at Bioinformatics online.