Precision-mapping and statistical validation of quantitative trait loci by machine learning

Justin Bedo¹^,3 , Peter Wenzl² , Adam Kowalczyk¹ and Andrzej Kilian²

¹Life Sciences, NICTA and Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia

²Diversity Arrays P/L, 1 Wilf Crane Cr. (Yarralumla), Canberra, ACT 2600, Australia

³The Research School of Information Sciences and Engineering, The Australian National University, Canberra, Australia

author email corresponding author email

BMC Genetics 2008, 9:35doi:10.1186/1471-2156-9-35


Published:	2 May 2008

Additional files

Additional file 1:

QTL detected with different algorithms (p < 0.05). PDF file containing a list of QTL identified for each combination of QTL-detection method (SML, MR, and CIM) and trait (α-amylase, diastatic power, heading date, plant height, lodging, malt extract, pubescent leaves, grain protein content, and yield).

Format: PDF Size: 77KB Download file

This file can be viewed with: Adobe Acrobat Reader

Additional file 2:

Unsmoothed results obtained in the analysis of a synthetic 'chromosome'. PowerPoint file with two plots containing the unsmoothed results from which the plots in Figure 9 were generated.

Format: PPT Size: 387KB Download file

This file can be viewed with: Microsoft PowerPoint Viewer

Additional file 3:

Genotypic data used for QTL analysis. Excel file containing 0/1 allele calls and A/B genotypes (segregation data) for both the 'raw' and the 'curated' Steptoe/Morex genetic map.

Format: XLS Size: 1.8MB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional file 4:

Phenotypic data used for QTL analysis. Excel file containing phenotypic data for the nine traits investigated in this study (α-amylase, diastatic power, heading date, plant height, lodging, malt extract, pubescent leaves, grain protein content, and yield). The data is from up to 16 different environments and includes averages across standardised environments (see section entitled 'Pre-processing of phenotypic data' in Methods).

Format: XLS Size: 136KB Download file

This file can be viewed with: Microsoft Excel Viewer