MpraObject: MpraObject

In YosefLab/MPRAnalyze: Statistical Analysis of MPRA data

Description

The main object MPRAnalyze works with, contains the input data, associated annotations, model parameters and analysis results.

Usage

MpraObject(
  dnaCounts,
  rnaCounts,
  dnaAnnot = NULL,
  rnaAnnot = NULL,
  colAnnot = NULL,
  controls = NA_integer_,
  rowAnnot = NULL,
  BPPARAM = NULL
)

## S4 method for signature 'matrix'
MpraObject(
  dnaCounts,
  rnaCounts,
  dnaAnnot = NULL,
  rnaAnnot = NULL,
  colAnnot = NULL,
  controls = NA_integer_,
  rowAnnot = NULL,
  BPPARAM = NULL
)

## S4 method for signature 'SummarizedExperiment'
MpraObject(
  dnaCounts,
  rnaCounts,
  dnaAnnot = NULL,
  rnaAnnot = NULL,
  colAnnot = NULL,
  controls = NA,
  rowAnnot = NULL,
  BPPARAM = NULL
)

dnaCounts(obj)

## S4 method for signature 'MpraObject'
dnaCounts(obj)

rnaCounts(obj)

## S4 method for signature 'MpraObject'
rnaCounts(obj)

dnaAnnot(obj)

## S4 method for signature 'MpraObject'
dnaAnnot(obj)

rnaAnnot(obj)

## S4 method for signature 'MpraObject'
rnaAnnot(obj)

rowAnnot(obj)

## S4 method for signature 'MpraObject'
rowAnnot(obj)

controls(obj)

## S4 method for signature 'MpraObject'
controls(obj)

dnaDepth(obj)

## S4 method for signature 'MpraObject'
dnaDepth(obj)

rnaDepth(obj)

## S4 method for signature 'MpraObject'
rnaDepth(obj)

model(obj)

## S4 method for signature 'MpraObject'
model(obj)

Arguments

dnaCounts	the DNA count matrix, or a SummarizedExperiment object containing the DNA Counts and column annotations for the DNA data. If the input is a SummarizedExperiment object, the dnaAnnot (or colAnnot) arguments will be ignored
rnaCounts	the RNA count matrix, or a SummarizedExperiment object containing the RNA Counts and column annotations for the RNA data. If the input is a SummarizedExperiment object, the rnaAnnot (or colAnnot) arguments will be ignored
dnaAnnot	data.frame with the DNA column (sample) annotations
rnaAnnot	data.frame with the RNA column (sample) annotations
colAnnot	if annotations for DNA and RNA are identical, they can be set at the same time using colAnnot instead of using both rnaAnnot and dnaAnnot
controls	IDs of the rows in the matrices that correspond to negative control enhancers. These are used to establish the null for quantification purposes, and to correct systemic bias in comparative analyses. Can be a character vectors (corresponding to rownames in the data matrices), logical or numeric indices.
rowAnnot	a data.frame with the row (candidate enhancer) annotations. The names must match the row names in the DNA and RNA count matrices.
BPPARAM	a parallelization backend using the BiocParallel package, see more details [here](http://bioconductor.org/packages/release/bioc/html/BiocParallel.html)
obj	The MpraObject to extract properties from

Value

an initialized MpraObject

Accessors

MpraObject properties can be accessed using accessor functions

dnaCounts

the DNA count matrix

rnaCounts

the RNA count matrix

dnaAnnot

data.frame with the DNA column (sample) annotations

ranAnnot

data.frame with the RNA column (sample) annotations

rowAnnot

data.frame with the row (candidate enhancers) annotations

model

the distributional model used. the Gamma-Poisson convolutional model is used by default. see setModel

dnaDepth

The library size correction factors computed for the DNA libraries. These are computed by the estimateDepthFactors function and can be set manually using the setDepthFactors function

rnaDepth

The library size correction factors computed for the RNA libraries These are computed by the estimateDepthFactors function and can be set manually using the setDepthFactors function

Examples

data <- simulateMPRA(tr = rep(2,10), da=c(rep(2,5), rep(2.5,5)), 
                     nbatch=2, nbc=20)
## use 3 of the non-active enhancers as controls
obj <- MpraObject(dnaCounts = data$obs.dna, 
                  rnaCounts = data$obs.rna, 
                  colAnnot = data$annot,
                  controls = as.integer(c(1,2,4)))
## alternatively, initialize the object with SummarizedExperiment objects:
## Not run: 
se.DNA <- SummarizedExperiment(list(data$obs.dna), colData=data$annot)
se.RNA <- SummarizedExperiment(list(data$obs.rna), colData=data$annot)
obj <- MpraObject(dnaCounts = se.DNA, rnaCounts = rna.se, 
                  controls = as.integer(c(1,2,4)))

## End(Not run)
dnaCounts <- dnaCounts(obj)
rnaCounts <- rnaCounts(obj)
dnaAnnot <- dnaAnnot(obj)
rnaAnnot <- rnaAnnot(obj)
controls <- controls(obj)
rowAnnot <- rowAnnot(obj) 
model <- model(obj)

obj <- estimateDepthFactors(obj, lib.factor=c("batch", "condition"))
dnaDepth <- dnaDepth(obj)
rnaDepth <- rnaDepth(obj)

YosefLab/MPRAnalyze documentation built on Nov. 14, 2020, 2:35 a.m.