mpra/README.md

In piquelab/QuASAR: Quantitative Allele Specific Analysis of Reads

QuASAR-MPRA: Accurate allele-specific analysis for massively parallel reporter assays

We have further developed our method for allele specific analysis QuASAR (quantitative allele-specific analysis of reads) (Harvey et al, 2015) to analyze allele specific signals in barcoded read counts data from MPRAs (preprint available in Kalita et al,2017). Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. Here, we demonstrate how to use QuASAR-MPRA to analyze the MPRA data by Tewhey et al,2016.

The current software is still in development and we will kindly appreciate any comments and bug reports. We assume that you already have installed the QuASAR library.

The mpra.R script contains the instructions to run the test. As an example we provide the HepG2 data for the forward strand in Tewhey et al,2016.[preprocessing.R] contains the steps to prepare this input file.

library(QuASAR)

## Loading the sample data:
HepG2 <- read.table("http://genome.grid.wayne.edu/quasar/samplempra/HepG2.mpra.txt",sep='\t',as.is=T,header=T)

## Fitting the QuASAR model:
HepG2.res <- fitQuasarMpra(HepG2$R,HepG2$A,HepG2$DNA_prop)

## Number of significant hits 10% FDR:
sum(HepG2.res$padj_quasar<0.1)

## QQ-plot: 
library(qqman)
qq(HepG2.res$pval3)

To fit the model we use the fitQuasarMpra function that needs three input vectors: - ref = number of RNA reads for the reference allele - alt = number of RNA reads for the alternate allele - prop = reference DNA proportion in the plasmid library

The returned data frame HepG2.res has the following fileds: - bin total coverage bin used - betas.beta.binom logit transfomation of the RNA allelic skew - betas_se standard error for the beta parameter estimate - betas_z zscore for betas.beta.binom -plogis(propr) - pval3 p.value - padj_quasar BH adjusted p.value

> head(HepG2.res)
                  bin betas.beta.binom  betas_se    betas_z       pval3 padj_quasar
1   (2.7e+03,3.3e+03]      -0.12164712 0.1409832 -0.2849424 0.774655868   1.0000000
2   (2.1e+03,2.7e+03]      -0.22659942 0.1630645 -1.0884486 0.273956397   1.0000000
3  (3.3e+03,3.96e+03]      -0.05672033 0.1282004 -0.6543586 0.513012947   1.0000000
4 (7.56e+03,2.22e+06]      -0.46219112 0.2338646 -0.1999347 0.838163133   1.0000000
5   (2.7e+03,3.3e+03]      -0.04063415 0.1403660  0.8889998 0.376112030   1.0000000
6             (0,859]      -1.17993132 0.5370852 -2.8797701 0.001298818   0.1951728

piquelab/QuASAR documentation built on May 25, 2019, 7:14 a.m.