Package 'InTAD'

Preparation for correlation analysis

Description

This function combines signals and genes in inside of Topologically Associated Domains (TADs)

Usage

combineInTAD(object, tadGR, selMaxTadOvlp = TRUE, closestGene = TRUE)

Arguments

object	InTADSig object
tadGR	TAD genomic regions
selMaxTadOvlp	If a signal overlaps 2 or more TADs by default only single TAD with max overlap is selected.All overlaps can be included by deactivating this option.
closestGene	By default closest to TAD genes are selected based on TSS location. Deactivate this option to use genes only lying within TAD.

Details

Each signal is checked if it is lying inside of TAD. Signals out of TADs are ignored. The genomic regions reprenting gene coordiantes are converted to TSS. By default, the closest genes are assigned belonging to TAD. If this option deactivated, only those lying with TAD are collected. Result is a list of signals connected to tables with gene details.

Value

Updated InTADSig object containing genes connected to eash signal

Examples

# create sigInTAD object
inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
# combine signals and genes in TAD
inTadSig <- combineInTAD(inTadSig, tadGR)

---

Preparation for correlation analysis via loops

Description

This function combines signals and genes based on the usage of loops obtained from HiC data analysis

Usage

combineWithLoops(object, loopsInitDf, fragmentLength = 0, tssWidth = 2000,
  extSize = 0)

Arguments

object	InTADSig object
loopsInitDf	Data frame with loops. By default 6-column format (chr1,start1,end1,chr2,start2,pos2) is expected.
fragmentLength	In case the input format is 4-column (chr1,middlePos1, chr2, middlePos2) fragment length should be provided to extend the corresponding loci for loop start and end positions.
tssWidth	The transcription start site width is used to control overlaps with loop anchor. Default is 2000 base pairs.
extSize	The loop endings can be extended upstream and downstream with provided corresponding increase size in base pairs.

Details

The expected input is the loops data.frame applied to find connections of signals to genes. This data.frame could be in two formats: either (chr1,start1,end1,chr2,start2,end2) or (chr1,middlePos1,chr2,middlePos2) with fragment size.

Value

Updated InTADSig object containing genes connected to signals via loops

---

Enhancer signals subset detected from medulloblatoma samples

Description

This data.frame contains 65 selected in chr15 normalized enhancers signals subset from 25 medulloblastoma samples.

Usage

enhSel

Format

a data.frame instance

Value

NULL, but makes available the dataframe

---

Genomic coordiantes of enhancer signals subet

Description

This GRanges object contains the coordinates of 65 medulloblastoma enhancer signals in chr15 target region

Usage

enhSelGR

Format

a GRanges object

Value

NULL, but makes available the dataset

---

Gene expression counts table

Description

This funcion returns gene expression counts table

Usage

## S4 method for signature 'InTADSig'
exprs(object)

Arguments

object

InTADSig object with signals and genes

Value

Gene expression table

Examples

inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
head(exprs(inTadSig))

---

Function to filter gene expression

Description

This function performs filtering of gene expression counts based on various parameters

Usage

filterGeneExpr(obj, cutVal = 0, geneType = NA, checkExprDistr = FALSE,
  plotExprDistr = FALSE)

Arguments

obj	InTADSig object
cutVal	Exclude genes that have max expression less or equal to this value in all samples. Default: 0
geneType	Type of gene to select for filtering i.e. "protein_coding". Default:NA
checkExprDistr	Adjust cutVal based on gene expression distribution
plotExprDistr	Perform visualziation of the distribution

Details

The function allows to stabilize the functional activity of the genes. By default all not expressed genes are filtered. It is also possible to set type of gene to take into account i.e. "protein_coding" only. This option requires additional metadata column "transcript_type". Also, special filtering option based on mclust library allows to analyze distribution of counts and adjust the cut value to exclude low expressed genes.

Value

InTADSig object with filtered counts table

Examples

## perform analysis on test data
inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
## default filtering
inTadSig <- filterGeneExpr(inTadSig)
## filter based on gene type
inTadSig <- filterGeneExpr(inTadSig, geneType = "protein_coding")

---

Function to perfrom correlation analysis via loops.

Description

This function combines genes and signals using obtained loop connections.

Usage

findCorFromLoops(object, method = "pearson", adj.pval = FALSE)

Arguments

object	InTADSig object with signals and genes combined via loops
method	Correlation method: "pearson" (default), "kendall", "spearman"
adj.pval	Perform p-value adjsutment and include q-values in result

Value

A table with correlation values for signal-gene pairs including correlation p-value and euclidian distance.

---

Function to perfrom correlation analysis in TADs

Description

This function combines genes and signals in inside of TADs

Usage

findCorrelation(object, method = "pearson", adj.pval = FALSE,
  plot.proportions = FALSE)

Arguments

object	InTADSig object with signals and genes combined in TADS
method	Correlation method: "pearson" (default), "kendall", "spearman"
adj.pval	Perform p-value adjsutment and include q-values in result
plot.proportions	Plot proportions of signals and genes in correlation

Value

A table with correlation values for signal-gene pairs including correlation p-value, euclidian distance and rank.

Examples

## perform analysis on test data
inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
inTadSig <- filterGeneExpr(inTadSig, geneType = "protein_coding")
inTadSig <- combineInTAD(inTadSig, tadGR)
corData <- findCorrelation(inTadSig, method="pearson")

---

Preparation for correlation analysis for a signal

Description

This function collects all genes for signal genomic region inside of Topologically Associated Domains (TADs)

Usage

fnSE(id, sigList, tadGR, tss, pickMaxOvlp, nearestTad)

Arguments

id	Id of signal from the list
sigList	List of signal GRs and their names
tadGR	TAD genomic regions
tss	Gene transcription start sites
pickMaxOvlp	Use TAD with max overlap
nearestTad	The table listing TADs nearest to each TSS #'

Details

The signal is checked if it is lying inside of TAD. Then all genes in this TAD are collected.

Value

Data.frame containing genes connected to signal

---

Gene coords GRanges

Description

This funcion returns the gene GRanges

Usage

geneCoords(object)

## S4 method for signature 'InTADSig'
geneCoords(object)

Arguments

object

InTADSig object with signals and genes

Value

Gene GRanges

Examples

inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
head(geneCoords(inTadSig))

---

Function to estimate gene expression

Description

This function uses mclust package to analyze gene expression distribution

Usage

get.enr.bg.normfit(x)

Arguments

x	Full gene expression vector

Details

The function adjust filtering cut value based on mclust library to exclude low expressed genes. It is a part of filtering procedure.

Value

Distribution properties: mean and std

---

The InTADSig Class

Description

The InTADSig object stores signals and gene expression data for the samples.

Details

It uses MultiAssayExperiment object to store information. Key slots to access are listed below.

Slots

sigMAE:

"MultiAssayExperiment", MultiAssayExperiment object containg signals and gene counts

signalConnections:

"list", The list of signals representing gene data frames in the same TAD

loopsDf:

"data.frame", The data.frame containing details of provided input loops

loopConnections:

"list", The list of connections between signals and genes via loops

ncore:

"numeric", Number of cores to use for parallel computing

#'

---

Load InTADSig object from text files

Description

The fuction loads the data tables to create an object that contains the signals and gene expression data.frames along with their genomic coordinates for further processing.

Usage

loadSigInTAD(signalsFile, countsFile, gtfFile, annFile = "",
  performLog = TRUE, logExprsOffset = 1, ncores = 1)

Arguments

signalsFile	Tab-seprated data table containg signals and their coordinates as row.names
countsFile	Tab-seprated counts table
gtfFile	GTF file containing all gene coordinates
annFile	Tab-delimited phenotype annotation of samples
performLog	Perform log2 convertion of expression values. Default: TRUE.
logExprsOffset	Offset x for log2 gene exrpression i.e. log2(value + x). Default: 1
ncores	Number of cores to use for parallel computing

Details

The function loads data from input files and creates object that stores matrices of signals and gene expression values along with coordiantes. The samples order and names of columns should match in both tables. It is expected that gene ids are applied in the validation of counts table.

Value

Novel InTADSig object

Examples

# create sigInTAD object
inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)

---

Data frame containing coordinates of loops

Description

The table contains genomic coordinates of chromatin loops in 6-column format derived from IMR90 cell line (focus : chr15)

Usage

loopsDfSel

Format

a data.frame object

Value

NULL, but makes available the dataset

---

Data frame containing information about samples

Description

The table includes additional informaiton about MB tumour samples (subgroup, gender, age, histology and M.Stage)

Usage

mbAnnData

Format

a data.frame object

Value

NULL, but makes available the dataset

---

Create InTADSig object

Description

The fuction generates an object that contains the signals and gene expression data.frames along with their genomic coordinates for further processing.

Usage

newSigInTAD(signalData = NULL, signalRegions = NULL, countsData = NULL,
  geneRegions = NULL, sampleInfo = NULL, performLog = TRUE,
  logExprsOffset = 1, ncores = 1)

Arguments

signalData	data frame containing signals
signalRegions	genomic regions of the signals
countsData	data matrix containing count expression values
geneRegions	gene coordiantes
sampleInfo	data frame containing additional sample info
performLog	Perform log2 convertion of expression values. Default: TRUE.
logExprsOffset	Offset x for log2 gene exrpression i.e. log2(value + x). Default: 1
ncores	Number of cores to use for parallel computing

Details

InTADSig object stores matrices of signals and gene expression values along with coordinates. The order of samples and names of columns should match in both datasets. For gene coordinates GRanges "gene_id" and "gene_name" are required in metadata. These are typical markers of genes in GTF anntotation format.

Value

Novel InTADSig object

Examples

## create sigInTAD object
inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)

---

Function to plot correlation across genome

Description

This function creates a plot of correlation strength in target genomic region from the result table. The X-coordinates represent signals, Y-coords represent genes, while each dot represents -log10(P-value) from correlation test. Additionallly all TAD boundaries can be visualized.

Usage

plotCorAcrossRef(obj, corRes, targetRegion, showCorVals = FALSE,
  symmetric = FALSE, tads = NULL)

Arguments

obj	InTADSig object with signals and genes combined in TADS
corRes	Correlation result table created by function findCorrelation()
targetRegion	Target genomic region visualise.
showCorVals	Use this option to visualize postive correlation values instead of correlation strength
symmetric	Activate mirrow symmetry for gene-signal connections
tads	TAD regions to visualize. By default only TADs persent in correlation result table are applied (NULL value).

Value

A ggplot object for visualization or customization.

Examples

inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
inTadSig <- combineInTAD(inTadSig, tadGR)
corData <- findCorrelation(inTadSig, method="pearson")
plotCorAcrossRef(inTadSig,corData,GRanges("chr15:25000000-28000000"))

---

Function to plot correlation

Description

This function creates a plot of selected pair signal-gene

Usage

plotCorrelation(obj, sId, geneName, xLabel = "Gene expression",
  yLabel = "Signal enrichment", colByPhenotype = "",
  corMethod = "pearson")

Arguments

obj	InTADSig object with signals and genes combined in TADS
sId	Signal id based on genomic cooridantes i.e. "chr:start-end"
geneName	Gene name to select. Based on "gene_name" attribute.
xLabel	The label to mark signal X-axis. Default: "Gene expression"
yLabel	The label to mark signal Y-axis. Default: "Signal enrichment"
colByPhenotype	The pheno data column i.e. tumour type that can be use for colour
corMethod	Correlation method. Default: Pearson

Value

A ggplot object for visualization or customization.

Examples

inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
inTadSig <- combineInTAD(inTadSig, tadGR)
plotCorrelation(inTadSig, "chr15:26372163-26398073", "GABRA5")

---

Gene expression subset from medulloblastoma samples

Description

This data.frame contains RPKM gene expression values from chr15 for subset from 25 medulluoblastoma samples.

Usage

rpkmCountsSel

Format

a data.frame instance

Value

NULL, but makes available the dataframe

---

Signal coords GRanges

Description

This funcion returns the signal GRanges

Usage

sigCoords(object)

## S4 method for signature 'InTADSig'
sigCoords(object)

Arguments

object

InTADSig object with signals and genes

Value

Signal GRanges

Examples

inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
head(sigCoords(inTadSig))

---

Signal values table

Description

This funcion returns the signal values table

Usage

signals(object)

## S4 method for signature 'InTADSig'
signals(object)

Arguments

object

InTADSig object with signals and genes

Value

Signals table

Examples

inTadSig <- newSigInTAD(enhSel, enhSelGR, rpkmCountsSel, txsSel)
head(signals(inTadSig))

---

Genomic coordiantes of topologically associated domains

Description

This GRanges object contains the coordinates of TADs revealed from IMR90 cell line (extracted from 0-indexed .bed file)

Usage

tadGR

Format

a GRanges object

Value

NULL, but makes available the dataset

---

Genomic coordiantes of genes subset

Description

This GRanges object contains the coordinates of genes subset from chr15

Usage

txsSel

Format

a GRanges object

Value

NULL, but makes avaialbe the dataset

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