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mapping2015
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Leonardo Collado-Torres
February 23, 2015
Science
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mapping2015
Leonardo Collado-Torres
February 23, 2015
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Transcript
Does mapping simulated RNA-seq reads provide information? Leonardo Collado-Torres tweet:
@fellgernon blog: tinyurl.com/FellBit
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
https://github.com/alyssafrazee/polyester_code/blob/master/polyester_manuscript.Rmd
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
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
• 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
Correlation
Correlation: summarize by sample
Correlation: summarize by gene
R^2
Scaling by max then RMSD
Scaling by max then RMSD
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ARIMA: predictor p-value
ARIMA: predictor p-value
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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