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Does mapping simulated RNA-seq reads provide information? Leonardo Collado-Torres tweet: @fellgernon blog: tinyurl.com/FellBit

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Previously • Choose 10 genes with FPKM > 20 • cufflinks: estimate isoform FPKM from 7 Geuvadis samples • polyester: simulate with uniform & rnaf models • Map with TopHat • View coverage https://github.com/alyssafrazee/polyester_code/blob/master/polyester_manuscript.Rmd

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https://github.com/alyssafrazee/polyester_code/blob/master/polyester_manuscript.Rmd

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Goals • Reproduce • Similar behavior in other genes/samples? • Do simulated reads predict observed data? Get a measure by gene • Even more than by chance?

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Original

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Reproduced

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Measures by gene: using single bp exon • Correlation (R^2) • RMSD: scaling by max first • ARIMA: forecast models – Auto ARIMA on obs – Fit again using simulated data as predictor – P-value for predictor and estimated coef • Chance: – Neg. binomial size 1 and 6 – Compare replicates of simulated data

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• d: default params, 2 reps (2x) • r: using rnaf bias, 2x • b1: neg. binomial with size = 1, 2x • b6: neg. binom. size = 6, 2x • d1-d2: using d1 as “obs” – Same for r1-r2, b1a-b1b, b6a-b6b

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Correlation

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Correlation: summarize by sample

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Correlation: summarize by gene

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R^2

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Scaling by max then RMSD

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Scaling by max then RMSD

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ARIMA: predictor p-value

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ARIMA: predictor p-value

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ARIMA: predictor coefficient

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Code • https://github.com/alyssafrazee/polyest er_code/blob/master/polyester_manuscri pt.Rmd • https://github.com/lcolladotor/mapBias (private for now)

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