Package 'gscreend'

Create PoolScreenExp Experiment

Description

Create PoolScreenExp Experiment

Usage

createPoolScreenExp(data)

Arguments

data	Input data object containing gRNA level data (SummarizedExperiment)

Value

object PoolScreenExp object

Examples

raw_counts <- read.table(
                        system.file('extdata', 'simulated_counts.txt',
                        package = 'gscreend'),
                        header=TRUE)

counts_matrix <- cbind(raw_counts$library0, raw_counts$R0_0, raw_counts$R1_0)

rowData <- data.frame(sgRNA_id = raw_counts$sgrna_id,
gene = raw_counts$Gene)

colData <- data.frame(samplename = c('library', 'R1', 'R2'),
timepoint = c('T0', 'T1', 'T1'))

library(SummarizedExperiment)
se <- SummarizedExperiment(assays=list(counts=counts_matrix),
rowData=rowData, colData=colData)

# create a PoolScreenExp experiment
pse <- createPoolScreenExp(se)

---

GeneData: set and retrieve GeneData of PoolScreenExp

Description

GeneData: set and retrieve GeneData of PoolScreenExp

Usage

GeneData(x)

Arguments

x	PoolScreenExp object

Value

Gene slot of the object

Examples

# import a PoolScreenExp object that has been generated using
# RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))

GeneData(pse_an)

---

Accessor function for the Gene slot of the PoolScreenExp class

Description

Accessor function for the Gene slot of the PoolScreenExp class

Usage

## S4 method for signature 'PoolScreenExp'
GeneData(x)

Arguments

x	PoolScreenExp object

Value

Gene slot of the object

Examples

# import a PoolScreenExp object that has been generated using
# RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))

GeneData(pse_an)

---

Plot model parameters from the fitting

Description

Plot model parameters from the fitting

Usage

plotModelParameters(object)

Arguments

object

PoolScreenExp object

Value

plot

Examples

# import a PoolScreenExp object that has been generated using
# RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))
plotModelParameters(pse_an)

---

Plot replicate correlation

Description

Plot replicate correlation

Usage

plotReplicateCorrelation(object, rep1 = "R1", rep2 = "R2")

Arguments

object	PoolScreenExp object
rep1	Name of replicate 1
rep2	Name of replicate 2

Value

replicate_plot

Examples

# import a PoolScreenExp object that has been generated using RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))
plotReplicateCorrelation(pse_an, rep1 = 'R1', rep2 = 'R2')

---

Class to store pooled CRISPR screening experiment

Description

The poolScreenExp class is an S4 class used to store sgRNA and gene related data as well as parameters necessary for statistical model.

Slots

sgRNAData

A SummarizedExperiment containing the data related to sgRNAs.

FittingIntervals

A vector defining the limits of the intervals used for fitting of null model.

LFCModelParameters

A vector of parameters estimated when fitting the null model.

GeneData

SummarizedExperiment containing the data related to genes.

FittingOptions

A named list with options for fitting: IntervalFraction - fraction of sgRNAs used in every fitting interval (default 0.1), alphaCutoff - alpha cutoff for alpha RRA algorithm (default: 0.05).

---

Extract a results table

Description

Extract a results table

Usage

ResultsTable(object, direction = "negative")

Arguments

object	PoolScreenExp object
direction	Whether the table should contain information on positive or negative fold changes ['negative'| 'positive']

Value

plot

Examples

# import a PoolScreenExp object that has been generated using
# RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))
ResultsTable(pse_an, direction = 'negative')

---

run gscreend

Description

run gscreend

Usage

RunGscreend(object, quant1 = 0.1, quant2 = 0.9, alphacutoff = 0.05)

Arguments

object	PoolScreenExp object
quant1	lower quantile for least quantile of squares regression (default: 0.1)
quant2	upper quantile for least quantile of squares regression (default: 0.9)
alphacutoff	alpha cutoff for alpha-RRA (default: 0.05)

Value

object

Examples

raw_counts <- read.table(
                        system.file('extdata', 'simulated_counts.txt',
                        package = 'gscreend'),
                        header=TRUE)

# Create the PoolScreenExp to be analyzed
counts_matrix <- cbind(raw_counts$library0, raw_counts$R0_0, raw_counts$R1_0)

rowData <- data.frame(sgRNA_id = raw_counts$sgrna_id,
gene = raw_counts$Gene)

colData <- data.frame(samplename = c('library', 'R1', 'R2'),
timepoint = c('T0', 'T1', 'T1'))

library(SummarizedExperiment)
se <- SummarizedExperiment(assays=list(counts=counts_matrix),
rowData=rowData, colData=colData)

pse <- createPoolScreenExp(se)

# Run Analysis
pse_an <- RunGscreend(pse)

---

sgRNAData: set and retrieve sgRNAData of PoolScreenExp

Description

sgRNAData: set and retrieve sgRNAData of PoolScreenExp

Usage

sgRNAData(x)

Arguments

x	PoolScreenExp object

Value

sgRNA slot of the object

Examples

# import a PoolScreenExp object that has been generated using
# RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))

sgRNAData(pse_an)

---

Accessor function for the sgRNA slot of the PoolScreenExp class

Description

Accessor function for the sgRNA slot of the PoolScreenExp class

Usage

## S4 method for signature 'PoolScreenExp'
sgRNAData(x)

Arguments

x	PoolScreenExp object

Value

sgRNA slot of the object

Examples

# import a PoolScreenExp object that has been generated using
# RunGscreend()
pse_an <- readRDS(
system.file('extdata', 'gscreend_analysed_experiment.RData',
package = 'gscreend'))

sgRNAData(pse_an)

---