## ----echo = FALSE, message = FALSE-------------------------------------------- knitr::opts_chunk$set(collapse = TRUE, comment = "#>") options(tibble.print_min = 4L, tibble.print_max = 4L) ## ----eval = FALSE------------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("HicAggR") ## ----eval = FALSE------------------------------------------------------------- # remotes::install_github("CuvierLab/HicAggR") ## ----eval = TRUE, message = FALSE--------------------------------------------- library("HicAggR") ## ----eval = TRUE, message = FALSE--------------------------------------------- withr::local_options(list(timeout = 3600)) cache.dir <- paste0(tools::R_user_dir("", which="cache"),".HicAggR_HIC_DATA") bfc <- BiocFileCache::BiocFileCache(cache.dir,ask = FALSE) ## ----eval = TRUE, message = FALSE--------------------------------------------- if(length(BiocFileCache::bfcinfo(bfc)$rname)==0 || !"Control_HIC.hic"%in%BiocFileCache::bfcinfo(bfc)$rname){ Hic.url <- paste0("https://4dn-open-data-public.s3.amazonaws.com/", "fourfront-webprod/wfoutput/7386f953-8da9-47b0-acb2-931cba810544/", "4DNFIOTPSS3L.hic") if(.Platform$OS.type == "windows"){ HicOutput.pth <- BiocFileCache::bfcadd( x = bfc,rname = "Control_HIC.hic", fpath = Hic.url, download = TRUE, config = list(method="auto",mode="wb")) }else{ HicOutput.pth <- BiocFileCache::bfcadd( x = bfc, rname = "Control_HIC.hic", fpath = Hic.url, download = TRUE, config = list(method="auto")) } }else{ HicOutput.pth <- BiocFileCache::bfcpath(bfc)[ which(BiocFileCache::bfcinfo(bfc)$rname=="Control_HIC.hic")] } ## ----eval = TRUE, message = FALSE--------------------------------------------- if(length(BiocFileCache::bfcinfo(bfc)$rname)==0 || !"HeatShock_HIC.mcool"%in%BiocFileCache::bfcinfo(bfc)$rname){ Mcool.url <- paste0("https://4dn-open-data-public.s3.amazonaws.com/", "fourfront-webprod/wfoutput/4f1479a2-4226-4163-ba99-837f2c8f4ac0/", "4DNFI8DRD739.mcool") if(.Platform$OS.type == "windows"){ McoolOutput.pth <- BiocFileCache::bfcadd( x = bfc, rname = "HeatShock_HIC.mcool", fpath = Mcool.url, download = TRUE, config = list(method="auto",mode="wb")) }else{ McoolOutput.pth <- BiocFileCache::bfcadd( x = bfc, rname = "HeatShock_HIC.mcool", fpath = Mcool.url, download = TRUE, config = list(method="auto")) } }else{ McoolOutput.pth <- as.character(BiocFileCache::bfcpath(bfc)[ which(BiocFileCache::bfcinfo(bfc)$rname=="HeatShock_HIC.mcool")]) } ## ----eval = TRUE-------------------------------------------------------------- data("Beaf32_Peaks.gnr") ## ----echo = FALSE, eval = TRUE, message = FALSE------------------------------- Beaf_Peaks.dtf <- Beaf32_Peaks.gnr |> as.data.frame() |> head(n=3L) Beaf_Peaks.dtf <- Beaf_Peaks.dtf[,-c(4)] knitr::kable(Beaf_Peaks.dtf[,c(1:4,6,5)], col.names = c( "seq","start","end","strand", "name","score"), align = "rccccc", digits = 1 ) ## ----eval = TRUE-------------------------------------------------------------- data("TSS_Peaks.gnr") ## ----echo = FALSE, eval = TRUE, message = FALSE------------------------------- TSS_Peaks.dtf <- TSS_Peaks.gnr |> as.data.frame() |> head(n=3L) TSS_Peaks.dtf <- TSS_Peaks.dtf[,-c(4)] knitr::kable(TSS_Peaks.dtf[,c(1:4,6,5)], col.names = c( "seq","start","end","strand", "name","class"), align = "rccccc" ) ## ----eval = TRUE-------------------------------------------------------------- data("TADs_Domains.gnr") ## ----echo = FALSE, eval = TRUE, message = FALSE------------------------------- domains.dtf <- TADs_Domains.gnr |> as.data.frame() |> head(n=3L) domains.dtf <- domains.dtf[,-c(4)] knitr::kable(domains.dtf[,c(1:4,7,5,6)], col.names = c( "seq","start","end","strand", "name","score","class"), align = "rcccccc" ) ## ----eval = TRUE-------------------------------------------------------------- seqlengths.num <- c('2L'=23513712, '2R'=25286936) chromSizes <- data.frame( seqnames = names(seqlengths.num ), seqlengths = seqlengths.num ) binSize <- 5000 ## ----eval = TRUE, message = FALSE--------------------------------------------- HiC_Ctrl.cmx_lst <- ImportHiC( file = HicOutput.pth, hicResolution = 5000, chrom_1 = c("2L", "2L", "2R"), chrom_2 = c("2L", "2R", "2R") ) ## ----eval = TRUE, message = FALSE--------------------------------------------- HiC_HS.cmx_lst <- ImportHiC( file = McoolOutput.pth, hicResolution = 5000, chrom_1 = c("2L", "2L", "2R"), chrom_2 = c("2L", "2R", "2R") ) ## ----eval = TRUE, results = FALSE--------------------------------------------- HiC_Ctrl.cmx_lst <- BalanceHiC(HiC_Ctrl.cmx_lst) HiC_HS.cmx_lst <- BalanceHiC(HiC_HS.cmx_lst) ## ----eval = TRUE, results = FALSE--------------------------------------------- HiC_Ctrl.cmx_lst <- OverExpectedHiC(HiC_Ctrl.cmx_lst) HiC_HS.cmx_lst <- OverExpectedHiC(HiC_HS.cmx_lst) ## ----eval = TRUE-------------------------------------------------------------- str(HiC_Ctrl.cmx_lst,max.level = 4) #> ## ----eval = TRUE-------------------------------------------------------------- attributes(HiC_Ctrl.cmx_lst) #> ## ----eval = TRUE-------------------------------------------------------------- str(S4Vectors::metadata(HiC_Ctrl.cmx_lst[["2L_2L"]])) #> ## ----message = FALSE, eval = TRUE--------------------------------------------- anchors_Index.gnr <- IndexFeatures( gRangeList = list(Beaf=Beaf32_Peaks.gnr), genomicConstraint = TADs_Domains.gnr, chromSizes = chromSizes, binSize = binSize, metadataColName = "score", method = "max" ) ## ----echo = FALSE, eval = TRUE------------------------------------------------ anchors_Index.gnr |> as.data.frame() |> head(n=3) |> knitr::kable() ## ----eval = TRUE-------------------------------------------------------------- baits_Index.gnr <- IndexFeatures( gRangeList = list(Tss=TSS_Peaks.gnr), genomicConstraint = TADs_Domains.gnr, chromSizes = chromSizes, binSize = binSize, metadataColName = "score", method = "max" ) ## ----echo = FALSE, eval = TRUE------------------------------------------------ baits_Index.gnr |> as.data.frame() |> head(n=3) |> knitr::kable() ## ----eval = TRUE-------------------------------------------------------------- non_Overlaps.ndx <- match(baits_Index.gnr$bin, anchors_Index.gnr$bin, nomatch=0L)==0L baits_Index.gnr <- baits_Index.gnr[non_Overlaps.ndx,] ## ----echo = FALSE, eval = TRUE------------------------------------------------ baits_Index.gnr |> as.data.frame() |> head(n=3) |> knitr::kable() ## ----eval = TRUE-------------------------------------------------------------- interactions.gni <- SearchPairs( indexAnchor = anchors_Index.gnr, indexBait = baits_Index.gnr ) ## ----eval = TRUE, echo = FALSE----------------------------------------------- interactions.dtf <- interactions.gni |> as.data.frame() |> head(n=3L) interactions.dtf <- interactions.dtf[,-c(4,5,9,10)] interactions.dtf <- interactions.dtf[,c(1:11,13,12,17,16,18,15,14,20,19,21)] |> `colnames<-`(c( "seq","start","end", "seq","start","end", "name", "constraint" ,"distance", "orientation", "submatrix.name", "name", "bin", "Beaf.name", "Beaf.score", "Beaf.bln", "name", "bin", "Tss.name", "Tss.class", "Tss.bln" )) knitr::kable(x=interactions.dtf, align = "rccrccccccccccccccccc", digits = 1 ) |> kableExtra::add_header_above(c( #"Names", "First" = 3, "Second" = 3, "Interaction"=5, "Anchor"=5, "Bait"=5) ) |> kableExtra::add_header_above(c(#" ", "Ranges" = 6 , "Metadata"=15)) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Extractions_of_LRI.png") ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/LRI_GInteractions.png") ## ----eval = FALSE------------------------------------------------------------- # interactions_PFmatrix.lst <- ExtractSubmatrix( # genomicFeature = interactions.gni, # hicLst = HiC_Ctrl.cmx_lst, # referencePoint = "pf", # matriceDim = 41 # ) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/LRI_GRanges.png") ## ----eval = TRUE-------------------------------------------------------------- domains_PFmatrix.lst <- ExtractSubmatrix( genomicFeature = TADs_Domains.gnr, hicLst = HiC_Ctrl.cmx_lst, referencePoint = "pf", matriceDim = 41 ) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Extractions_of_Regions.png") ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Regions_GInteractions.png") ## ----eval = TRUE-------------------------------------------------------------- interactions_RFmatrix_ctrl.lst <- ExtractSubmatrix( genomicFeature = interactions.gni, hicLst = HiC_Ctrl.cmx_lst, hicResolution = NULL, referencePoint = "rf", matriceDim = 101 ) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Regions_GRanges.png") ## ----eval = FALSE------------------------------------------------------------- # domains_RFmatrix.lst <- ExtractSubmatrix( # genomicFeature = TADs_Domains.gnr, # hicLst = HiC_Ctrl.cmx_lst, # referencePoint = "rf", # matriceDim = 101, # cores = 1, # verbose = FALSE # ) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Extractions_of_Ponctuals_Interactions.png") ## ----eval = TRUE-------------------------------------------------------------- domains_Border.gnr <- c( GenomicRanges::resize(TADs_Domains.gnr, 1, "start"), GenomicRanges::resize(TADs_Domains.gnr, 1, "end" ) ) |> sort() ## ----eval = TRUE-------------------------------------------------------------- domains_Border_Bin.gnr <- BinGRanges( gRange = domains_Border.gnr, binSize = binSize, verbose = FALSE ) domains_Border_Bin.gnr$subname <- domains_Border_Bin.gnr$name domains_Border_Bin.gnr$name <- domains_Border_Bin.gnr$bin ## ----eval = FALSE------------------------------------------------------------- # domains_Border_Bin.gnr ## ----eval = TRUE, echo = FALSE------------------------------------------------ domains_Border_Bin.dtf <- domains_Border_Bin.gnr |> as.data.frame() |> head(n=3L) domains_Border_Bin.dtf <- domains_Border_Bin.dtf[,-c(4)] knitr::kable(domains_Border_Bin.dtf[,c(1:4,7,5,6,8,9)], col.names = c( "seq","start","end","strand", "name","score", "class","bin","subname"), align = "rcccccccc" ) ## ----eval = TRUE-------------------------------------------------------------- domains_Border_Bin.gni <- InteractionSet::GInteractions( domains_Border_Bin.gnr,domains_Border_Bin.gnr) ## ----eval = TRUE, echo = FALSE------------------------------------------------ domains_Border_Bin.dtf <- domains_Border_Bin.gni |> as.data.frame() |> head(n=3L) domains_Border_Bin.dtf <- domains_Border_Bin.dtf[,-c(4,5,9,10)] domains_Border_Bin.dtf[,c(1,2,3,9,7,8,10,11,4,5,6,14,13,12,15,16)] |> knitr::kable( col.names = c( "seq","start","end","name","score", "class", "bin", "subname", "seq","start","end","name","score", "class", "bin", "subname" ), align = "rccrccccccccccccccccc", digits = 1 ) |> kableExtra::add_header_above(c("First" = 8, "Second" = 8)) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Ponctuals_Interactions_GRanges.png") ## ----eval = FALSE------------------------------------------------------------- # border_PFmatrix.lst <- ExtractSubmatrix( # genomicFeature = domains_Border_Bin.gnr, # hicLst = HiC_Ctrl.cmx_lst, # referencePoint = "pf", # matriceDim = 101 # ) ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Ponctuals_Interactions_GInteractions.png") ## ----eval = FALSE------------------------------------------------------------- # border_PFmatrix.lst <- ExtractSubmatrix( # genomicFeature = domains_Border_Bin.gni, # hicLst = HiC_Ctrl.cmx_lst, # referencePoint = "pf", # matriceDim = 101 # ) ## ----eval = FALSE------------------------------------------------------------- # structureTarget.lst <- list( # first_colname_of_GInteraction = c("value"), # second_colname_of_GInteraction = function(eachElement){ # min_th as.data.frame() |> head(n=10L) interactions_RFmatrix_ctrl.dtf <- interactions_RFmatrix_ctrl.dtf[,-c(4,5,9,10)] interactions_RFmatrix_ctrl.dtf[,c(1:11,13,12,17,16,18,15,14,20,19,21)] |> knitr::kable( col.names = c( "seq","start","end", "seq","start","end", "name", "constraint" ,"distance", "orientation", "submatrix.name", "name", "bin", "Beaf.name", "Beaf.score", "Beaf.bln", "name", "bin", "Tss.name", "Tss.class", "Tss.bln" ), align = "rccrccccccccccccccccc", digits = 1 ) |> kableExtra::add_header_above(c( # "Names", "First" = 3, "Second" = 3, "Interaction"=5, "Anchor"=5, "Bait"=5) ) |> kableExtra::add_header_above(c(#" ", "Ranges" = 6, "Metadata"=15)) ## ----eval = TRUE-------------------------------------------------------------- targets <- list( anchor.Beaf.name = c("Beaf32_62","Beaf32_204"), bait.Tss.name = c("FBgn0015924","FBgn0264943"), name = c("2L:25_2L:22"), distance = function(columnElement){ return(20000==columnElement || columnElement == 40000) } ) ## ----eval = TRUE-------------------------------------------------------------- selectionFun = function(){ Reduce(intersect, list(anchor.Beaf.name, bait.Tss.name ,distance) ) |> setdiff(name) } ## ----eval = TRUE-------------------------------------------------------------- FilterInteractions( genomicInteractions = attributes(interactions_RFmatrix_ctrl.lst)$interactions, targets = targets, selectionFun = selectionFun ) ## ----eval = TRUE-------------------------------------------------------------- filtred_interactions_RFmatrix_ctrl.lst <- FilterInteractions( matrices = interactions_RFmatrix_ctrl.lst, targets = targets, selectionFun = selectionFun ) ## ----eval = TRUE-------------------------------------------------------------- first100_targets = list( submatrix.name = names(interactions_RFmatrix_ctrl.lst)[1:100] ) ## ----eval = TRUE-------------------------------------------------------------- FilterInteractions( genomicInteractions = attributes(interactions_RFmatrix_ctrl.lst)$interactions, targets = first100_targets, selectionFun = NULL ) |> head() ## ----eval = TRUE-------------------------------------------------------------- first100_interactions_RFmatrix_ctrl.lst <- FilterInteractions( matrices = interactions_RFmatrix_ctrl.lst, targets = first100_targets, selectionFun = NULL ) attributes(first100_interactions_RFmatrix_ctrl.lst)$interactions ## ----eval = TRUE-------------------------------------------------------------- attributes(interactions_RFmatrix_ctrl.lst[1:20])$interactions ## ----eval = TRUE-------------------------------------------------------------- nSample.num = 3 set.seed(123) targets = list(name=sample( attributes(interactions_RFmatrix_ctrl.lst)$interactions$name,nSample.num)) ## ----eval = TRUE-------------------------------------------------------------- FilterInteractions( genomicInteractions = attributes(interactions_RFmatrix_ctrl.lst)$interactions, targets = targets, selectionFun = NULL ) ## ----eval = TRUE-------------------------------------------------------------- sampled_interactions_RFmatrix_ctrl.lst <- FilterInteractions( matrices = interactions_RFmatrix_ctrl.lst, targets = targets, selectionFun = NULL ) attributes(sampled_interactions_RFmatrix_ctrl.lst)$interactions ## ----eval = TRUE-------------------------------------------------------------- targets <- list( anchor.Beaf.name = c("Beaf32_8","Beaf32_15"), bait.Tss.name = c("FBgn0031214","FBgn0005278"), name = c("2L:74_2L:77"), distance = function(columnElement){ return(14000==columnElement || columnElement == 3000) } ) ## ----eval = TRUE-------------------------------------------------------------- FilterInteractions( genomicInteractions = attributes(interactions_RFmatrix_ctrl.lst)$interactions, targets = targets, selectionFun = NULL ) |> str() ## ----eval = TRUE-------------------------------------------------------------- FilterInteractions( matrices = interactions_RFmatrix_ctrl.lst, targets = targets, selectionFun = NULL ) |> str() ## ----eval = TRUE-------------------------------------------------------------- a <- c("A","B","D","G") b <- c("E","B","C","G") c <- c("A","F","C","G") ## ----eval = TRUE-------------------------------------------------------------- Reduce(intersect, list(a,b,c)) |> sort() intersect(a,b) |> intersect(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- Reduce(union, list(a,b,c)) |> sort() union(a,b) |> union(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- Reduce(setdiff,list(a,b,c)) |> sort() setdiff(a,b) |> setdiff(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- intersect(a,b) |> setdiff(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- intersect(a,b) |> union(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- union(a,b) |> intersect(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- union(a,b) |> setdiff(c) |> sort() ## ----eval = TRUE-------------------------------------------------------------- d <- c(a,b,c) setdiff(d,d[duplicated(d)]) |> sort() ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Orientation_extraction.png") ## ----eval = TRUE, echo = FALSE------------------------------------------------ knitr::include_graphics("images/Orientation.png") ## ----eval = FALSE------------------------------------------------------------- # # mcols(attributes( # # first100_interactions_RFmatrix_ctrl.lst)$interactions)$orientation ## ----eval = TRUE-------------------------------------------------------------- oriented_first100_interactions_RFmatrix_ctrl.lst <- OrientateMatrix(first100_interactions_RFmatrix_ctrl.lst) ## ----eval = FALSE------------------------------------------------------------- # orientedMatrix.mtx <- # OrientateMatrix(first100_interactions_RFmatrix_ctrl.lst[[1]]) ## ----eval = TRUE-------------------------------------------------------------- oriented_quantiled_first100_interactions_RFmatrix_ctrl.lst <- PrepareMtxList( first100_interactions_RFmatrix_ctrl.lst, transFun = 'quantile', orientate = TRUE) oriented_first100_interactions_RFmatrix_ctrl.lst <- PrepareMtxList( first100_interactions_RFmatrix_ctrl.lst, orientate = TRUE) ## ----eval = TRUE-------------------------------------------------------------- center.num <- GetQuantif( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, areaFun = "center", operationFun = "mean" ) ## ----eval = TRUE-------------------------------------------------------------- GetQuantif( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, areaFun = function(matrice.mtx){matrice.mtx[33:35,67:69]}, operationFun = function(area.mtx){ area.mtx[which(area.mtx==0)]<-NA; return(mean(area.mtx,na.rm=TRUE)) } ) |> c() |> unlist() |> head() ## ----eval = TRUE-------------------------------------------------------------- namedCenter.num <- GetQuantif( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, areaFun = "center", operationFun = "mean", varName = "anchor.Beaf.name" ) ## ----eval = TRUE, echo = FALSE------------------------------------------------ S4Vectors::mcols(attributes( oriented_first100_interactions_RFmatrix_ctrl.lst)$interactions)[ 45:50,c("name","anchor.Beaf.name")] |> `row.names<-`(45:50) |> knitr::kable(align = "cc", digits = 1) ## ----eval = TRUE-------------------------------------------------------------- unlist(c(center.num))[45:50] unlist(c(namedCenter.num))[45:51] ## ----eval = TRUE-------------------------------------------------------------- attributes(center.num)$duplicated attributes(namedCenter.num)$duplicated ## ----eval = TRUE-------------------------------------------------------------- GetQuantif( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, areaFun = function(matrice.mtx){matrice.mtx[5,5]}, operationFun = function(area.mtx){area.mtx} ) |> head() ## ----eval = TRUE-------------------------------------------------------------- GetQuantif( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, areaFun = function(matrice.mtx){matrice.mtx[4:6,4:6]}, operationFun = function(area){area} ) |> head() ## ----eval = TRUE-------------------------------------------------------------- GetQuantif( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, areaFun = function(matrice.mtx){matrice.mtx[4:6,4:6]}, operationFun = NULL ) |> head() ## ----eval = TRUE-------------------------------------------------------------- # rm0 argument can be added to PrepareMtxList to assign NA to 0 values. oriented_first100_interactions_RFmatrix_ctrl.lst = PrepareMtxList( oriented_first100_interactions_RFmatrix_ctrl.lst, rm0 = FALSE) agg_sum.mtx <- Aggregation( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, aggFun = "sum" ) ## ----eval = TRUE-------------------------------------------------------------- agg_mean.mtx <- Aggregation( matrices = oriented_first100_interactions_RFmatrix_ctrl.lst, aggFun = function(x){mean(x,na.rm=TRUE)} ) ## ----eval = FALSE------------------------------------------------------------- # first100_targets = list( # submatrix.name = names(interactions_RFmatrix_ctrl.lst)[1:100] # ) # first100_interactions_RFmatrix_ctrl.lst <- FilterInteractions( # matrices = interactions_RFmatrix_ctrl.lst, # targets = first100_targets, # selectionFun = NULL # ) ## ----eval = FALSE------------------------------------------------------------- # oriented_first100_interactions_RFmatrix_ctrl.lst <- # OrientateMatrix(first100_interactions_RFmatrix_ctrl.lst) ## ----eval = TRUE-------------------------------------------------------------- interactions_RFmatrix.lst <- ExtractSubmatrix( genomicFeature = interactions.gni, hicLst = HiC_HS.cmx_lst, referencePoint = "rf", matriceDim = 101 ) ## ----eval = TRUE-------------------------------------------------------------- first100_interactions_RFmatrix.lst <- FilterInteractions( matrices = interactions_RFmatrix.lst, targets = first100_targets, selectionFun = NULL ) ## ----eval = TRUE-------------------------------------------------------------- oriented_first100_interactions_RFmatrix.lst <- OrientateMatrix(first100_interactions_RFmatrix.lst) ## ----eval = TRUE-------------------------------------------------------------- oriented_first100_interactions_RFmatrix_ctrl.lst = PrepareMtxList(first100_interactions_RFmatrix_ctrl.lst, minDist = NULL, maxDist = NULL, rm0 = FALSE, orientate = TRUE ) oriented_first100_interactions_RFmatrix.lst = PrepareMtxList(first100_interactions_RFmatrix.lst, minDist = NULL, maxDist = NULL, rm0 = FALSE, orientate = TRUE ) diffAggreg.mtx <- Aggregation( ctrlMatrices = oriented_first100_interactions_RFmatrix_ctrl.lst, matrices = oriented_first100_interactions_RFmatrix.lst, aggFun = "mean", diffFun = "substraction", scaleCorrection = TRUE, correctionArea = list( i = c(1:30), j = c(72:101) ), statCompare = TRUE) ## ----------------------------------------------------------------------------- aggreg.mtx <- Aggregation( ctrlMatrices=interactions_RFmatrix_ctrl.lst, aggFun="mean" ) ## ----------------------------------------------------------------------------- oriented_interactions_RFmatrix_ctrl.lst <- OrientateMatrix(interactions_RFmatrix_ctrl.lst) orientedAggreg.mtx <- Aggregation( ctrlMatrices=oriented_interactions_RFmatrix_ctrl.lst, aggFun="mean" ) ## ----------------------------------------------------------------------------- oriented_interactions_RFmatrix.lst <- OrientateMatrix(interactions_RFmatrix.lst) diffAggreg.mtx <- Aggregation( ctrlMatrices = oriented_interactions_RFmatrix_ctrl.lst, matrices = oriented_interactions_RFmatrix.lst, aggFun = "mean", diffFun = "log2+1", scaleCorrection = TRUE, correctionArea = list( i=c(1:30) , j=c(72:101) ), statCompare = TRUE ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = aggreg.mtx, title = "APA" ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA" ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA 30% trimmed on upper side", trim = 30, tails = "upper" ) ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA 30% trimmed on upper side", trim = 30, tails = "lower" ) ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA 30% trimmed", trim = 30, tails = "both" ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA [0-1]", colMin = 0, colMax = 1 ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA center on 0.2", colMid = 0.5 ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA [0, .25, .50, .30, .75, 1]", colBreaks = c(0,0.25,0.5,0.75,1) ) ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA [0, .15, .20, .25, 1]", colBreaks = c(0,0.15,0.20,0.25,1) ) ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA [0, .5, .6, .8, 1]", colBreaks = c(0,0.4,0.5,0.7,1) ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA", colorScale = "density" ) ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA", bias = 2 ) ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA", bias = 0.5 ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA", colors = viridis(6), na.value = "black" ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA", blurPass = 1, stdev = 0.5, loTri = NA ) ## ----fig.dim = c(7,7)--------------------------------------------------------- ggAPA( aggregatedMtx = orientedAggreg.mtx, title = "APA", ) + ggplot2::labs( title = "New title", subtitle = "and subtitle" ) ## ----eval = TRUE-------------------------------------------------------------- sessionInfo()