Experiment 14
• Aim:
• For each gene, compute the |Ng| test statistics measuring association
of SNPs in Ng with mean expression of gene g;
• Obtain a measure of statistical significance for each test statistic;
• Support adjustment and assessment of sensitivity analysis of
statistical tests (e.g., adjustment for batch effects, effects of filtering
on gene expression variation or SNP minor allele frequency);
• Provide the test results in a format for ready interrogation using
various types of search key;
• Support visualization of associations at various scales.
Experiment 14
1. Find RNA-seq data for a disease of your choice with N number of
patients
2. Write your detailed method to perform RNA expression analysis
(G) for each person in your RNA-Seq dataset.
3. Write your detailed method to perform variant call analysis (S) for
each subject in your RNA-Seq data set
4. Search for GGTools from Bioconductor
5. Use the manual and the system.file data to:
1. Compute score tests for all SNP cis to genes, with flexible
filtering (page 4)
2. Appraise the eQTL prediction models (page 6)
3. Collect genewise best scoring eQTL (page 9)
4. collect strongest trans SNP-gene associations in a buffer of
size K genes per SNP (page 12)
5. bind testing metadata to a best.cis.eQTLs result (page 14)
6. test for variant-expression associations in cis, using VCF (page
16)
7. Compute FDRs for various filterings/results (page 22)
6. Write up your codes from step 5 sections 1 – 7
7. Combine the methods in steps 1 – 3, and 6 into a workflow for A3
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