Download Ch1 Intro

Ch1 Intro
• 1.1 Intro to QTL: general intro of QTL
– QTL/ plural form QTL’s
• 1.2 what’s the thesis about
– References problem
– The word “expression level” v.s. “matching”
• 1.3 relevant literature
– References problem again
– QTL mapping / graphing
Ch2 Data
• Bioconductor -> affymetrix
• 2.1 Data sources
– Database Origin: affymetrix “R” & “Original”
– Datasets: 2.1.2 QTL , 2.1.3 special gene
groups
• 2.2 Graphical overview
– “5000 interesting genes” needs an
explanation
• 2.3 modelling bp v.s. cm
Ch3 comparison
• 3.1 “breakdown”
– Gene’s way v.s. QTL’s way
• 3.2 analysis of overall table
– In gene’s way, odds ratio is to justify indep.
• 3.3 GLM (Modeling)
– 3.3.1 loglinear model:Model selection X2/G2
– 3.3.2 logit model: model selection
Ch3 Cont’d
• 3.4 GLMM
– Chromosome as a random effect (in the thesis)
– 3.4.1 Poisson regression from gene’s way
– 3.4.2 GLMM from QTL’s way (chromosome
not sig.)
• 3.5 discussion
– Summary of this chapter and stage
conclusion
Ch4 More comparison
• MBH genes
• 4.1 further stratified table
• 4.2 GLMM from gene’s way
– Model selection: almost every model is good
– Choose the simplest one
• 4.3 GLMM from QTL’s way
– Choose the parsimonious model
Ch5 simu.
• Randomly chosen genes from every chr.
• Count # rand. genes covered by pQTL
• Compare with # N-A genes covered by
pQTL
• Compare with # N-A genes covered by
bQTL
Ch6 con.
• Verify the association between pQTL and
N-A genes.