Package 'SingleMoleculeFootprinting'

Title: Analysis tools for Single Molecule Footprinting (SMF) data
Description: SingleMoleculeFootprinting provides functions to analyze Single Molecule Footprinting (SMF) data. Following the workflow exemplified in its vignette, the user will be able to perform basic data analysis of SMF data with minimal coding effort. Starting from an aligned bam file, we show how to perform quality controls over sequencing libraries, extract methylation information at the single molecule level accounting for the two possible kind of SMF experiments (single enzyme or double enzyme), classify single molecules based on their patterns of molecular occupancy, plot SMF information at a given genomic location.
Authors: Guido Barzaghi [aut, cre] , Arnaud Krebs [aut] , Mike Smith [ctb]
Maintainer: Guido Barzaghi <[email protected]>
License: GPL-3
Version: 2.1.0
Built: 2024-11-30 05:23:49 UTC
Source: https://github.com/bioc/SingleMoleculeFootprinting

Help Index


Convenience function to arrange a list of given TFBSs into clusters

Description

For each TFBS, the genomic neighborhood defined by max_cluster_width will be scanned for adjacent TFBSs. The hits will be filtered for min_intersite_distance where, in case of overlapping TFBSs, the second TFBS will be arbitrarily dropped. These TFBSs plus the central "anchoring" one will define a TFBS cluster. This approach implies that the same TFBS can be employed to design multiple clusters in a sliding-window fashion.

Usage

Arrange_TFBSs_clusters(
  TFBSs,
  max_intersite_distance = 75,
  min_intersite_distance = 15,
  max_cluster_size = 6,
  max_cluster_width = 300,
  add.single.TFs = TRUE
)

Arguments

TFBSs

GRanges object of TFBSs

max_intersite_distance

maximum allowed distance in base pairs between two TFBS centers for them to be considered part of the same cluster. Defaults to 75.

min_intersite_distance

minimum allowed distance in base pairs between two TFBS centers for them not to be discarded as overlapping. This parameter should be set according to the width of the bins used for later sorting. Defaults to 15.

max_cluster_size

maximum number of TFBSs to be contained in any given cluster. Defaults to 6

max_cluster_width

maximum width of TFBS clusters in bps. Defaults to 300

add.single.TFs

Whether to add the TFs not used to create TFBS.clusters to the list for sorting. Defaults to TRUE

Value

list with two elements: ClusterCoordinates (GRanges object of clusters coordinates) and ClusterComposition (GRangesList of sites for each cluster)

Examples

KLF4s = qs::qread(system.file("extdata", "KLF4_chr19.qs", package="SingleMoleculeFootprinting"))
Arrange_TFBSs_clusters(KLF4s)

Bait capture efficiency

Description

check bait capture efficiency. Expected to be ~70

Usage

BaitCapture(sampleFile, genome, baits, clObj = NULL)

Arguments

sampleFile

QuasR sample sheet

genome

BS genome

baits

GRanges obj of bait coordinates. We provide and example through SingleMoleculeFootprintingData::EnrichmentRegions_mm10.rds()

clObj

cluster object to emply for parallel processing created using the parallel::makeCluster function. Defaults to NULL

Value

bait capture efficiency

Examples

sampleFile = paste0(tempdir(), "/NRF1Pair_Qinput.txt")

if(file.exists(sampleFile)){
library(BSgenome.Mmusculus.UCSC.mm10)
BaitRegions = SingleMoleculeFootprintingData::EnrichmentRegions_mm10.rds()
BaitCapture(sampleFile = sampleFile, genome = BSgenome.Mmusculus.UCSC.mm10, baits = BaitRegions)
}

Summarize methylation inside sorting bins

Description

Summarize methylation inside sorting bins

Usage

BinMethylation(MethSM, Bin)

Arguments

MethSM

Single molecule matrix

Bin

IRanges object with absolute coordinates for single sorting bin.

Value

Reads covering bin with their summarized methylation status

Examples

library(IRanges)
library(GenomicRanges)

MethSM = qs::qread(system.file("extdata", "Methylation_4.qs", 
package="SingleMoleculeFootprinting"))[[2]]$SMF_MM_TKO_DE_

TFBSs = qs::qread(system.file("extdata", "TFBSs_1.qs", 
package="SingleMoleculeFootprinting"))

motif_center_1 = start(IRanges::resize(TFBSs[1], 1, "center"))
motif_center_2 = start(IRanges::resize(TFBSs[2], 1, "center"))
SortingBins = c(
GRanges("chr6", IRanges(motif_center_1-35, motif_center_1-25)),
GRanges("chr6", IRanges(motif_center_1-7, motif_center_1+7)),
GRanges("chr6", IRanges(motif_center_2-7, motif_center_2+7)),
GRanges("chr6", IRanges(motif_center_2+25, motif_center_2+35))
)

binMethylationValues = BinMethylation(MethSM = MethSM, Bin = SortingBins[1])

Call Context Methylation

Description

Can deal with multiple samples

Usage

CallContextMethylation(
  sampleFile,
  samples,
  genome,
  RegionOfInterest,
  coverage = 20,
  ConvRate.thr = NULL,
  returnSM = TRUE,
  clObj = NULL,
  verbose = FALSE
)

Arguments

sampleFile

QuasR pointer file

samples

vector of unique sample names corresponding to the SampleName field from the sampleFile

genome

BSgenome

RegionOfInterest

GenimocRange representing the genomic region of interest

coverage

coverage threshold as integer for least number of reads to cover a cytosine for it to be carried over in the analysis. Defaults to 20.

ConvRate.thr

Convesion rate threshold. Double between 0 and 1, defaults to NULL. To skip this filtering step, set to NULL. For more information, check out the details section.

returnSM

whether to return the single molecule matrix, defaults to TRUE

clObj

cluster object for parallel processing of multiple samples. For now only used by qMeth call for bulk methylation. Should be the output of a parallel::makeCluster() call

verbose

whether to print out messages while executing. Defaults to FALSE

Details

The ConvRate.thr argument should be used with care as it could create biases (e.g. when only one C out of context is present) while generally only marginally cleaning up the data.

Value

List with two Granges objects: average methylation call (GRanges) and single molecule methylation call (matrix)

Examples

sampleFile = NULL
if(!is.null(sampleFile)){
Methylation <- CallContextMethylation(
  sampleFile = sampleFile, 
  samples = samples, 
  genome = BSgenome.Mmusculus.UCSC.mm10, 
  RegionOfInterest = RegionOfInterest,
  coverage = 20, 
  returnSM = TRUE,
  ConvRate.thr = NULL,
  clObj = NULL
)
}

Implementation performing a similar operation of rbind.fill.Matrix but for columns

Description

Implementation performing a similar operation of rbind.fill.Matrix but for columns

Usage

cbind.fill.Matrix(x, y)

Arguments

x

sparse matrix constructed using the function Matrix::sparseMatrix. Should have Dimnames and dims (e.g. when indexing drop=FALSE)

y

sparse matrix constructed using the function Matrix::sparseMatrix. Should have Dimnames and dims (e.g. when indexing drop=FALSE)

Details

N.b. only possible fill at the moment is 0

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
MethSM_1 = Methylation[[2]][[1]]
Methylation = qs::qread(system.file("extdata", "Methylation_4.qs", 
package="SingleMoleculeFootprinting"))
MethSM_2 = Methylation[[2]][[1]]
cbind.fill.Matrix(MethSM_1, MethSM_2)

Collapse strands

Description

Collapse strands

Usage

CollapseStrands(MethGR, context)

Arguments

MethGR

Granges obj of average methylation

context

"GC" or "HCG". Broad because indicates just the directionality of collapse.

Value

MethGR with collapsed strands (everything turned to - strand)

Examples

# CollapseStrands(MethGR, "GC")

Collapse strands in single molecule matrix

Description

The idea here is that (regardless of context) if a C is on the - strand, calling getSeq on that coord (N.b. unstranded, that's the important bit) will give a "G', a "C" if it's a + strand.

Usage

CollapseStrandsSM(MethSM, context, genome, chr)

Arguments

MethSM

Single molecule matrix

context

"GC" or "CG". Broad because indicates just the directionality of collapse.

genome

BSgenome

chr

Chromosome, MethSM doesn't carry this info

Value

Strand collapsed MethSM

Examples

# CollapseStrandsSM(MethSM, "GC", BSgenome.Mmusculus.UCSC.mm10, "chr19")

Collect bulk SMF data for later composite plotting

Description

Collect bulk SMF data for later composite plotting

Usage

CollectCompositeData(
  sampleFile,
  samples,
  genome,
  TFBSs,
  window,
  coverage = 20,
  ConvRate.thr = NULL,
  cores = 1
)

Arguments

sampleFile

QuasR sampleFile

samples

vector of unique sample names corresponding to the SampleName field from the sampleFile

genome

BSgenome

TFBSs

GRanges object of TF binding sites to collect info for. We reccommend employing 50 to 200 TFBSs.

window

window size to collect methylation information for

coverage

coverage threshold as integer for least number of reads to cover a cytosine for it to be carried over in the analysis. Defaults to 20.

ConvRate.thr

Convesion rate threshold. Double between 0 and 1, defaults to NULL For more information, check out the details section

cores

number of cores to use

Value

data.frame of bulk SMF info ready for plotting

Examples

sampleFile = NULL
if(!is.null(sampleFile)){
CollectCompositeData(
sampleFile = sampleFile, 
samples = samples, 
genome = BSgenome.Mmusculus.UCSC.mm10, 
TFBSs = TopMotifs, 
window = 1000, 
coverage = 20, 
ConvRate.thr = NULL, 
cores = 16
) -> CompositeData
}

Calculate colMeans after dropping zeros

Description

Calculate colMeans after dropping zeros

Usage

colMeans_drop0(MethSM)

Arguments

MethSM

one single molecule sparse matrix

Value

colMeans (N.b. this is +1 based)


Composite Methylation Rate

Description

Monitor methylation rate distribution in a low coverage samples as compared to a high coverage "reference" one. It bins cytosines with similar methylation rates (as observed in the HighCoverage sample) into bins. A single methylation rate value is computed for each bin

Usage

CompositeMethylationCorrelation(
  LowCoverage,
  LowCoverage_samples,
  HighCoverage,
  HighCoverage_samples,
  bins = 50,
  returnDF = FALSE,
  returnPlot = TRUE,
  RMSE = TRUE,
  return_RMSE_DF = FALSE,
  return_RMSE_plot = TRUE
)

Arguments

LowCoverage

Single GRanges object as returned by CallContextMethylation function run with Coverage parameter set to 1. The object can also contain cytosines from multiple contexts

LowCoverage_samples

Samples to use from the LowCoverage object. Either a string or a vector (for multiple samples).

HighCoverage

Single GRanges object as returned by CallContextMethylation function. The object can also contain cytosines from multiple contexts.

HighCoverage_samples

Single sample to use from HighCoverage. String

bins

The number of bins for which to calculate the "binned" methylation rate. Defaults to 50

returnDF

Whether to return the data.frame used for plotting. Defaults to FALSE

returnPlot

Whether to return the plot. Defaults to TRUE

RMSE

Whether to calculate Mean squared error (RMSE) of methylation rate distribution estimates for low coverage samples. Defaults to TRUE

return_RMSE_DF

Whether to return a data.frame of computed RMSE values. Defaults to FALSE

return_RMSE_plot

Whether to return a barplot of computed values. Defaults to TRUE

Examples

# I don't have enough example data for this
# CompositeMethylationCorrelation(LowCoverage = LowCoverage$DGCHN,
#                                 LowCoverage_samples = LowCoverage_Samples,
#                                 HighCoverage = HighCoverage$DGCHN,
#                                 HighCoverage_samples = HighCoverage_samples[1],
#                                 returnDF = FALSE,
#                                 returnPlot = TRUE,
#                                 RMSE = TRUE,
#                                 return_RMSE_DF = FALSE,
#                                 return_RMSE_plot = TRUE)

Plot composite SMF data

Description

Will use geom_point with <= 5000 points, geom_hex otherwise

Usage

CompositePlot(CompositeData, span = 0.1, TF)

Arguments

CompositeData

the output of the CollectCompositeData function

span

the span parameter to pass to geom_smooth

TF

string of TF name to use for plot title

Examples

# CompositePlot(CompositeData = CompositeData, span = 0.1, TF = "Rest")

Conversion rate

Description

calculate sequencing library conversion rate on a chromosome of choice

Usage

ConversionRate(sampleFile, genome, chr = 19, cores = 1)

Arguments

sampleFile

QuasR sample sheet

genome

BS genome

chr

chromosome to calculate conversion rate on (default: 19)

cores

number of cores for parallel processing. Defaults to 1

Examples

# ConversionRate(sampleFile = sampleFile, 
# genome = BSgenome.Mmusculus.UCSC.mm10, chr = 19, cores = 1)

Filter Cs for coverage

Description

Filter Cs for coverage

Usage

CoverageFilter(MethGR, thr)

Arguments

MethGR

Granges obj of average methylation

thr

converage threshold

Value

filtered MethGR


Create methylation calling windows to call context methylation in one run for clusters lying proximally to each other

Description

Relevant for genome-wide analyses

Usage

Create_MethylationCallingWindows(
  RegionsOfInterest,
  max_intercluster_distance = 1e+05,
  max_window_width = 5e+06,
  min_cluster_width = 600,
  genomic.seqlenghts,
  fix.window.size = FALSE,
  max.window.size = 500
)

Arguments

RegionsOfInterest

TFBS cluster coordinates analogous to ClusterCoordinates object returned by Arrange_TFBSs_clusters function

max_intercluster_distance

maximum distance between two consecutive TFBS clusters for them to be grouped in the same window

max_window_width

upper limit to window width. This value should be adjusted according to the user's system as it determines the amount of memory used in the later context methylation call

min_cluster_width

lower limit to window width. Corresponds to the scenario when a window contains a single TFBS cluster.

genomic.seqlenghts

used to fix the windows spanning over chromosome edges. To be fetched by GenomeInfoDb::seqlengths() or equivalent.

fix.window.size

Defaults to FALSE. When TRUE, overrides arguments max_intercluster_distance and max_window_width and produces windows containing a fixed number of TFBS_clusters.

max.window.size

Max number of TFBS_clusters per window. Used only when fix.window.size is TRUE. N.b.: window size could be slightly higher than passed value if RegionsOfInterest overlap

Value

GRanges object of window coordinates to be used for more efficient calls of CallContextMethylation

Examples

KLF4s = qs::qread(system.file("extdata", "KLF4_chr19.qs", package="SingleMoleculeFootprinting"))
Create_MethylationCallingWindows(RegionsOfInterest = KLF4s)

Detect type of experiment

Description

Detect type of experiment

Usage

DetectExperimentType(Samples)

Arguments

Samples

SampleNames field from QuasR sampleFile

Examples

CacheDir = ExperimentHub::getExperimentHubOption(arg = "CACHE")
sampleFile = paste0(CacheDir, "/NRF1Pair_sampleFile.txt")
samples = suppressMessages(unique(readr::read_delim(sampleFile, delim = "\t")[[2]]))
DetectExperimentType(samples)

Recalculate *_T and *_M values in MethGR object after filtering reads e.g. for conversion rate

Description

Recalculate *_T and *_M values in MethGR object after filtering reads e.g. for conversion rate

Usage

filter_reads_from_MethGR(MethGR, MethSM, MethSM_filtered, sampleIndex)

Arguments

MethGR

GRanges object of methylation call

MethSM

Single Molecule methylation matrix

MethSM_filtered

Single Molecule methylation matrix after filtering reads

sampleIndex

index for sample to treat. It serves as a correspondence between the index of the SM matrix and the order samples appear in the elementMetadata() columns

Value

MethGR with recalculated counts


Calculate reads conversion rate

Description

Calculate reads conversion rate

Usage

FilterByConversionRate(MethSM, chr, genome, thr)

Arguments

MethSM

as comes out of the func GetSingleMolMethMat

chr

Chromosome, MethSM doesn't carry this info

genome

BSgenome

thr

Double between 0 and 1. Threshold below which to filter reads.

Value

Filtered MethSM

Examples

library(BSgenome.Mmusculus.UCSC.mm10)
MethSM = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))[[2]]$SMF_MM_TKO_DE_
FilterByConversionRate(MethSM, chr = "chr19", 
genome = BSgenome.Mmusculus.UCSC.mm10, thr = 0.8)

Filter Cytosines in context

Description

Filter Cytosines in context

Usage

FilterContextCytosines(MethGR, genome, context)

Arguments

MethGR

Granges obj of average methylation

genome

BSgenome

context

Context of interest (e.g. "GC", "CG",..)

Value

filtered Granges obj

Examples

library(BSgenome.Mmusculus.UCSC.mm10)
MethGR = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))[[1]]

FilterContextCytosines(MethGR, BSgenome.Mmusculus.UCSC.mm10, "NGCNN")

Utility function to perform the dplyr full_join operation on GRanges object

Description

Utility function to perform the dplyr full_join operation on GRanges object

Usage

full.join.granges(MethGR1, MethGR2)

Arguments

MethGR1

Methylation GRanges as output by the CallContextMethylation() function

MethGR2

Methylation GRanges as output by the CallContextMethylation() function


Get QuasRprj

Description

Get QuasRprj

Usage

GetQuasRprj(sampleFile, genome)

Arguments

sampleFile

QuasR pointer file

genome

BSgenome

Examples

library(BSgenome.Mmusculus.UCSC.mm10)
CacheDir <- ExperimentHub::getExperimentHubOption(arg = "CACHE")
sampleFile = paste0(CacheDir, "/NRF1Pair_sampleFile.txt")
QuasRprj = GetQuasRprj(sampleFile, BSgenome.Mmusculus.UCSC.mm10)

Get Single Molecule methylation matrix

Description

Used internally as the first step in CallContextMethylation

Usage

GetSingleMolMethMat(QuasRprj, range, sample)

Arguments

QuasRprj

QuasR project object as returned by calling the QuasR function qAling on previously aligned data

range

GenimocRange representing the genomic region of interest

sample

One of the sample names as reported in the SampleName field of the QuasR sampleFile provided to qAlign. N.b. all the files with the passed sample name will be used to call methylation

Value

List of single molecule methylation matrixes (all Cytosines), one per sample

Examples

library(BSgenome.Mmusculus.UCSC.mm10)
library(IRanges)
library(GenomicRanges)

CacheDir <- ExperimentHub::getExperimentHubOption(arg = "CACHE")
sampleFile = paste0(CacheDir, "/NRF1Pair_sampleFile.txt")
sample = suppressMessages(readr::read_delim(sampleFile, delim = "\t")[[2]])
QuasRprj = GetQuasRprj(sampleFile, BSgenome.Mmusculus.UCSC.mm10)
range = GRanges("chr6", IRanges(88106000, 88106500))

GetSingleMolMethMat(QuasRprj, range, sample)

Manipulate GRanges into data.frame

Description

Inner utility for LowCoverageMethRateDistribution

Usage

GRanges_to_DF(GRanges_obj)

Arguments

GRanges_obj

GRanges object as returned by CallContextMethylation function


Perform Hierarchical clustering on single reads

Description

Perform Hierarchical clustering on single reads

Usage

HierarchicalClustering(MethSM)

Arguments

MethSM

Single molecule methylation matrix


Low Coverage Methylation Rate RMSE

Description

Calculate Root mean squared error (RMSE) of methylation rate distribution estimates for low coverage samples

Usage

LowCoverageMethRate_RMSE(BinnedMethRate)

Arguments

BinnedMethRate

data.frame as returned by GRanges_to_DF function.


Utility function to remove cytosines whose MTase target genomic context is affected by SNPs

Description

Utility function to remove cytosines whose MTase target genomic context is affected by SNPs

Usage

MaskSNPs(
  Methylation,
  CytosinesToMask,
  MaskSMmat = FALSE,
  SampleStringMatch = list(Cast = "_CTKO", Spret = "_STKO"),
  Experiment
)

Arguments

Methylation

as output by the CallContextMethylation() function

CytosinesToMask

GRanges specifying the coordinate of the cytosines to discard.

MaskSMmat

whether the parameter Methylation includes single molecule matrixes

SampleStringMatch

list of per-sample string matches that are used to uniquely identify the relevant column for each species in the Methylation object. Defaults to list(Cast = "_CTKO", Spret = "_STKO")

Experiment

as detected by the DetectExperimentType() function. Should be either "DE" or "NO"

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_2.qs", 
package="SingleMoleculeFootprinting"))
CytosinesToMask = qs::qread(system.file("extdata", "cytosines_to_mask.qs", 
package="SingleMoleculeFootprinting"))

MaskSNPs(Methylation = Methylation, CytosinesToMask = CytosinesToMask, MaskSMmat = FALSE, 
SampleStringMatch = list(Cast = "_CTKO", Spret = "_STKO"), Experiment = "DE") -> Methylation_masked

Compute MethGR from MethSM

Description

Compute MethGR from MethSM

Usage

MethSM.to.MethGR(MethSM, chromosome)

Arguments

MethSM

internal CallContextMethylation

chromosome

string


Utility for HighCoverage_MethRate_SampleCorrelation

Description

Utility for HighCoverage_MethRate_SampleCorrelation

Usage

panel.cor(x, y, digits = 2, prefix = "", cex.cor)

Arguments

x

x variable

y

y variable

digits

number of digits

prefix

string

cex.cor

graphical param


Utility for HighCoverage_MethRate_SampleCorrelation

Description

Utility for HighCoverage_MethRate_SampleCorrelation

Usage

panel.hist(x, ...)

Arguments

x

data for hist

...

data for hist


Utility for HighCoverage_MethRate_SampleCorrelation

Description

Utility for HighCoverage_MethRate_SampleCorrelation

Usage

panel.jet(...)

Arguments

...

data for lower pairs panel


Plot low coverage methylation rate

Description

Inner utility for LowCoverageMethRateDistribution

Usage

Plot_LowCoverageMethRate(Plotting_DF)

Arguments

Plotting_DF

data.frame as returned by GRanges_to_DF function.


Plot Low Coverage Methylation Rate RMSE

Description

Produce barplot of RMSE values calculated for methylation rate distribution estimates of low coverage samples

Usage

Plot_LowCoverageMethRate_RMSE(RMSE_DF)

Arguments

RMSE_DF

data.frame as returned by the LowCoverageMethRate_RMSE function


Plot average methylation

Description

Plot average methylation

Usage

PlotAvgSMF(
  MethGR,
  MethSM = NULL,
  RegionOfInterest,
  SortedReads = NULL,
  ShowContext = FALSE,
  TFBSs = NULL,
  SNPs = NULL,
  SortingBins = NULL
)

Arguments

MethGR

Average methylation GRanges obj

MethSM

Single molecule matrix(es)

RegionOfInterest

GRanges interval to plot

SortedReads

List of sorted reads, needs to be passed along with the parameter MethSM. If both are passed, only counts relevant to sorting will be plotted

ShowContext

TRUE or FALSE (default). Causes the genomic context of the plotted cytosines to be displayed as the dot shape

TFBSs

GRanges object of transcription factor binding sites to include in the plot. Assumed to be already subset. Also assumed that the tf names are under the column "TF"

SNPs

GRanges object of SNPs to visualize. Assumed to be already subset. Assumed to have the reference and alternative sequences respectively under the columns "R" and "A"

SortingBins

GRanges object of sorting bins (absolute) coordinate to visualize

Examples

library(GenomicRanges)

RegionOfInterest = GRanges("chr12", IRanges(20464551, 20465050))
Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_3.qs", package="SingleMoleculeFootprinting"))

PlotAvgSMF(MethGR = Methylation[[1]], RegionOfInterest = RegionOfInterest, TFBSs = TFBSs)

Plot single molecule stack

Description

Plot single molecule stack

Usage

PlotSingleMoleculeStack(MethSM, RegionOfInterest)

Arguments

MethSM

Single molecule methylation matrix

RegionOfInterest

GRanges interval to plot

Examples

library(GenomicRanges)

RegionOfInterest = GRanges("chr12", IRanges(20464551, 20465050))
Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))

PlotSingleMoleculeStack(MethSM = Methylation[[2]], RegionOfInterest = RegionOfInterest)

Plot SMF data at single site

Description

Plot SMF data at single site

Usage

PlotSingleSiteSMF(
  Methylation,
  RegionOfInterest,
  ShowContext = FALSE,
  TFBSs = NULL,
  SNPs = NULL,
  SortingBins = NULL,
  SortedReads = NULL,
  sorting.strategy = "None"
)

Arguments

Methylation

Context methylation object as returned by CallContextMethylation function

RegionOfInterest

GRanges interval to plot

ShowContext

TRUE or FALSE (default). Causes the genomic context of the plotted cytosines to be displayed as the dot shape

TFBSs

GRanges object of transcription factor binding sites to include in the plot. Assumed to be already subset. Also assumed that the tf names are under the column "TF"

SNPs

GRanges object of SNPs to visualize. Assumed to be already subset. Assumed to have the reference and alternative sequences respectively under the columns "R" and "A"

SortingBins

GRanges object of sorting bins (absolute) coordinate to visualize

SortedReads

Defaults to NULL, in which case will plot unsorted reads. Sorted reads object as returned by SortReads function or "HC" to perform hierarchical clustering

sorting.strategy

One of "classical" (default), "custom", "hierarchical.clustering" or "None". Determines how to display reads. For details check documentation from PlotSM function.

Examples

library(GenomicRanges)

RegionOfInterest = GRanges("chr12", IRanges(20464551, 20465050))
Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_3.qs", package="SingleMoleculeFootprinting"))
SortedReads = SortReadsBySingleTF(MethSM = Methylation[[2]], TFBS = TFBSs)

PlotSingleSiteSMF(Methylation = Methylation,
                  RegionOfInterest = RegionOfInterest,
                  SortedReads = SortedReads,
                  TFBSs = TFBSs)

Wrapper for PlotSingleMoleculeStack function

Description

adds the convenience of arranging reads before plotting

Usage

PlotSM(
  MethSM,
  RegionOfInterest,
  sorting.strategy = "classical",
  SortedReads = NULL
)

Arguments

MethSM

Single molecule methylation matrix

RegionOfInterest

GRanges interval to plot

sorting.strategy

One of "classical" (default), "custom", "hierarchical.clustering" or "None". Set to "classical" for classical one-TF/TF-pair sorting (as described in Sönmezer et al, MolCell, 2021). Should be passed along with argument SortedReads set to the Sorted reads object as returned by SortReads function. If set to "custom", SortedReads should be a list with one item per sample (corresponding to MethSM). If set to "hierarchical.clustering", the function will perform hierarchical clustering in place on a subset of reads. Useful to check for duplicated reads in amplicon sequencing experiments. If set to "None", it will plot unsorted reads. The argument sorting,strategy will always determine how to display reads with priority over the argument SortedReads

SortedReads

Defaults to NULL, in which case will plot unsorted reads. Sorted reads object as returned by SortReads function

Examples

library(GenomicRanges)

RegionOfInterest = GRanges("chr12", IRanges(20464551, 20465050))
Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_3.qs", 
package="SingleMoleculeFootprinting"))
SortedReads = SortReadsBySingleTF(MethSM = Methylation[[2]], TFBS = TFBSs)

PlotSM(MethSM = Methylation[[2]], RegionOfInterest = RegionOfInterest, SortedReads = SortedReads)

Implementation performing a similar operation of plyr::rbind.fill.matrix but for sparseMatrix

Description

Implementation performing a similar operation of plyr::rbind.fill.matrix but for sparseMatrix

Usage

rbind.fill.Matrix(x, y)

Arguments

x

sparse matrix constructed using the function Matrix::sparseMatrix. Should have Dimnames and dims (e.g. when indexing drop=FALSE)

y

sparse matrix constructed using the function Matrix::sparseMatrix. Should have Dimnames and dims (e.g. when indexing drop=FALSE)

Details

N.b. only possible fill at the moment is 0

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
MethSM_1 = Methylation[[2]][[1]]
Methylation = qs::qread(system.file("extdata", "Methylation_4.qs", 
package="SingleMoleculeFootprinting"))
MethSM_2 = Methylation[[2]][[1]]
rbind.fill.Matrix(MethSM_1, MethSM_2)

Calculate rowMeans after dropping zeros

Description

Calculate rowMeans after dropping zeros

Usage

rowMeans_drop0(MethSM)

Arguments

MethSM

one single molecule sparse matrix

Value

rowMeans (N.b. this is +1 based)


Single TF state quantification bar

Description

Single TF state quantification bar

Usage

SingleTFStateQuantificationPlot(SortedReads)

Arguments

SortedReads

Sorted reads as returned by SortReadsBySingleTF


Hard-coded interpretation of biological states from single TF sorting

Description

Hard-coded interpretation of biological states from single TF sorting

Usage

SingleTFStates()

Value

list of states

Examples

SingleTFStates()

Sort reads by single TF

Description

Sort reads by single TF

Usage

SortReads(MethSM, BinsCoordinates, coverage = NULL)

Arguments

MethSM

Single molecule matrix

BinsCoordinates

IRanges object of absolute coordinates for sorting bins

coverage

integer. Minimum number of reads covering all sorting bins for sorting to be performed

Value

list of sorted reads

Examples

library(IRanges)

Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBS = qs::qread(system.file("extdata", "TFBSs_3.qs", 
package="SingleMoleculeFootprinting"))

bins = list(c(-35,-25), c(-15,15), c(25,35))
TFBS_center = start(TFBS) + (end(TFBS)-start(TFBS))/2
BinsCoordinates = IRanges(
start = c(TFBS_center+bins[[1]][1], TFBS_center+bins[[2]][1], TFBS_center+bins[[3]][1]),
end = c(TFBS_center+bins[[1]][2], TFBS_center+bins[[2]][2], TFBS_center+bins[[3]][2])
)

SortedReads = SortReads(Methylation[[2]]$SMF_MM_TKO_DE_, BinsCoordinates, coverage = 20)

Wrapper to SortReads for single TF case

Description

Wrapper to SortReads for single TF case

Usage

SortReadsBySingleTF(
  MethSM,
  TFBS,
  bins = list(c(-35, -25), c(-15, 15), c(25, 35)),
  coverage = 20
)

Arguments

MethSM

Single molecule matrix list as returned by CallContextMethylation

TFBS

Transcription factor binding site to use for sorting, passed as a GRanges object of length 1

bins

list of 3 relative bin coordinates. Defaults to list(c(-35,-25), c(-15,15), c(25,35)). bins[[1]] represents the upstream bin, with coordinates relative to the start of the TFBS. bins[[2]] represents the TFBS bin, with coordinates relative to the center of the TFBS. bins[[3]] represents the downstream bin, with coordinates relative to the end of the TFBS.

coverage

integer. Minimum number of reads covering all sorting bins for sorting to be performed. Defaults to 20

Value

List of reads sorted by single TF

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_3.qs", 
package="SingleMoleculeFootprinting"))

SortedReads = SortReadsBySingleTF(MethSM = Methylation[[2]], TFBS = TFBSs)

Convenience wrapper to sort single molecule according to TFBS clusters at multiple sites in the genome

Description

The function starts from a list of single TFBSs, arranges them into clusters, calls methylation at the interested sites and outputs sorted reads

Usage

SortReadsBySingleTF_MultiSiteWrapper(
  sampleFile,
  samples,
  genome,
  coverage = 20,
  ConvRate.thr = NULL,
  CytosinesToMask = NULL,
  TFBSs,
  max_interTF_distance = 1e+05,
  max_window_width = 5e+06,
  min_cluster_width = 600,
  fix.window.size = FALSE,
  max.window.size = NULL,
  sorting_coverage = 30,
  bins = list(c(-35, -25), c(-15, 15), c(25, 35)),
  cores = 1
)

Arguments

sampleFile

QuasR pointer file

samples

samples to use, from the SampleName field of the sampleFile

genome

BSgenome

coverage

coverage threshold as integer for least number of reads to cover a cytosine for it to be carried over in the analysis. Defaults to 20.

ConvRate.thr

Convesion rate threshold. Double between 0 and 1, defaults to NULL. To skip this filtering step, set to NULL. For more information, check out the details section.

CytosinesToMask

CytosinesToMask object. Passed to MaskSNPs function

TFBSs

GRanges object of transcription factor binding sites coordinates

max_interTF_distance

maximum distance between two consecutive TFBSs for them to be grouped in the same window

max_window_width

upper limit to window width. This value should be adjusted according to the user's system as it determines the amount of memory used in the later context methylation call

min_cluster_width

lower limit to window width. Corresponds to the scenario when a window contains a single TFBS.

fix.window.size

defaults to FALSE. Passed to Create_MethylationCallingWindows function.

max.window.size

defaults to NULL. Passed to Create_MethylationCallingWindows function.

sorting_coverage

integer. Minimum number of reads covering all sorting bins for sorting to be performed. Defaults to 30.

bins

list of 3 relative bin coordinates. Defaults to list(c(-35,-25), c(-15,15), c(25,35)). bins[[1]] represents the upstream bin, with coordinates relative to the start of the most upstream TFBS. bins[[2]] represents all the TFBS bins, with coordinates relative to the center of each TFBS. bins[[3]] represents the downstream bin, with coordinates relative to the end of the most downstream TFBS.

cores

number of cores to use for parallel processing of multiple Methylation Calling Windows (i.e. groupings of adjecent TFBS clusters)

Value

list where [[1]] is the TFBSs GRanges object describing coordinates TFBSs used to sort single molecules [[2]] is a list of SortedReads nested per TFBS_cluster and sample [[3]] is a tibble reporting the count (and frequency) of reads per state, sample and TFBS cluster

Examples

sampleFile = NULL
if(!is.null(sampleFile)){
SortReadsBySingleTF_MultiSiteWrapper(
sampleFile = sampleFile, 
samples = samples, 
genome = BSgenome.Mmusculus.UCSC.mm10, 
coverage = 20, ConvRate.thr = NULL, 
CytosinesToMask = NULL,
TFBSs = KLF4s, 
max_interTF_distance = NULL, max_window_width = NULL, min_cluster_width = NULL, 
fix.window.size = TRUE, max.window.size = 50, 
cores = 4
) -> sorting_results
}

Wrapper to SortReads for TF cluster case

Description

Wrapper to SortReads for TF cluster case

Usage

SortReadsByTFCluster(
  MethSM,
  TFBS_cluster,
  bins = list(c(-35, -25), c(-7, 7), c(25, 35)),
  coverage = 30
)

Arguments

MethSM

Single molecule matrix list as returned by CallContextMethylation

TFBS_cluster

Transcription factor binding sites to use for sorting, passed as a GRanges object of length > 1

bins

list of 3 relative bin coordinates. Defaults to list(c(-35,-25), c(-7,7), c(25,35)). bins[[1]] represents the upstream bin, with coordinates relative to the start of the most upstream TFBS. bins[[2]] represents all the TFBS bins, with coordinates relative to the center of each TFBS. bins[[3]] represents the downstream bin, with coordinates relative to the end of the most downstream TFBS.

coverage

integer. Minimum number of reads covering all sorting bins for sorting to be performed. Defaults to 30

Value

List of reads sorted by TF cluster

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_4.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_1.qs", 
package="SingleMoleculeFootprinting"))

SortedReads = SortReadsByTFCluster(MethSM = Methylation[[2]], TFBS_cluster = TFBSs)

Convenience wrapper to sort single molecule according to TFBS clusters at multiple sites in the genome

Description

The function starts from a list of single TFBSs, arranges them into clusters, calls methylation at the interested sites and outputs sorted reads

Usage

SortReadsByTFCluster_MultiSiteWrapper(
  sampleFile,
  samples,
  genome,
  coverage = 20,
  ConvRate.thr = 0.8,
  CytosinesToMask = NULL,
  TFBSs,
  max_intersite_distance = 75,
  min_intersite_distance = 15,
  max_cluster_size = 10,
  max_cluster_width = 300,
  add.single.TFs = TRUE,
  max_intercluster_distance = 1e+05,
  max_window_width = 5e+06,
  min_cluster_width = 600,
  fix.window.size = FALSE,
  max.window.size = NULL,
  sorting_coverage = 30,
  bins = list(c(-35, -25), c(-7, 7), c(25, 35)),
  cores = 1
)

Arguments

sampleFile

QuasR pointer file

samples

samples to use, from the SampleName field of the sampleFile

genome

BSgenome

coverage

coverage threshold as integer for least number of reads to cover a cytosine for it to be carried over in the analysis. Defaults to 20.

ConvRate.thr

Convesion rate threshold. Double between 0 and 1, defaults to 0.8. To skip this filtering step, set to NULL. For more information, check out the details section.

CytosinesToMask

CytosinesToMask object. Passed to MaskSNPs function

TFBSs

GRanges object of transcription factor binding sites coordinates

max_intersite_distance

maximum allowed distance in base pairs between two TFBS centers for them to be considered part of the same cluster. Defaults to 75.

min_intersite_distance

minimum allowed distance in base pairs between two TFBS centers for them not to be discarded as overlapping. This parameter should be set according to the width of the bins used for later sorting. Defaults to 15.

max_cluster_size

maximum number of TFBSs to be contained in any given cluster. Defaults to 10

max_cluster_width

maximum cluster width in bp. Defaults to 300

add.single.TFs

whether to add to output the TFBSs that didn't make it into clusters. Defaults to TRUE

max_intercluster_distance

maximum distance between two consecutive TFBS clusters for them to be grouped in the same window

max_window_width

upper limit to window width. This value should be adjusted according to the user's system as it determines the amount of memory used in the later context methylation call

min_cluster_width

lower limit to window width. Corresponds to the scenario when a window contains a single TFBS cluster.

fix.window.size

defaults to FALSE. Passed to Create_MethylationCallingWindows function.

max.window.size

defaults to NULL. Passed to Create_MethylationCallingWindows function.

sorting_coverage

integer. Minimum number of reads covering all sorting bins for sorting to be performed. Defaults to 30.

bins

list of 3 relative bin coordinates. Defaults to list(c(-35,-25), c(-7,7), c(25,35)). bins[[1]] represents the upstream bin, with coordinates relative to the start of the most upstream TFBS. bins[[2]] represents all the TFBS bins, with coordinates relative to the center of each TFBS. bins[[3]] represents the downstream bin, with coordinates relative to the end of the most downstream TFBS.

cores

number of cores to use for parallel processing of multiple Methylation Calling Windows (i.e. groupings of adjecent TFBS clusters)

Value

list where [[1]] is the TFBS_Clusters object describing coordinates and composition of the TFBS clusters used to sort single molecules [[2]] is a list of SortedReads nested per TFBS_cluster and sample [[3]] is a tibble reporting the count (and frequency) of reads per state, samples and TFBS cluster

Examples

sampleFile = NULL
if(!is.null(sampleFile)){
SortReadsByTFCluster_MultiSiteWrapper(
sampleFile = sampleFile, 
samples = samples, 
genome = BSgenome.Mmusculus.UCSC.mm10, 
coverage = 20, ConvRate.thr = NULL, 
CytosinesToMask = NULL,
TFBSs = KLF4s, 
max_interTF_distance = NULL, max_window_width = NULL, min_cluster_width = NULL, 
fix.window.size = TRUE, max.window.size = 50, 
cores = 4
) -> sorting_results
}

Convenience for calculating state frequencies

Description

Convenience for calculating state frequencies

Usage

StateQuantification(SortedReads, states)

Arguments

SortedReads

List of sorted reads (can be multiple samples) as returned by either read sorting function (SortReads, SortReadsBySingleTF, SortReadsByTFCluster)

states

states reporting the biological interpretation of patterns as return by either SingleTFStates or TFPairStates functions. If NULL (default) will return frequencies without biological interpretation.

Value

tibble with state frequency information

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_4.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_1.qs", 
package="SingleMoleculeFootprinting"))
SortedReads = SortReadsByTFCluster(MethSM = Methylation[[2]], TFBS_cluster = TFBSs)
StateQuantification(SortedReads = SortedReads, states = TFPairStates())

Convenience for calculating state frequencies after sorting reads by single TF

Description

wraps around StateQuantification function

Usage

StateQuantificationBySingleTF(SortedReads)

Arguments

SortedReads

List of sorted reads (can be multiple samples) as returned by SortReadsBySingleTF (or SortReads run with analogous parameters)

Value

tibble with state frequency information

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_3.qs", 
package="SingleMoleculeFootprinting"))
SortedReads = SortReadsBySingleTF(MethSM = Methylation[[2]], TFBS = TFBSs)
StateQuantificationBySingleTF(SortedReads = SortedReads)

Convenience for calculating state frequencies after sorting reads by TF pair

Description

wraps around StateQuantification function

Usage

StateQuantificationByTFPair(SortedReads)

Arguments

SortedReads

List of sorted reads (can be multiple samples) as returned by SortReadsByTFCluster run for clusters of size 2 (or SortReads run with analogous parameters)

Value

tibble with state frequency information

Examples

Methylation = qs::qread(system.file("extdata", "Methylation_4.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_1.qs", 
package="SingleMoleculeFootprinting"))
SortedReads = SortReadsByTFCluster(MethSM = Methylation[[2]], TFBS_cluster = TFBSs)
StateQuantificationByTFPair(SortedReads = SortedReads)

Plot states quantification bar

Description

Plot states quantification bar

Usage

StateQuantificationPlot(SortedReads, states)

Arguments

SortedReads

Sorted reads object as returned by SortReads function

states

either SingleTFStates() or TFPairStates()

Value

Bar plot quantifying states

Examples

library(GenomicRanges)

RegionOfInterest = GRanges("chr12", IRanges(20464551, 20465050))
Methylation = qs::qread(system.file("extdata", "Methylation_3.qs", 
package="SingleMoleculeFootprinting"))
TFBSs = qs::qread(system.file("extdata", "TFBSs_3.qs", package="SingleMoleculeFootprinting"))
SortedReads = SortReadsBySingleTF(MethSM = Methylation[[2]], TFBS = TFBSs)

StateQuantificationPlot(SortedReads = SortedReads, states = SingleTFStates())

Subset Granges for given samples

Description

Inner utility for LowCoverageMethRateDistribution

Usage

SubsetGRangesForSamples(GRanges_obj, Samples)

Arguments

GRanges_obj

GRanges object as returned by CallContextMethylation function

Samples

vector of sample names as they appear in the SampleName field of the QuasR sampleFile


TF pair state quantification bar

Description

TF pair state quantification bar

Usage

TFPairStateQuantificationPlot(SortedReads)

Arguments

SortedReads

Sorted reads as returned by SortReadsByTFCluster


Design states for TF pair case

Description

Design states for TF pair case

Usage

TFPairStates()

Value

list of states

Examples

TFPairStates()