Introduction to the Data Set
- Leptinob/ob mice do now produce insulin and become obese due to overeating.
- This study crossed mice carrying the Leptinob/ob mutation in C57BL/6J and BTBR T+ tf/J.
- C57BL/6J mice are resistant to diabetes and BTBR mice are susceptible.
- By crossing these two strains, the authors aimed to identify genes which influence susceptibility to T2D.
Input File Format
- QTL mapping data consists of a set of tables of data: marker genotypes, phenotypes, marker maps, etc.
- These different tables are in separate comma-delimited (CSV) files.
- In each file, the first column is a set of IDs for the rows, and the first row is a set of IDs for the columns.
- In addition to primary data, a separate file with control parameters (or metadata) in either YAML or JSON format is required.
- Published and public data already formatted for QTL mapping are available on the web.
- These data can be used as a model for formatting your own QTL data.
Calculating Genotype Probabilities
- The first step in QTL analysis is to calculate genotype probabilities.
- Calculate genotype probabilities between genotyped markers with
calc_genoprob()
.
Performing a genome scan
- A qtl2 genome scan requires genotype probabilities and a phenotype matrix.
- The output from a genome scan contains a LOD score matrix, map positions, and phenotypes.
- LOD curve plots for a genome scan can be viewed with plot_scan1().
Calculating A Kinship Matrix
- Kinship matrices account for relationships among individuals.
- Kinship is calculated as the proportion of shared alleles between individuals.
- Kinship calculation is a precursor to a genome scan via a linear mixed model.
Performing a genome scan with a linear mixed model
- “To perform a genome scan with a linear mixed model, supply a kinship matrix.”
- “Different mapping and kinship calculation methods give different results.”
Performing a genome scan with binary traits
- “A genome scan for binary traits (0 and 1) requires special handling; scans for non-binary traits assume normal variation of the residuals.”
- “A genome scan for binary traits is performed with logistic regression.”
Performing a permutation test
- “A permutation test establishes the statistical significance of a genome scan.”
Finding QTL peaks
- LOD peaks and support intervals can be identified with find_peaks().
- The Bayesian Credible Interval estimates the width of the support interval around a QTL peak.
Estimating QTL effects
- “Estimated founder allele effects can be plotted from the mapping model coefficients.”
- “Additive and dominance effects can be plotted using contrasts.”
Integrating Gene Expression Data
- Use
.md
files for episodes when you want static content - Use
.Rmd
files for episodes when you need to generate output - Run
sandpaper::check_lesson()
to identify any issues with your lesson - Run
sandpaper::build_lesson()
to preview your lesson locally
QTL Mapping in Diversity Outbred Mice
- There are generally five steps to QTL mapping in DO mice:
- map the trait,
- perform permutations,
- find significant peaks,
- calculate founder allele effects at the QTL peak,
- perform association mapping to narrow the gene candidates.
- You may need to bring in outside resources to help narrow your candidate gene list.
- You will need the 10 GB SNP database to perform association mapping.