Short read quality assessment Martin Morgan 1 June 20-23, 2011 1 - PowerPoint PPT Presentation

Short read quality assessment Martin Morgan 1 June 20-23, 2011 1 mtmorgan@fhcrc.org

Why sequence? e.g., RNA-seq ◮ Expression in novel (un-annotated) regions ◮ Exon junction / RNA editing insights ◮ Allele-specific / transcript isoform quantification ◮ Non-model organisms ◮ Greater dynamic range and sensitivity? Lessons from microarrays ◮ Initially: variability between manufactures, technologies, labs ◮ MAQC: quality control standards and analysis protocols

Example work flow – [4] Sample ◮ Purify poly(A)+ RNA with oligo(dT) magnetic beads ◮ cDNA synthesis primed with random hexamers Microarray ◮ Dye-swap, hybridization, florescence, analysis RNA-seq ◮ Fragment and size-select ◮ Illumina adapter ligation

Example work flow – [4] Sample ◮ Purify poly(A)+ RNA with oligo(dT) magnetic beads ◮ cDNA synthesis primed with random hexamers Microarray ◮ Dye-swap, hybridization, florescence, analysis RNA-seq ◮ Fragment and size-select ◮ Illumina adapter ligation

Example work flow – [4] Sample ◮ Purify poly(A)+ RNA with oligo(dT) magnetic beads ◮ cDNA synthesis primed with random hexamers Microarray ◮ Dye-swap, hybridization, florescence, analysis RNA-seq ◮ Fragment and size-select ◮ Illumina adapter ligation

Key issues ◮ Experimental design [1] ◮ Replication ◮ Randomization and blocking, e.g., batch effects ◮ Depth of coverage ◮ Statistical power ◮ Library complexity ◮ Coverage heterogeneity ◮ Estimation biases ◮ Legitimate comparison ◮ Sequencing uncertainty [2]

Key issues ◮ Experimental design [1] ◮ Replication ◮ Randomization and blocking, e.g., batch effects ◮ Depth of coverage ◮ Statistical power ◮ Library complexity ROC simulation ◮ Coverage heterogeneity ◮ Replication (red vs. blue) ◮ Estimation biases ◮ Randomization and blocking ◮ Legitimate comparison (solid vs. dot) ◮ Sequencing uncertainty [2]

Key issues 0 1 2 3 4 0 1 2 3 4 5 6 7 8 ◮ Experimental design [1] 1.0 0.8 ◮ Replication 0.6 ◮ Randomization and 0.4 Cumulative proportion of reads blocking, e.g., batch 0.2 effects 0.0 1 2 3 4 1.0 ◮ Depth of coverage 0.8 ◮ Statistical power 0.6 ◮ Library complexity 0.4 0.2 ◮ Coverage heterogeneity 0.0 ◮ Estimation biases 0 1 2 3 4 0 1 2 3 4 Number of occurrences of each read (log 10 ) ◮ Legitimate comparison ◮ Sequencing uncertainty [2] Cumulative proportion of reads occuring 0, 1, . . . times

Key issues ◮ Experimental design [1] 1.0 Cummulative proportion ◮ Replication 0.8 ◮ Randomization and blocking, e.g., batch 0.6 effects 0.4 ◮ Depth of coverage ◮ Statistical power 0.2 ◮ Library complexity 0.0 ◮ Coverage heterogeneity 2.0 2.2 2.4 2.6 ◮ Estimation biases Copies per read (log 10 ) ◮ Legitimate comparison ◮ Sequencing uncertainty [2] Actual versus uniform φ X 174 coverage

Key issues ◮ Experimental design [1] ◮ Replication ◮ Randomization and blocking, e.g., batch effects ◮ Depth of coverage ◮ Statistical power ◮ Library complexity ◮ Coverage heterogeneity ◮ Estimation biases ◮ Legitimate comparison Read count increases with gene length ◮ Sequencing uncertainty [2]

Key issues ◮ Experimental design [1] ◮ Replication ◮ Randomization and blocking, e.g., batch effects ◮ Depth of coverage ◮ Statistical power ◮ Library complexity ◮ Coverage heterogeneity ◮ Estimation biases Reads, stratified by cycle, ◮ Legitimate comparison supporting a spurious SNP call in ◮ Sequencing uncertainty [2] φ X 174

Case study Subset of Brooks et al. [3] ◮ RNAi and mRNA-seq to identify pasilla-regulated alternative splicing ◮ Purified polyA, random hexamer primed ◮ Single- and paired end sequences ◮ Alignment to reference genome and curated splic junctions

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