# HG changeset patch # User artbio # Date 1710023566 0 # Node ID 6bba3e33c2e771791b751bf8fac70acd94244323 # Parent 6f41438934635cf5debf19a97e0694b23b46d423 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/repenrich commit 11df9f0b68d35d3a9424a17e4cefee6cfb9d4c19 diff -r 6f4143893463 -r 6bba3e33c2e7 RepEnrich_setup.py --- a/RepEnrich_setup.py Tue Feb 05 17:20:55 2019 -0500 +++ b/RepEnrich_setup.py Sat Mar 09 22:32:46 2024 +0000 @@ -7,7 +7,6 @@ import sys from Bio import SeqIO -from Bio.Alphabet import IUPAC from Bio.Seq import Seq from Bio.SeqRecord import SeqRecord @@ -242,7 +241,7 @@ print("Unrecognised Chromosome: "+chr) pass # Convert metagenome to SeqRecord object (required by SeqIO.write) - record = SeqRecord(Seq(metagenome, IUPAC.unambiguous_dna), id="repname", + record = SeqRecord(Seq(metagenome), id="repname", name="", description="") print("saving repgenome " + newname + ".fa" + " (" + str(k) + " of " + str(nrepgenomes) + ")") diff -r 6f4143893463 -r 6bba3e33c2e7 edgeR_repenrich.R --- a/edgeR_repenrich.R Tue Feb 05 17:20:55 2019 -0500 +++ b/edgeR_repenrich.R Sat Mar 09 22:32:46 2024 +0000 @@ -1,228 +1,192 @@ -#!/usr/bin/env Rscript - -# A command-line interface to edgeR for use with Galaxy edger-repenrich -# written by Christophe Antoniewski drosofff@gmail.com 2017.05.30 - - # setup R error handling to go to stderr -options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) +options(show.error.messages = FALSE, error = function() { + cat(geterrmessage(), file = stderr()) + q("no", 1, FALSE) +}) # To not crash galaxy with an UTF8 error with not-US LC settings. loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") +# load libraries library("getopt") library("tools") +library("rjson") +suppressPackageStartupMessages({ + library("edgeR") + library("limma") +}) + options(stringAsFactors = FALSE, useFancyQuotes = FALSE) -args <- commandArgs(trailingOnly = TRUE) # get options, using the spec as defined by the enclosed list. # we read the options from the default: commandArgs(TRUE). -spec <- matrix(c( - "quiet", "q", 0, "logical", - "help", "h", 0, "logical", - "outfile", "o", 1, "character", - "countsfile", "n", 1, "character", - "factorName", "N", 1, "character", - "levelNameA", "A", 1, "character", - "levelNameB", "B", 1, "character", - "levelAfiles", "a", 1, "character", - "levelBfiles", "b", 1, "character", - "alignmentA", "i", 1, "character", - "alignmentB", "j", 1, "character", - "plots" , "p", 1, "character"), - byrow=TRUE, ncol=4) +spec <- matrix( + c( + "quiet", "q", 0, "logical", + "outfile", "o", 1, "character", + "countsfile", "n", 1, "character", + "factorName", "N", 1, "character", + "levelNameA", "A", 1, "character", + "levelNameB", "B", 1, "character", + "levelAfiles", "a", 1, "character", + "levelBfiles", "b", 1, "character", + "alignmentA", "i", 1, "character", + "alignmentB", "j", 1, "character", + "plots", "p", 1, "character" + ), + byrow = TRUE, ncol = 4 +) opt <- getopt(spec) -# if help was asked for print a friendly message -# and exit with a non-zero error code -if (!is.null(opt$help)) { - cat(getopt(spec, usage=TRUE)) - q(status=1) -} - -# enforce the following required arguments -if (is.null(opt$outfile)) { - cat("'outfile' is required\n") - q(status=1) -} -if (is.null(opt$levelAfiles) | is.null(opt$levelBfiles)) { - cat("input count files are required for both levels\n") - q(status=1) -} -if (is.null(opt$alignmentA) | is.null(opt$alignmentB)) { - cat("total aligned read files are required for both levels\n") - q(status=1) -} - -verbose <- if (is.null(opt$quiet)) { - TRUE -} else { - FALSE -} - -suppressPackageStartupMessages({ - library("edgeR") - library("limma") -}) - # build levels A and B file lists - -library("rjson") filesA <- fromJSON(opt$levelAfiles, method = "C", unexpected.escape = "error") filesB <- fromJSON(opt$levelBfiles, method = "C", unexpected.escape = "error") listA <- list() -indice = 0 +indice <- 0 listA[["level"]] <- opt$levelNameA for (file in filesA) { - indice = indice +1 - listA[[paste0(opt$levelNameA,"_",indice)]] <- read.delim(file, header=FALSE) - } + indice <- indice + 1 + listA[[paste0(opt$levelNameA, "_", indice)]] <- read.delim(file, header = FALSE) +} listB <- list() -indice = 0 +indice <- 0 listB[["level"]] <- opt$levelNameB for (file in filesB) { - indice = indice +1 - listB[[paste0(opt$levelNameB,"_",indice)]] <- read.delim(file, header=FALSE) - } + indice <- indice + 1 + listB[[paste0(opt$levelNameB, "_", indice)]] <- read.delim(file, header = FALSE) +} # build a counts table -counts <- data.frame(row.names=listA[[2]][,1]) +counts <- data.frame(row.names = listA[[2]][, 1]) for (element in names(listA[-1])) { - counts<-cbind(counts, listA[[element]][,4]) - } + counts <- cbind(counts, listA[[element]][, 4]) +} for (element in names(listB[-1])) { - counts<-cbind(counts, listB[[element]][,4]) - } -colnames(counts)=c(names(listA[-1]), names(listB[-1])) + counts <- cbind(counts, listB[[element]][, 4]) +} +colnames(counts) <- c(names(listA[-1]), names(listB[-1])) # build aligned counts vector - filesi <- fromJSON(opt$alignmentA, method = "C", unexpected.escape = "error") filesj <- fromJSON(opt$alignmentB, method = "C", unexpected.escape = "error") sizes <- c() for (file in filesi) { - sizes <- c(sizes, read.delim(file, header=TRUE)[1,1]) - } + sizes <- c(sizes, read.delim(file, header = TRUE)[1, 1]) +} for (file in filesj) { - sizes <- c(sizes, read.delim(file, header=TRUE)[1,1]) - } + sizes <- c(sizes, read.delim(file, header = TRUE)[1, 1]) +} # build a meta data object - meta <- data.frame( - row.names=colnames(counts), - condition=c(rep(opt$levelNameA,length(filesA)), rep(opt$levelNameB,length(filesB)) ), - libsize=sizes + row.names = colnames(counts), + condition = c(rep(opt$levelNameA, length(filesA)), rep(opt$levelNameB, length(filesB))), + libsize = sizes ) # Define the library size and conditions for the GLM libsize <- meta$libsize condition <- factor(meta$condition) -design <- model.matrix(~0+condition) -colnames(design) <- levels(meta$condition) - +design <- model.matrix(~ 0 + condition) +colnames(design) <- levels(condition) # Build a DGE object for the GLM -y <- DGEList(counts=counts, lib.size=libsize) +y <- DGEList(counts = counts, lib.size = libsize) # Normalize the data y <- calcNormFactors(y) -y$samples -# plotMDS(y) latter # Estimate the variance y <- estimateGLMCommonDisp(y, design) y <- estimateGLMTrendedDisp(y, design) y <- estimateGLMTagwiseDisp(y, design) -# plotBCV(y) latter # Builds and outputs an object to contain the normalized read abundance in counts per million of reads -cpm <- cpm(y, log=FALSE, lib.size=libsize) +cpm <- cpm(y, log = FALSE, lib.size = libsize) cpm <- as.data.frame(cpm) colnames(cpm) <- colnames(counts) if (!is.null(opt$countsfile)) { - normalizedAbundance <- data.frame(Tag=rownames(cpm)) + normalizedAbundance <- data.frame(Tag = rownames(cpm)) normalizedAbundance <- cbind(normalizedAbundance, cpm) - write.table(normalizedAbundance, file=opt$countsfile, sep="\t", col.names=TRUE, row.names=FALSE, quote=FALSE) + write.table(normalizedAbundance, file = opt$countsfile, sep = "\t", col.names = TRUE, row.names = FALSE, quote = FALSE) } # Conduct fitting of the GLM yfit <- glmFit(y, design) # Initialize result matrices to contain the results of the GLM -results <- matrix(nrow=dim(counts)[1],ncol=0) -logfc <- matrix(nrow=dim(counts)[1],ncol=0) +results <- matrix(nrow = dim(counts)[1], ncol = 0) +logfc <- matrix(nrow = dim(counts)[1], ncol = 0) # Make the comparisons for the GLM my.contrasts <- makeContrasts( - paste0(opt$levelNameA,"_",opt$levelNameB," = ", opt$levelNameA, " - ", opt$levelNameB), + paste0(opt$levelNameA, "_", opt$levelNameB, " = ", opt$levelNameA, " - ", opt$levelNameB), levels = design ) # Define the contrasts used in the comparisons -allcontrasts = paste0(opt$levelNameA," vs ",opt$levelNameB) +allcontrasts <- paste0(opt$levelNameA, " vs ", opt$levelNameB) # Conduct a for loop that will do the fitting of the GLM for each comparison # Put the results into the results objects - lrt <- glmLRT(yfit, contrast=my.contrasts[,1]) - plotSmear(lrt, de.tags=rownames(y)) - title(allcontrasts) - res <- topTags(lrt,n=dim(c)[1],sort.by="none")$table - results <- cbind(results,res[,c(1,5)]) - logfc <- cbind(logfc,res[c(1)]) +lrt <- glmLRT(yfit, contrast = my.contrasts[, 1]) +res <- topTags(lrt, n = dim(c)[1], sort.by = "none")$table +results <- cbind(results, res[, c(1, 5)]) +logfc <- cbind(logfc, res[c(1)]) # Add the repeat types back into the results. # We should still have the same order as the input data -results$class <- listA[[2]][,2] -results$type <- listA[[2]][,3] - +results$class <- listA[[2]][, 2] +results$type <- listA[[2]][, 3] # Sort the results table by the FDR results <- results[with(results, order(FDR)), ] -# Save the results -write.table(results, opt$outfile, quote=FALSE, sep="\t", col.names=FALSE) - # Plot Fold Changes for repeat classes and types # open the device and plots if (!is.null(opt$plots)) { - if (verbose) cat("creating plots\n") pdf(opt$plots) - plotMDS(y, main="Multidimensional Scaling Plot Of Distances Between Samples") - plotBCV(y, xlab="Gene abundance (Average log CPM)", main="Biological Coefficient of Variation Plot") + plotMDS(y, main = "Multidimensional Scaling Plot Of Distances Between Samples") + plotBCV(y, xlab = "Gene abundance (Average log CPM)", main = "Biological Coefficient of Variation Plot") logFC <- results[, "logFC"] # Plot the repeat classes classes <- with(results, reorder(class, -logFC, median)) classes - par(mar=c(6,10,4,1)) - boxplot(logFC ~ classes, data=results, outline=FALSE, horizontal=TRUE, - las=2, xlab="log2(Fold Change)", main=paste0(allcontrasts, ", by Class")) - abline(v=0) + par(mar = c(6, 10, 4, 1)) + boxplot(logFC ~ classes, + data = results, outline = FALSE, horizontal = TRUE, + las = 2, xlab = "log2(Fold Change)", ylab = "", cex.axis = 0.7, main = paste0(allcontrasts, ", by Class") + ) + abline(v = 0) # Plot the repeat types types <- with(results, reorder(type, -logFC, median)) - boxplot(logFC ~ types, data=results, outline=FALSE, horizontal=TRUE, - las=2, xlab="log2(Fold Change)", main=paste0(allcontrasts, ", by Type"), yaxt="n") - axis(2, cex.axis=(1*28)/(length(levels(types))), - at=seq(from=1, to=length(levels(types))), - labels=levels(types), las=2) - abline(v=0) + boxplot(logFC ~ types, + data = results, outline = FALSE, horizontal = TRUE, + las = 2, xlab = "log2(Fold Change)", ylab = "", cex.axis = 0.7, main = paste0(allcontrasts, ", by Type") + ) + abline(v = 0) # volcano plot - TEdata = cbind(rownames(results), as.data.frame(results), score=-log(results$FDR, 10)) - colnames(TEdata) = c("Tag","log2FC", "FDR", "Class", "Type", "score") - color = ifelse(TEdata$FDR<0.05, "red", "black") - s <- subset(TEdata, FDR<0.01) - with(TEdata, plot(log2FC, score, pch=20, col=color, main="Volcano plot (all tag types)", ylab="-log10(FDR)")) - text(s[,2], s[,6], labels = s[,5], pos = seq(from=1, to=3), cex=0.5) + TEdata <- cbind(rownames(results), as.data.frame(results), score = -log(results$FDR, 10)) + colnames(TEdata) <- c("Tag", "log2FC", "FDR", "Class", "Type", "score") + color <- ifelse(TEdata$FDR < 0.05, "red", "black") + s <- subset(TEdata, FDR < 0.01) + with(TEdata, plot(log2FC, score, pch = 20, col = color, main = "Volcano plot (all tag types)", ylab = "-log10(FDR)")) + text(s[, 2], s[, 6], labels = s[, 5], pos = seq(from = 1, to = 3), cex = 0.5) } # close the plot device if (!is.null(opt$plots)) { - cat("closing plot device\n") - dev.off() + cat("closing plot device\n") + dev.off() } -cat("Session information:\n\n") +# Save the results +results <- cbind(TE_item = rownames(results), results) +colnames(results) <- c("TE_item", "log2FC", "FDR", "Class", "Type") +results$log2FC <- format(results$log2FC, digits = 5) +results$FDR <- format(results$FDR, digits = 5) +write.table(results, opt$outfile, quote = FALSE, sep = "\t", col.names = TRUE, row.names = FALSE) +cat("Session information:\n\n") sessionInfo() - diff -r 6f4143893463 -r 6bba3e33c2e7 edger-repenrich.xml --- a/edger-repenrich.xml Tue Feb 05 17:20:55 2019 -0500 +++ b/edger-repenrich.xml Sat Mar 09 22:32:46 2024 +0000 @@ -1,11 +1,9 @@ - + Determines differentially expressed features from RepEnrich counts - - bioconductor-edger - bioconductor-limma - r-getopt - r-rjson - + + macros.xml + + - + diff -r 6f4143893463 -r 6bba3e33c2e7 macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Sat Mar 09 22:32:46 2024 +0000 @@ -0,0 +1,18 @@ + + 1.83 + 0 + 23.0 + + + + bioconductor-edger + bioconductor-limma + r-getopt + r-rjson + bowtie + samtools + bedtools + biopython + + + diff -r 6f4143893463 -r 6bba3e33c2e7 repenrich.xml --- a/repenrich.xml Tue Feb 05 17:20:55 2019 -0500 +++ b/repenrich.xml Sat Mar 09 22:32:46 2024 +0000 @@ -1,11 +1,9 @@ - + Repeat Element Profiling - - bowtie - samtools - bedtools - biopython - + + macros.xml + + @@ -55,11 +53,8 @@ echo -e "# Total reads aligned to repeated sequences\n" > bowtie_aligned.numb && echo \$((\$TOTAL-\$NONALIGNED)) >> bowtie_aligned.numb && #end if - samtools view -bS ${input_base}_unique.sam > ${input_base}_unique.bam && - samtools sort ${input_base}_unique.bam ${input_base}_unique_sorted && - mv ${input_base}_unique_sorted.bam ${input_base}_unique.bam && + samtools view -@ \${GALAXY_SLOTS:-4} -bS '${input_base}_unique.sam' | samtools sort -@ \${GALAXY_SLOTS:-4} -O bam -o '${input_base}_unique.bam' && samtools index ${input_base}_unique.bam && - rm ${input_base}_unique.sam && #if $seq_method.seq_method_list == "single-read": python $__tool_directory__/RepEnrich.py $repeatmasker ${input_base} ${input_base} setup_folder_${baseReference} ${input_base}_multimap.fastq ${input_base}_unique.bam --cpus "\${GALAXY_SLOTS:-4}" && #else: diff -r 6f4143893463 -r 6bba3e33c2e7 test-data/Normalized_counts_file.tab --- a/test-data/Normalized_counts_file.tab Tue Feb 05 17:20:55 2019 -0500 +++ b/test-data/Normalized_counts_file.tab Sat Mar 09 22:32:46 2024 +0000 @@ -14,18 +14,18 @@ BEL_I-int 1148.97283940843 1304.98396962057 1022.22666828812 1059.36800967358 BEL_LTR 36.3043773308206 51.9691483425779 37.6498857074591 41.5799520722748 Bica_I-int 61.1339083208317 53.0858407863027 79.6886723773878 67.3614608163893 -Bica_LTR 4.81708566525451 5.7552610561202 6.02398171319346 6.05768532521486 +Bica_LTR 4.81708566525452 5.7552610561202 6.02398171319346 6.05768532521486 BLASTOPIA_I-int 539.670247700872 1034.65849882041 443.580196295081 462.322544020398 BLASTOPIA_LTR 40.6515034189771 78.9415658294696 23.6656424446886 23.1645886836216 BLOOD_I-int 1071.58616237963 1140.74428097427 960.825083254357 834.603653366803 -BLOOD_LTR 49.6982252781136 46.55748496145 32.1852737247765 36.1522660208823 +BLOOD_LTR 49.6982252781137 46.55748496145 32.1852737247765 36.1522660208823 BS 203.649150075801 355.194096523239 313.935504138996 242.355874491196 BS2 204.197436249082 179.186187508459 240.744126323696 241.871259665179 BS3_DM 33.3279666758666 38.9124366928724 53.871607892273 42.5007202417075 BS4_DM 0.313306384732001 1.97568663120544 1.46296698748984 1.0176911346361 BURDOCK_I-int 203.257517094886 191.727502645676 134.205706881789 161.473660028927 BURDOCK_LTR 21.2656708636846 16.5785878183761 12.3491625120466 17.930748562636 -Chimpo_I-int 53.4970651929892 31.7827849367832 55.4206317613798 51.369171557822 +Chimpo_I-int 53.4970651929892 31.7827849367832 55.4206317613799 51.369171557822 Chimpo_LTR 4.19047289579051 2.83468081868607 4.04467343600132 5.81537791220627 Chouto_I-int 48.2100199506366 44.4958989114965 72.7180649664068 63.1937733126415 Chouto_LTR 6.34445429082302 13.658007580942 12.8655038017489 13.617676611083 @@ -49,9 +49,9 @@ DM412 1711.00533031955 2019.32353592946 1036.38302531413 1142.04329899211 DM412B_LTR 219.588612399041 257.784155662936 132.441540808639 141.022914371002 DMCR1A 684.926920322246 693.380108134362 876.919623677734 870.222843079066 -DMLTR5 7.40186333929352 8.07454536231789 6.92757897017248 7.75383721627503 +DMLTR5 7.40186333929352 8.07454536231789 6.92757897017248 7.75383721627502 DMRP1 11.5531729369925 12.369516299721 11.2734514918335 11.0007565505902 -DMRPR 8.65508887822152 11.6823209497365 5.50764042349117 9.06229724652144 +DMRPR 8.65508887822153 11.6823209497365 5.50764042349117 9.06229724652144 DMRT1A 148.703042853426 106.085782153857 191.734732242786 171.553648410085 DMRT1B 352.587172717776 353.476108148278 417.634046487541 344.997294641637 DMRT1C 74.6844094604907 57.552610561202 108.861955245568 101.139114189787 @@ -71,11 +71,11 @@ FW2_DM 694.091132075657 761.412447782827 612.466826468541 671.046149586002 FW3_DM 25.3386538652006 32.2981814492716 35.756634311884 44.2453336153694 G_DM 428.759787505743 393.591136703623 383.168265399913 389.388012704811 -G2_DM 48.3666731430026 65.6271559235199 57.1417693937208 54.8583983051458 +G2_DM 48.3666731430027 65.6271559235199 57.1417693937208 54.8583983051458 G3_DM 18.7983830839201 21.4748546870157 34.2936673243942 26.9445843265557 G4_DM 87.0600116574048 105.226787966377 157.828320885669 165.108271224056 G5_DM 106.289191020331 111.669244372481 111.916974542973 123.625242116985 -G5A_DM 61.7996843883872 49.9934617113725 77.6233072185786 77.2960647497417 +G5A_DM 61.7996843883872 49.9934617113725 77.6233072185786 77.2960647497416 G6_DM 112.555318714971 67.5169431359773 207.698283782749 168.30672907577 G7_DM 76.3292679803337 35.9059570366902 6.97060741098101 4.74922529496845 GTWIN_I-int 296.387839956473 251.685296931824 234.418945524843 244.924333069087 @@ -97,7 +97,7 @@ Gypsy2-LTR_DM 45.2336092956826 33.0712762180041 41.5654738210349 33.438422995186 Gypsy3_I-int 225.81557679559 193.960887533126 146.253670308176 133.414461602532 Gypsy3_LTR 26.6702060003116 18.2106767745893 24.354097497625 21.6622827229683 -Gypsy4_I-int 513.587491171932 459.390091464639 521.20350351366 487.328669042885 +Gypsy4_I-int 513.587491171933 459.390091464639 521.20350351366 487.328669042885 Gypsy4_LTR 15.273686255685 18.7260732870777 11.7897927815358 9.40152762473347 Gypsy5_I-int 110.988786791311 88.9917978229929 105.333623099269 105.936800967358 Gypsy5_LTR 19.6599756419331 28.0032105118684 28.0115149663496 21.8561286533752 @@ -106,14 +106,14 @@ Gypsy6A_LTR 31.0564953865596 18.8119727058257 26.5485479788598 27.7684295307849 Gypsy7_I-int 45.5077523823231 63.7373687110625 54.0437216555071 48.8976359451344 Gypsy7_LTR 3.13306384732001 3.35007733117444 4.81918537055477 4.21614898634954 -Gypsy8_I-int 163.545932830104 107.116575178834 206.923771848195 197.868233462818 +Gypsy8_I-int 163.545932830105 107.116575178834 206.923771848195 197.868233462818 Gypsy8_LTR 57.4525583002307 41.7471175115585 56.4102858999759 60.1406999087332 -Gypsy9_I-int 16.8010548812535 16.1490907246358 21.6863341674965 22.9707427532148 +Gypsy9_I-int 16.8010548812536 16.1490907246358 21.6863341674965 22.9707427532148 Gypsy9_LTR 2.42812448167301 0.687195349984501 2.19445048123476 2.03538226927219 HELENA_RT 36.5785204174611 35.7341581991941 28.0975718479666 30.3853495912778 Helitron1_DM 0 0 0.129085322425574 0.290768895610313 HETA 879.568511837001 887.083297411243 990.729849616282 1182.31479103414 -HMSBEAGLE_I-int 307.941012893465 350.383729073348 311.48288301291 286.310439210955 +HMSBEAGLE_I-int 307.941012893465 350.383729073348 311.482883012911 286.310439210955 HOBO 171.339429150313 182.020868327145 216.476085707688 213.42436937797 I_DM 449.55549879233 957.692619622151 343.668156737687 339.860377485855 IDEFIX_I-int 282.837338816814 282.265490006134 266.475133927194 268.815843991735 @@ -134,7 +134,7 @@ Jockey2 71.3946924208047 65.2835582485276 76.1603402310888 76.9568343715296 LINEJ1_DM 974.813652795529 1369.15083542537 302.274796679886 306.712723386279 LmeSINE1c 24.5553879033706 56.0923204424849 25.7740360443063 68.5245363988305 -LOOPER1_DM 8.61592558013002 2.66288198118994 35.3263499037988 28.5438132524124 +LOOPER1_DM 8.61592558013003 2.66288198118994 35.3263499037988 28.5438132524124 LSU-rRNA_Cel 14243.5740259843 21618.3926157437 22382.0179984887 15843.270199567 LSU-rRNA_Dme 218650.181450173 354466.098949349 157455.221275418 149201.031867455 LSU-rRNA_Hsa 0.587449471372502 0.944893606228689 0.215142204042624 0 @@ -152,7 +152,7 @@ MuDR-1_DEl 1.253225538928 0.343597674992251 0.258170644851148 0.43615334341547 NINJA_I-int 143.964283784354 98.4407338852798 226.931996824159 218.22205615554 NINJA_LTR 11.6314995331755 9.79253373727915 21.1269644369856 19.6753619362979 -NOF_FB 8.92923196486203 5.41166338112795 54.7321767084434 46.5230232976501 +NOF_FB 8.92923196486203 5.41166338112795 54.7321767084435 46.5230232976501 NOMAD_I-int 454.842544034682 700.423860471703 708.635391675594 561.862429284329 NOMAD_LTR 29.6466166552656 23.7941389932134 26.6346048604768 39.8353386986129 NTS_DM 2194.82871494194 1868.57005602661 2837.89778508544 1754.54797759523 diff -r 6f4143893463 -r 6bba3e33c2e7 test-data/edgeR_plots.pdf Binary file test-data/edgeR_plots.pdf has changed diff -r 6f4143893463 -r 6bba3e33c2e7 test-data/edgeR_result_file.tab --- a/test-data/edgeR_result_file.tab Tue Feb 05 17:20:55 2019 -0500 +++ b/test-data/edgeR_result_file.tab Sat Mar 09 22:32:46 2024 +0000 @@ -1,210 +1,211 @@ -DM297_I-int 2.69047105438237 4.49448726299278e-21 LTR Gypsy -DM297_LTR 1.74961921158059 1.33970311552449e-18 LTR Gypsy -Gypsy1-I_DM 2.37388633230267 4.48026988291108e-16 LTR Gypsy -NOF_FB -2.79644759297337 4.48026988291108e-16 DNA MULE-NOF -G7_DM 3.25987374806405 1.55296802933692e-15 LINE Jockey -Gypsy_I-int 1.74702179622354 4.35250852545265e-12 LTR Gypsy -LINEJ1_DM 1.94429217926762 5.18070558194078e-12 LINE Jockey -TOM_I-int 1.33935222283437 6.6922795621824e-12 LTR Gypsy -GTWIN_LTR 1.89490932455113 8.80590960313784e-12 LTR Gypsy -Gypsy_LTR 1.56024435809038 2.99852403114994e-11 LTR Gypsy -DM1731_I-int 1.53134429520835 6.4920552091728e-10 LTR Copia -Gypsy6_LTR 1.53023046204423 1.07509345482848e-06 LTR Gypsy -LOOPER1_DM -2.46983670012103 1.61917280285007e-06 DNA PiggyBac -TIRANT_LTR 1.12203469288475 1.78012665029166e-06 LTR Gypsy -Gypsy12_I-int -1.12204057066646 2.19485691074579e-06 LTR Gypsy -R2_DM 1.67889583354494 2.73035057005978e-06 LINE R2 -TRANSPAC_LTR 1.49364968145495 2.9021047542613e-06 LTR Gypsy -Copia_LTR 1.66649088148806 1.18604111278586e-05 LTR Copia -ACCORD_LTR 1.3724059468295 1.75953804703817e-05 LTR Gypsy -TIRANT_I-int 1.17728139313168 2.04686461971632e-05 LTR Gypsy -TART_B1 -1.14695345949677 3.09658484730011e-05 LINE Jockey -TRANSIB1 -1.3902119423097 6.16503339250305e-05 DNA CMC-Transib -DM412B_LTR 0.803090050933452 0.00012443453312414 LTR Gypsy -MICROPIA_LTR -1.29556276189806 0.000129852108160169 LTR Gypsy -G6_DM -1.05894868960943 0.000138305097075584 LINE Jockey -NINJA_I-int -0.874264518473233 0.000155536374046075 LTR Pao -R1_DM 0.955905154410719 0.000189845334697796 LINE R1 -Invader6_LTR -1.18865109431199 0.000212988712815497 LTR Gypsy -Copia_I-int 1.9331690527025 0.000223130721644621 LTR Copia -BLASTOPIA_LTR 1.34881958569428 0.000364879309201161 LTR Gypsy -LSU-rRNA_Hsa 2.61189118344978 0.000801598301190925 rRNA rRNA -TRANSPAC_I-int 1.16122217809542 0.000845313292130344 LTR Gypsy -G4_DM -0.74970144243323 0.000914365923267624 LINE Jockey -SSU-rRNA_Hsa 1.12389968473263 0.0010425909765405 rRNA rRNA -DOC5_DM -0.809872869194368 0.00162410751644423 LINE Jockey -Invader1_I-int 0.749727833008358 0.00198920329215702 LTR Gypsy -TRANSIB4 -1.00230688125284 0.00206051807311839 DNA CMC-Transib -MICROPIA_I-int -0.751193028928835 0.00292932704926266 LTR Gypsy -PLACW_DM 1.16310826488548 0.00305178248567248 DNA P -TABOR_I-int 0.737702190628259 0.00354953953973759 LTR Gypsy -I_DM 1.04141382256571 0.00457151681951996 LINE I -Gypsy3_I-int 0.586594796021762 0.00533147146680179 LTR Gypsy -DOC 0.94015335715084 0.00552118010544697 LINE Jockey -Helitron1_DM -5.10401049101919 0.00636579556275411 RC Helitron -Invader5_I-int -0.973422642391873 0.00666026639838213 LTR Gypsy -ACCORD_I-int 0.593047691019391 0.00701363615971209 LTR Gypsy -LSU-rRNA_Dme 0.902204791675651 0.0102101724391352 rRNA rRNA -DM412 0.775970807845826 0.0108079710929838 LTR Gypsy -NINJA_LTR -0.923408172476265 0.0109563169817133 LTR Pao -BATUMI_I-int -0.562867612987509 0.0148551719821132 LTR Pao -DMRT1C -0.664744166716986 0.0174563775735471 LINE R1 -TAHRE -0.509503033739914 0.0198535740576507 LINE Jockey -Gypsy8_I-int -0.578276897527121 0.0248976847994314 LTR Gypsy -BLASTOPIA_I-int 0.796987753936179 0.0301824235833205 LTR Gypsy -DM176_LTR -0.691384671506076 0.0432538714324547 LTR Gypsy -DMRT1A -0.509608409844153 0.0432538714324547 LINE R1 -Gypsy11_I-int -0.734634622561586 0.0432538714324547 LTR Gypsy -QUASIMODO2-I_DM 0.470057940126177 0.044414105251971 LTR Gypsy -MuDR-1_DEl 1.35524442785064 0.0532319546519159 DNA MULE-NOF -DM1731_LTR 0.752238181600754 0.0540130070646644 LTR Copia -FROGGER_I-int -0.60531971025629 0.0540130070646644 LTR Copia -MAX_I-int -0.516456091983578 0.0643402067819527 LTR Pao -BURDOCK_I-int 0.418223330277469 0.0691214301126813 LTR Gypsy -FROGGER_LTR 0.888326398013863 0.0706362756551064 LTR Copia -DIVER_I-int 0.579052226156673 0.0738156276916979 LTR Pao -Chouto_I-int -0.551029990754245 0.081511593859774 LTR Gypsy -DM176_I-int 0.387008766766431 0.0918637211505497 LTR Gypsy -Invader4_I-int 0.532747054501905 0.0948962153500033 LTR Gypsy -G3_DM -0.607648157164968 0.103160664266056 LINE Jockey -Gypsy4_LTR 0.67676362702008 0.105307005535582 LTR Gypsy -BATUMI_LTR -0.625598883331715 0.112325719453317 LTR Pao -Gypsy2-I_DM 0.418860685191156 0.127538985839499 LTR Gypsy -Invader3_LTR -0.553726127316243 0.130228544874336 LTR Gypsy -MDG3_I-int 0.417195433411295 0.130837858091619 LTR Gypsy -SSU-rRNA_Dme 0.50182621141568 0.130837858091619 rRNA rRNA -G5A_DM -0.468375220785066 0.142388172856184 LINE Jockey -S2_DM -0.576444154651051 0.154380925206633 DNA TcMar-Tc1 -Stalker2_I-int -0.424817076156048 0.157921464286182 LTR Gypsy -BLOOD_LTR 0.494999752604753 0.158635278613665 LTR Gypsy -Invader5_LTR -0.675984091871337 0.158635278613665 LTR Gypsy -R1-2_DM -0.611853226580459 0.158635278613665 LINE R1 -Transib5 -0.51646991193603 0.158635278613665 DNA CMC-Transib -TLD2 -1.24823548505769 0.158665416598185 LTR Gypsy -TC1_DM 0.400572910860442 0.167626897114732 DNA TcMar-Tc1 -BS2 -0.331386491833491 0.185478101135035 LINE Jockey -ROVER-LTR_DM -0.529681787599071 0.188737381603441 LTR Gypsy -ACCORD2_I-int -0.350572607465432 0.191790844708841 LTR Gypsy -Gypsy12A_LTR -0.354465506898828 0.204428444984748 LTR Gypsy -FW3_DM -0.476342557702003 0.216920256528982 LINE Jockey -ROO_LTR 0.400232536676207 0.244465267216066 LTR Pao -STALKER4_LTR 0.383349427659289 0.248258091824749 LTR Gypsy -POGON1 0.482507112501569 0.255779427421414 DNA TcMar-Pogo -HOBO -0.283220815078204 0.273166685685814 DNA hAT-hobo -BS3_DM -0.418041606433149 0.277910060681416 LINE Jockey -Gypsy9_I-int -0.437336296478435 0.280951304168472 LTR Gypsy -P-1_DY 0.969417874734635 0.280951304168472 DNA P -Bica_I-int -0.363151852276854 0.287621291763315 LTR Gypsy -DMCR1A -0.342108879038489 0.320538100201906 LINE CR1 -Mariner2_DM -0.422114252836712 0.320538100201906 DNA TcMar-Tc1 -Gypsy7_LTR -0.484940393339899 0.322658401361327 LTR Gypsy -TRANSIB3 0.344232145502121 0.322658401361327 DNA CMC-Transib -DMRPR 0.474671090698546 0.369600785239272 Unknown Unknown -DIVER2_LTR -0.381362071713278 0.384462351162869 LTR Pao -Gypsy1-LTR_DM 0.341547880045558 0.384860099197221 LTR Gypsy -DOC4_DM 0.362114244909638 0.389414554540185 LINE Jockey -SSU-rRNA_Cel 0.268693361351043 0.389414554540185 rRNA rRNA -ZAM_I-int 0.25296287202699 0.397202788288282 LTR Gypsy -XDMR_DM -0.256211211677393 0.408914532732159 Unknown Unknown -Chimpo_LTR -0.460515218470088 0.409319591327129 LTR Gypsy -5S_DM -0.36064468671157 0.412039231991319 RNA RNA -BLOOD_I-int 0.301193505006723 0.412039231991319 LTR Gypsy -CIRCE -0.21220098912431 0.412039231991319 LTR Gypsy -DOC2_DM -0.219218822289782 0.412039231991319 LINE Jockey -HELENA_RT 0.306716860759321 0.412039231991319 LINE Jockey -HETA -0.298692871636692 0.412039231991319 LINE Jockey -Invader2_LTR -0.349451178427879 0.412039231991319 LTR Gypsy -PROTOP -0.21894181311432 0.412039231991319 DNA P -ACCORD2_LTR -0.373877436518785 0.415323684742582 LTR Gypsy -BARI1 -0.361825471165769 0.439062969216072 DNA TcMar-Tc1 -Copia2_I-int -0.199651272204726 0.454016393978291 LTR Copia -Chouto_LTR -0.42256718750228 0.457631460799645 LTR Gypsy -S_DM 0.193275098711318 0.466588891242574 DNA TcMar-Tc1 -Chimpo_I-int -0.3198026895528 0.469668398060595 LTR Gypsy -Gypsy2_LTR 0.337405927915915 0.469668398060595 LTR Gypsy -Gypsy6_I-int 0.244887845096584 0.469668398060595 LTR Gypsy -NOMAD_LTR -0.310707505731374 0.469668398060595 LTR Gypsy -DIVER2_I-int -0.217400353167491 0.482143273163041 LTR Pao -DOC3_DM -0.226748306440889 0.495640056965812 LINE Jockey -XDMR 0.249633734746355 0.503551868695532 Unknown Unknown -ROO_I-int 0.276608752749181 0.50509162020251 LTR Pao -BURDOCK_LTR 0.32676718204459 0.510777537217992 LTR Gypsy -BEL_I-int 0.237362494177496 0.533794803142695 LTR Pao -Invader6_I-int -0.205266937253198 0.533794803142695 LTR Gypsy -ROOA_I-int -0.194233478923581 0.533794803142695 LTR Pao -DIVER_LTR 0.271030983517942 0.536617484807809 LTR Pao -DOC6_DM 0.222079405295424 0.536617484807809 LINE Jockey -GTWIN_I-int 0.193808394449743 0.536617484807809 LTR Gypsy -MAX_LTR -0.257749452683052 0.540151898310569 LTR Pao -Gypsy10_I-int -0.188834668589015 0.568470618173646 LTR Gypsy -Gypsy11_LTR -0.304519901682671 0.568470618173646 LTR Gypsy -Transib-N1_DM -0.285359544492984 0.568470618173646 DNA CMC-Transib -Gypsy8_LTR -0.22930840819102 0.572155988619062 LTR Gypsy -MDG1_LTR -0.222278232633914 0.598330807400594 LTR Gypsy -ARS406_DM -0.253969785738388 0.616310720408007 Unknown Unknown -TRANSIB2 -0.146222438911029 0.625405183746808 DNA CMC-Transib -Invader3_I-int -0.138005789457227 0.63087021446348 LTR Gypsy -FW2_DM 0.18134923098773 0.631976090641453 LINE Jockey -Gypsy9_LTR -0.341386719736692 0.637388403082853 LTR Gypsy -PROTOP_A 0.129470019526978 0.641582941744779 DNA P -TART-A 0.137000662462686 0.641582941744779 LINE Jockey -Invader2_I-int -0.151224307192946 0.653366733778121 LTR Gypsy -MDG3_LTR -0.188668582948884 0.653366733778121 LTR Gypsy -Jockey2 -0.162959614427421 0.6545684300628 LINE Jockey -POGO -0.150727724968995 0.655487951511946 DNA TcMar-Pogo -Baggins1 -0.134826103211095 0.693165877070164 LINE LOA -Bica_LTR -0.203027970314789 0.707635948527852 LTR Gypsy -HMSBEAGLE_I-int 0.13884460350775 0.707635948527852 LTR Gypsy -Stalker3_LTR -0.174018068430168 0.707635948527852 LTR Gypsy -NTS_DM -0.176552072990723 0.7126900116144 Other Other -TABOR_LTR -0.243243320673685 0.7126900116144 LTR Gypsy -ZAM_LTR 0.185889162361338 0.717882303973929 LTR Gypsy -G5_DM -0.112256553949312 0.728328879400999 LINE Jockey -BEL_LTR 0.152542861711851 0.756425760962704 LTR Pao -FB4_DM -0.114616335459739 0.756425760962704 DNA TcMar-Tc1 -Invader1_LTR 0.141219962488351 0.756425760962704 LTR Gypsy -QUASIMODO_I-int 0.126271255526405 0.756425760962704 LTR Gypsy -DMRT1B -0.111235216287692 0.760051744799183 LINE R1 -NOMAD_I-int -0.137546703453753 0.760051744799183 LTR Gypsy -LmeSINE1c -0.228543531933743 0.760296029745035 SINE tRNA-Deu-L2 -Copia2_LTR_DM 0.147979193864449 0.76240178289376 LTR Copia -Gypsy10_LTR -0.154651074858764 0.76240178289376 LTR Gypsy -QUASIMODO2-LTR_DM -0.155430480903998 0.76240178289376 LTR Gypsy -BS4_DM -0.253251631796478 0.81092436860891 LINE Jockey -G_DM 0.0902785903431559 0.81092436860891 LINE Jockey -IVK_DM -0.0807211765160779 0.818709085450591 LINE I -Gypsy12_LTR -0.0832045482918072 0.835273508731359 LTR Gypsy -Gypsy5_I-int -0.0774807293903186 0.835273508731359 LTR Gypsy -Gypsy6A_LTR -0.116239966704279 0.835273508731359 LTR Gypsy -IDEFIX_I-int 0.0781972363147815 0.835273508731359 LTR Gypsy -DMRP1 0.100504519100353 0.846311908195535 Unknown Unknown -PROTOP_B -0.0745501769371703 0.846311908195535 DNA P -Copia1-LTR_DM -0.0961752276665428 0.850550157756311 LTR Copia -TC1-2_DM 0.0595720035046981 0.853067020850826 DNA TcMar-Tc1 -Gypsy7_I-int 0.0826410967604942 0.861339242519926 LTR Gypsy -LSU-rRNA_Cel -0.0920825033469626 0.861339242519926 rRNA rRNA -DMLTR5 0.0726894766496021 0.905487490633946 LTR Gypsy -Gypsy2-LTR_DM 0.0652192786223383 0.905487490633946 LTR Gypsy -Gypsy4_I-int -0.0516274039610208 0.905487490633946 LTR Gypsy -Gypsy5_LTR -0.0710979993807782 0.905487490633946 LTR Gypsy -QUASIMODO_LTR -0.0643467685962964 0.905487490633946 LTR Gypsy -Stalker2_LTR -0.0523210063310555 0.917308330496379 LTR Gypsy -ROVER-I_DM -0.0408110836395496 0.922716163337686 LTR Gypsy -MDG1_I-int -0.0411424164719924 0.937452811422426 LTR Gypsy -ALA_DM -0.11425480149938 0.942917068804402 Unknown Unknown -DNAREP1_DM 0.039354033592028 0.942917068804402 RC Helitron -BARI_DM 0.0372716083617889 0.949850971355763 DNA TcMar-Tc1 -Gypsy2_I-int -0.0261599267227275 0.951965771983562 LTR Gypsy -DMTOM1_LTR 0.0349640382618226 0.953829042793374 LTR Gypsy -Gypsy3_LTR -0.0298883238815861 0.957715681080923 LTR Gypsy -IDEFIX_LTR 0.0219961145617681 0.957715681080923 LTR Gypsy -MINOS 0.0330479824589295 0.957715681080923 DNA TcMar-Tc1 -STALKER4_I-int 0.0241275307638275 0.957715681080923 LTR Gypsy -G2_DM 0.0226097987515835 0.962242582647045 LINE Jockey -Copia1-I_DM 0.0124236833262227 0.963045943681341 LTR Copia -Invader4_LTR 0.016495431966038 0.963045943681341 LTR Gypsy -M4DM -0.0173659751457427 0.963045943681341 DNA CMC-Transib -BS 0.00565217021634194 0.997858051773989 LINE Jockey -FTZ_DM 0 1 Unknown Unknown -FUSHI_DM 0 1 Unknown Unknown -ROOA_LTR -0.0005425128837839 1 LTR Pao +TE_item log2FC FDR Class Type +DM297_I-int 2.69047105 4.4945e-21 LTR Gypsy +DM297_LTR 1.74961921 1.3397e-18 LTR Gypsy +Gypsy1-I_DM 2.37388633 4.4803e-16 LTR Gypsy +NOF_FB -2.79644759 4.4803e-16 DNA MULE-NOF +G7_DM 3.25987375 1.5530e-15 LINE Jockey +Gypsy_I-int 1.74702180 4.3525e-12 LTR Gypsy +LINEJ1_DM 1.94429218 5.1807e-12 LINE Jockey +TOM_I-int 1.33935222 6.6923e-12 LTR Gypsy +GTWIN_LTR 1.89490932 8.8059e-12 LTR Gypsy +Gypsy_LTR 1.56024436 2.9985e-11 LTR Gypsy +DM1731_I-int 1.53134430 6.4921e-10 LTR Copia +Gypsy6_LTR 1.53023046 1.0751e-06 LTR Gypsy +LOOPER1_DM -2.46983670 1.6192e-06 DNA PiggyBac +TIRANT_LTR 1.12203469 1.7801e-06 LTR Gypsy +Gypsy12_I-int -1.12204057 2.1949e-06 LTR Gypsy +R2_DM 1.67889583 2.7304e-06 LINE R2 +TRANSPAC_LTR 1.49364968 2.9021e-06 LTR Gypsy +Copia_LTR 1.66649088 1.1860e-05 LTR Copia +ACCORD_LTR 1.37240595 1.7595e-05 LTR Gypsy +TIRANT_I-int 1.17728139 2.0469e-05 LTR Gypsy +TART_B1 -1.14695346 3.0966e-05 LINE Jockey +TRANSIB1 -1.39021194 6.1650e-05 DNA CMC-Transib +DM412B_LTR 0.80309005 1.2443e-04 LTR Gypsy +MICROPIA_LTR -1.29556276 1.2985e-04 LTR Gypsy +G6_DM -1.05894869 1.3831e-04 LINE Jockey +NINJA_I-int -0.87426452 1.5554e-04 LTR Pao +R1_DM 0.95590515 1.8985e-04 LINE R1 +Invader6_LTR -1.18865109 2.1299e-04 LTR Gypsy +Copia_I-int 1.93316905 2.2313e-04 LTR Copia +BLASTOPIA_LTR 1.34881959 3.6488e-04 LTR Gypsy +LSU-rRNA_Hsa 2.61189118 8.0160e-04 rRNA rRNA +TRANSPAC_I-int 1.16122218 8.4531e-04 LTR Gypsy +G4_DM -0.74970144 9.1437e-04 LINE Jockey +SSU-rRNA_Hsa 1.12389968 1.0426e-03 rRNA rRNA +DOC5_DM -0.80987287 1.6241e-03 LINE Jockey +Invader1_I-int 0.74972783 1.9892e-03 LTR Gypsy +TRANSIB4 -1.00230688 2.0605e-03 DNA CMC-Transib +MICROPIA_I-int -0.75119303 2.9293e-03 LTR Gypsy +PLACW_DM 1.16310826 3.0518e-03 DNA P +TABOR_I-int 0.73770219 3.5495e-03 LTR Gypsy +I_DM 1.04141382 4.5715e-03 LINE I +Gypsy3_I-int 0.58659480 5.3315e-03 LTR Gypsy +DOC 0.94015336 5.5212e-03 LINE Jockey +Helitron1_DM -5.10401049 6.3658e-03 RC Helitron +Invader5_I-int -0.97342264 6.6603e-03 LTR Gypsy +ACCORD_I-int 0.59304769 7.0136e-03 LTR Gypsy +LSU-rRNA_Dme 0.90220479 1.0210e-02 rRNA rRNA +DM412 0.77597081 1.0808e-02 LTR Gypsy +NINJA_LTR -0.92340817 1.0956e-02 LTR Pao +BATUMI_I-int -0.56286761 1.4855e-02 LTR Pao +DMRT1C -0.66474417 1.7456e-02 LINE R1 +TAHRE -0.50950303 1.9854e-02 LINE Jockey +Gypsy8_I-int -0.57827690 2.4898e-02 LTR Gypsy +BLASTOPIA_I-int 0.79698775 3.0182e-02 LTR Gypsy +DM176_LTR -0.69138467 4.3254e-02 LTR Gypsy +DMRT1A -0.50960841 4.3254e-02 LINE R1 +Gypsy11_I-int -0.73463462 4.3254e-02 LTR Gypsy +QUASIMODO2-I_DM 0.47005794 4.4414e-02 LTR Gypsy +MuDR-1_DEl 1.35524443 5.3232e-02 DNA MULE-NOF +DM1731_LTR 0.75223818 5.4013e-02 LTR Copia +FROGGER_I-int -0.60531971 5.4013e-02 LTR Copia +MAX_I-int -0.51645609 6.4340e-02 LTR Pao +BURDOCK_I-int 0.41822333 6.9121e-02 LTR Gypsy +FROGGER_LTR 0.88832640 7.0636e-02 LTR Copia +DIVER_I-int 0.57905223 7.3816e-02 LTR Pao +Chouto_I-int -0.55102999 8.1512e-02 LTR Gypsy +DM176_I-int 0.38700877 9.1864e-02 LTR Gypsy +Invader4_I-int 0.53274705 9.4896e-02 LTR Gypsy +G3_DM -0.60764816 1.0316e-01 LINE Jockey +Gypsy4_LTR 0.67676363 1.0531e-01 LTR Gypsy +BATUMI_LTR -0.62559888 1.1233e-01 LTR Pao +Gypsy2-I_DM 0.41886069 1.2754e-01 LTR Gypsy +Invader3_LTR -0.55372613 1.3023e-01 LTR Gypsy +MDG3_I-int 0.41719543 1.3084e-01 LTR Gypsy +SSU-rRNA_Dme 0.50182621 1.3084e-01 rRNA rRNA +G5A_DM -0.46837522 1.4239e-01 LINE Jockey +S2_DM -0.57644415 1.5438e-01 DNA TcMar-Tc1 +Stalker2_I-int -0.42481708 1.5792e-01 LTR Gypsy +BLOOD_LTR 0.49499975 1.5864e-01 LTR Gypsy +Invader5_LTR -0.67598409 1.5864e-01 LTR Gypsy +R1-2_DM -0.61185323 1.5864e-01 LINE R1 +Transib5 -0.51646991 1.5864e-01 DNA CMC-Transib +TLD2 -1.24823549 1.5867e-01 LTR Gypsy +TC1_DM 0.40057291 1.6763e-01 DNA TcMar-Tc1 +BS2 -0.33138649 1.8548e-01 LINE Jockey +ROVER-LTR_DM -0.52968179 1.8874e-01 LTR Gypsy +ACCORD2_I-int -0.35057261 1.9179e-01 LTR Gypsy +Gypsy12A_LTR -0.35446551 2.0443e-01 LTR Gypsy +FW3_DM -0.47634256 2.1692e-01 LINE Jockey +ROO_LTR 0.40023254 2.4447e-01 LTR Pao +STALKER4_LTR 0.38334943 2.4826e-01 LTR Gypsy +POGON1 0.48250711 2.5578e-01 DNA TcMar-Pogo +HOBO -0.28322082 2.7317e-01 DNA hAT-hobo +BS3_DM -0.41804161 2.7791e-01 LINE Jockey +Gypsy9_I-int -0.43733630 2.8095e-01 LTR Gypsy +P-1_DY 0.96941787 2.8095e-01 DNA P +Bica_I-int -0.36315185 2.8762e-01 LTR Gypsy +DMCR1A -0.34210888 3.2054e-01 LINE CR1 +Mariner2_DM -0.42211425 3.2054e-01 DNA TcMar-Tc1 +Gypsy7_LTR -0.48494039 3.2266e-01 LTR Gypsy +TRANSIB3 0.34423215 3.2266e-01 DNA CMC-Transib +DMRPR 0.47467109 3.6960e-01 Unknown Unknown +DIVER2_LTR -0.38136207 3.8446e-01 LTR Pao +Gypsy1-LTR_DM 0.34154788 3.8486e-01 LTR Gypsy +DOC4_DM 0.36211424 3.8941e-01 LINE Jockey +SSU-rRNA_Cel 0.26869336 3.8941e-01 rRNA rRNA +ZAM_I-int 0.25296287 3.9720e-01 LTR Gypsy +XDMR_DM -0.25621121 4.0891e-01 Unknown Unknown +Chimpo_LTR -0.46051522 4.0932e-01 LTR Gypsy +5S_DM -0.36064469 4.1204e-01 RNA RNA +BLOOD_I-int 0.30119351 4.1204e-01 LTR Gypsy +CIRCE -0.21220099 4.1204e-01 LTR Gypsy +DOC2_DM -0.21921882 4.1204e-01 LINE Jockey +HELENA_RT 0.30671686 4.1204e-01 LINE Jockey +HETA -0.29869287 4.1204e-01 LINE Jockey +Invader2_LTR -0.34945118 4.1204e-01 LTR Gypsy +PROTOP -0.21894181 4.1204e-01 DNA P +ACCORD2_LTR -0.37387744 4.1532e-01 LTR Gypsy +BARI1 -0.36182547 4.3906e-01 DNA TcMar-Tc1 +Copia2_I-int -0.19965127 4.5402e-01 LTR Copia +Chouto_LTR -0.42256719 4.5763e-01 LTR Gypsy +S_DM 0.19327510 4.6659e-01 DNA TcMar-Tc1 +Chimpo_I-int -0.31980269 4.6967e-01 LTR Gypsy +Gypsy2_LTR 0.33740593 4.6967e-01 LTR Gypsy +Gypsy6_I-int 0.24488785 4.6967e-01 LTR Gypsy +NOMAD_LTR -0.31070751 4.6967e-01 LTR Gypsy +DIVER2_I-int -0.21740035 4.8214e-01 LTR Pao +DOC3_DM -0.22674831 4.9564e-01 LINE Jockey +XDMR 0.24963373 5.0355e-01 Unknown Unknown +ROO_I-int 0.27660875 5.0509e-01 LTR Pao +BURDOCK_LTR 0.32676718 5.1078e-01 LTR Gypsy +BEL_I-int 0.23736249 5.3379e-01 LTR Pao +Invader6_I-int -0.20526694 5.3379e-01 LTR Gypsy +ROOA_I-int -0.19423348 5.3379e-01 LTR Pao +DIVER_LTR 0.27103098 5.3662e-01 LTR Pao +DOC6_DM 0.22207941 5.3662e-01 LINE Jockey +GTWIN_I-int 0.19380839 5.3662e-01 LTR Gypsy +MAX_LTR -0.25774945 5.4015e-01 LTR Pao +Gypsy10_I-int -0.18883467 5.6847e-01 LTR Gypsy +Gypsy11_LTR -0.30451990 5.6847e-01 LTR Gypsy +Transib-N1_DM -0.28535954 5.6847e-01 DNA CMC-Transib +Gypsy8_LTR -0.22930841 5.7216e-01 LTR Gypsy +MDG1_LTR -0.22227823 5.9833e-01 LTR Gypsy +ARS406_DM -0.25396979 6.1631e-01 Unknown Unknown +TRANSIB2 -0.14622244 6.2541e-01 DNA CMC-Transib +Invader3_I-int -0.13800579 6.3087e-01 LTR Gypsy +FW2_DM 0.18134923 6.3198e-01 LINE Jockey +Gypsy9_LTR -0.34138672 6.3739e-01 LTR Gypsy +PROTOP_A 0.12947002 6.4158e-01 DNA P +TART-A 0.13700066 6.4158e-01 LINE Jockey +Invader2_I-int -0.15122431 6.5337e-01 LTR Gypsy +MDG3_LTR -0.18866858 6.5337e-01 LTR Gypsy +Jockey2 -0.16295961 6.5457e-01 LINE Jockey +POGO -0.15072772 6.5549e-01 DNA TcMar-Pogo +Baggins1 -0.13482610 6.9317e-01 LINE LOA +Bica_LTR -0.20302797 7.0764e-01 LTR Gypsy +HMSBEAGLE_I-int 0.13884460 7.0764e-01 LTR Gypsy +Stalker3_LTR -0.17401807 7.0764e-01 LTR Gypsy +NTS_DM -0.17655207 7.1269e-01 Other Other +TABOR_LTR -0.24324332 7.1269e-01 LTR Gypsy +ZAM_LTR 0.18588916 7.1788e-01 LTR Gypsy +G5_DM -0.11225655 7.2833e-01 LINE Jockey +BEL_LTR 0.15254286 7.5643e-01 LTR Pao +FB4_DM -0.11461634 7.5643e-01 DNA TcMar-Tc1 +Invader1_LTR 0.14121996 7.5643e-01 LTR Gypsy +QUASIMODO_I-int 0.12627126 7.5643e-01 LTR Gypsy +DMRT1B -0.11123522 7.6005e-01 LINE R1 +NOMAD_I-int -0.13754670 7.6005e-01 LTR Gypsy +LmeSINE1c -0.22854353 7.6030e-01 SINE tRNA-Deu-L2 +Copia2_LTR_DM 0.14797919 7.6240e-01 LTR Copia +Gypsy10_LTR -0.15465107 7.6240e-01 LTR Gypsy +QUASIMODO2-LTR_DM -0.15543048 7.6240e-01 LTR Gypsy +BS4_DM -0.25325163 8.1092e-01 LINE Jockey +G_DM 0.09027859 8.1092e-01 LINE Jockey +IVK_DM -0.08072118 8.1871e-01 LINE I +Gypsy12_LTR -0.08320455 8.3527e-01 LTR Gypsy +Gypsy5_I-int -0.07748073 8.3527e-01 LTR Gypsy +Gypsy6A_LTR -0.11623997 8.3527e-01 LTR Gypsy +IDEFIX_I-int 0.07819724 8.3527e-01 LTR Gypsy +DMRP1 0.10050452 8.4631e-01 Unknown Unknown +PROTOP_B -0.07455018 8.4631e-01 DNA P +Copia1-LTR_DM -0.09617523 8.5055e-01 LTR Copia +TC1-2_DM 0.05957200 8.5307e-01 DNA TcMar-Tc1 +Gypsy7_I-int 0.08264110 8.6134e-01 LTR Gypsy +LSU-rRNA_Cel -0.09208250 8.6134e-01 rRNA rRNA +DMLTR5 0.07268948 9.0549e-01 LTR Gypsy +Gypsy2-LTR_DM 0.06521928 9.0549e-01 LTR Gypsy +Gypsy4_I-int -0.05162740 9.0549e-01 LTR Gypsy +Gypsy5_LTR -0.07109800 9.0549e-01 LTR Gypsy +QUASIMODO_LTR -0.06434677 9.0549e-01 LTR Gypsy +Stalker2_LTR -0.05232101 9.1731e-01 LTR Gypsy +ROVER-I_DM -0.04081108 9.2272e-01 LTR Gypsy +MDG1_I-int -0.04114242 9.3745e-01 LTR Gypsy +ALA_DM -0.11425480 9.4292e-01 Unknown Unknown +DNAREP1_DM 0.03935403 9.4292e-01 RC Helitron +BARI_DM 0.03727161 9.4985e-01 DNA TcMar-Tc1 +Gypsy2_I-int -0.02615993 9.5197e-01 LTR Gypsy +DMTOM1_LTR 0.03496404 9.5383e-01 LTR Gypsy +Gypsy3_LTR -0.02988832 9.5772e-01 LTR Gypsy +IDEFIX_LTR 0.02199611 9.5772e-01 LTR Gypsy +MINOS 0.03304798 9.5772e-01 DNA TcMar-Tc1 +STALKER4_I-int 0.02412753 9.5772e-01 LTR Gypsy +G2_DM 0.02260980 9.6224e-01 LINE Jockey +Copia1-I_DM 0.01242368 9.6305e-01 LTR Copia +Invader4_LTR 0.01649543 9.6305e-01 LTR Gypsy +M4DM -0.01736598 9.6305e-01 DNA CMC-Transib +BS 0.00565217 9.9786e-01 LINE Jockey +FTZ_DM 0.00000000 1.0000e+00 Unknown Unknown +FUSHI_DM 0.00000000 1.0000e+00 Unknown Unknown +ROOA_LTR -0.00054251 1.0000e+00 LTR Pao