Package evenn. March 10, 2015

Transcription

1 Type Package Package evenn March 10, 2015 Title A Powerful Tool to Quickly Compare Huge Lists and Draw Venn Diagrams Version 2.2 Imports tcltk Date Author Nicolas Cagnard Maintainer Nicolas Cagnard <nicolas.cagnard@gmail.com> Compute a matrix comparison of lists (from 2 to infinite) and plot the results in a Venn diagram if (N<=4) with regulation details. It allows to produce a complete annotated file, merging the annotations of the compared lists. It is also possible to compute an overlaps table to show the overlaps proportions of all the couples of lists and draw proportional Venn diagrams. License GPL LazyLoad yes Depends R (>= 2.10) NeedsCompilation no Repository CRAN Date/Publication :21:47 R topics documented: evenn-package autoevenn Data_Binary_Matrix Data_Lists Data_Matrix_Of_Folds Data_Matrix_Of_Ratios evenn man.evenn Index 10 1

2 2 evenn-package evenn-package A Powerful Tool to Quickly Compare Huge Lists and Draw Venn Diagrams Details Compute a matrix comparison of lists (from 2 to infinite) and plot the results in a Venn diagram if (N<=4) or a bar chart. It is can to produce a complete annotated file, merging the annotations of the compared lists. It is can also to compute an overlaps table to compute the overlaps proportions of all the couples of lists. Package: evenn Type: Package Version: 2.2 Date: License: GPL LazyLoad: yes Author(s) Author & Maintainer: Nicolas Cagnard <nicolas.cagnard@gmail.com> library(evenn) library(evenn) YNdisplay = TRUE # Allows commentaries and display of the main steps of the process # Matrix of binary data data(data_binary_matrix) evenn(matlists=data_binary_matrix, display=yndisplay, CompName="Binary_Matrix") # Matrix of folds # data(data_matrix_of_folds) # evenn(matlists=data_matrix_of_folds, display=yndisplay, CompName="Matrix_Of_Folds") # Matrix of ratios # data(data_matrix_of_ratios) # evenn(matlists=data_matrix_of_ratios, display=yndisplay, CompName="Matrix_Of_Ratios")

3 autoevenn 3 # List of 2, 3 or 4 matrix w/wo modulations and w/wo profils data data(data_lists) # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4")], annot=true, # display=yndisplay, CompName="Lists_4") # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4")], ud=true, # annot=true, display=yndisplay, CompName="Lists_4_UD") # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4", "DataMoy")], # ud=true, annot=true, Profils=TRUE, display=yndisplay, CompName="Lists_4_UD_Profils") autoevenn Automates the process of several evenn This function creates a list of folders where are placed sources files for venn diagrams and call the evenn function for each one. autoevenn(folderpath = "", annot = TRUE, ud = TRUE, VennBar = FALSE, Solid = TRUE, Profils = TRUE, prop = FALSE, display = FALSE) Arguments FolderPath annot ud Path where are placed the source data folders. If the compared files got more than one column (not only IDs). If the source files comport a ratio or fold column the details of up and down regulated genes will be shown. VennBar Represent the zones of a venn diagram with a bars chart even for more than 4 lists. Solid Profils prop display Author(s) No transparancy, disks are filled with solid colours. This option is valid only if the modulations (UD) are available (ie ratio column or each list) and a DataMoy.txt file containing the means of each group for all the items. The items will be separated by modulations profiles. If the surfaces of the disks should be proportional to the size of the lists. Print commentaries during the process. Author & Maintainer: Nicolas Cagnard <nicolas.cagnard@gmail.com>

4 4 Data_Lists Data_Binary_Matrix Dataset of a binary matrix for a usage example of the package evenn A matrix of 4 columns * lines filled with 0 and 1. 0 means that the item (line) does not belong to the list (column), 1 if it belongs. data("data_binary_matrix") Format The format is: int [1:10493, 1:4] attr(*, "dimnames")=list of 2..$ : chr [1:10493] " " " " " " " ".....$ : chr [1:4] "List_1" "List_2" "List_3" "List_4" # library(evenn) # YNdisplay = TRUE # Allows commentaries and display of the main steps of the process # data(data_binary_matrix) # evenn(matlists=data_binary_matrix, display=yndisplay, CompName="Binary_Matrix") Data_Lists Dataset of a list of 4 matrix of expression data with ratio columns and a matrix of means for a usage example of the package evenn List of 4 matrix (List_1, List_2, List_3, List_4) with IDs, annotations and a column of ratios and a matrix of means (DataMoy). data("data_lists")

5 Data_Matrix_Of_Folds 5 Format The format is: List of 5 $ DataMoy: num [1:33793, 1:6] attr(*, "dimnames")=list of 2....$ : chr [1:33793] " " " " " " " " $ : chr [1:6] "Group_1" "Group_2" "Group_3" "Group_4"... $ List_1 : chr [1:3845, 1:15] "Pcmtd1 " " " "Cspp1 " "Tmem14a " attr(*, "dimnames")=list of 2....$ : chr [1:3845] " " " " " " " " $ : chr [1:15] "Gene" "Name" "pval" "Group_5_sample_1"... $ List_2 : chr [1:2445, 1:15] "Rb1cc1 " "Pcmtd1 " "Cspp1 " " L15 // L15 " attr(*, "dimnames")=list of 2....$ : chr [1:2445] " " " " " " " " $ : chr [1:15] "Gene" "Name" "pval" "Group_6_sample_1"... $ List_3 : chr [1:2525, 1:15] "Terf1 " "Tfap2d " "Efhc1 " "Cfc1 " attr(*, "dimnames")=list of 2....$ : chr [1:2525] " " " " " " " " $ : chr [1:15] "Gene" "Name" "pval" "Group_2_sample_1"... $ List_4 : chr [1:1558, 1:15] "Terf1 " "Khdc1c // Khdc1c " "Khdrbs2 " "Cfc1 " attr(*, "dimnames")=list of 2....$ : chr [1:1558] " " " " " " " " $ : chr [1:15] "Gene" "Name" "pval" "Group_3_sample_1"... library(evenn) # List of 2, 3 or 4 matrix w/wo modulations and w/wo profils data # data(data_lists) # YNdisplay = TRUE # Allows commentaries and display of the main steps of the process # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4")], annot=true, # display=yndisplay, CompName="Lists_4") # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4")], ud=true, # annot=true, display=yndisplay, CompName="Lists_4_UD") # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4", "DataMoy")], # ud=true, annot=true, Profils=TRUE, display=yndisplay, CompName="Lists_4_UD_Profils") Data_Matrix_Of_Folds Dataset of a matrix of folds for a usage example of the package evenn A matrix of 4 columns * lines filled with folds or NA. NA means that the item (line) does not belong to the list (column), there is a fold if it belongs. data("data_matrix_of_folds")

6 6 Data_Matrix_Of_Ratios Format The format is: num [1:10493, 1:4] NA 1.94 NA NA NA... - attr(*, "dimnames")=list of 2..$ : chr [1:10493] " " " " " " " ".....$ : chr [1:4] "List_1" "List_2" "List_3" "List_4" # library(evenn) # YNdisplay = TRUE # Allows commentaries and display of the main steps of the process # data(data_matrix_of_folds) # evenn(matlists=data_matrix_of_folds, display=yndisplay, CompName="Matrix_Of_Folds") Data_Matrix_Of_Ratios Dataset of a matrix of ratios for a usage example of the package evenn A matrix of 4 columns * lines filled with ratios or NA. NA means that the item (line) does not belong to the list (column), there is a ratio if it belongs. data("data_matrix_of_ratios") Format The format is: num [1:10493, 1:4] NA 1.94 NA NA NA... - attr(*, "dimnames")=list of 2..$ : chr [1:10493] " " " " " " " ".....$ : chr [1:4] "List_1" "List_2" "List_3" "List_4" # library(evenn) # YNdisplay = TRUE # Allows commentaries and display of the main steps of the process # data(data_matrix_of_ratios) # evenn(matlists=data_matrix_of_ratios, display=yndisplay, CompName="Matrix_Of_Ratios")

7 evenn 7 evenn A Powerful Tool to Quickly Compare Huge Lists and Draw Venn Diagrams Compute a matrix comparison of lists (from 2 to infinite) and plot the results in a Venn diagram if (N<=4) or a bar chart. It is can to produce a complete annotated file, merging the annotations of the compared lists. It is can also to compute an overlaps table to compute the overlaps proportions of all the couples of lists. evenn(annot=false, matlists="", pathres="", pathlists="", ud=false, prop=false, noms="", overlaps=false, f=0, display=false, couleurs="", VennBar=FALSE, CompName="", transp=0.5, Solid=TRUE, Profils=FALSE, OnlyVariable=FALSE, colblack=false) Arguments annot matlists pathres pathlists ud prop noms If the compared files got more than one column (not only IDs). Matrix, list of matrix or list of lists to be compared. Path used to save the results. The working directory is used by default. Path of the data folder where are placed the files to be compared. The files must be text tabulated or csv format. If the source files comport a ratio or fold column the details of up and down regulated genes will be shown. If the surfaces of the disks should be proportional to the size of the lists. Custom short names for each list. overlaps Compute the proportions of the overlaps for each couple of lists in two ways (A in B and B in A). A heatmap is created if at least three lists are processed. f display couleurs Set a minimum overlap to produce a filtered overlaps matrix. Default f=0 is set to no filter. Print commentaries during the process. Vector of custom colours to be used in the graphics. Default colours: c("blue", "red", "green", "orange") VennBar Represent the zones of a venn diagram with a bars chart even for more than 4 lists. CompName transp Solid Profils Custom name for the main folder. Percentage of transparency of the disks. No transparancy, disks are filled with solid colours. This option is valid only if the modulations (UD) are available (ie ratio column or each list) and a DataMoy.txt file containing the means of each group for all the items. The items will be separated by modulations profiles.

8 8 evenn OnlyVariable colblack evenn expect a variable in (matlist) and produce a binary matrix. (=> Binary- MatrixOut = evenn(matlist=datain)) No color, only Black on a white background. Value All the results are saved in a folder names with date and hour. The comparison binary matrix is saved as a csv file "venn_matrix.csv". If annot is True, the resulting file (same as venn matrix with annotation given by the source lists) is saved as a text file "venn_annot.txt". The venn diagram is saved in a png file "venn_diagram.png". Author(s) Author & Maintainer: Nicolas Cagnard <nicolas.cagnard@gmail.com> library(evenn) YNdisplay = TRUE # Allows commentaries and display of the main steps of the process # Matrix of binary data # data(data_binary_matrix) # evenn(matlists=data_binary_matrix, display=yndisplay, CompName="Binary_Matrix") # Matrix of folds # data(data_matrix_of_folds) # evenn(matlists=data_matrix_of_folds[,c(1,2)], display=yndisplay, CompName="Matrix_Of_Folds") # Matrix of ratios # data(data_matrix_of_ratios) # evenn(matlists=data_matrix_of_ratios, display=yndisplay, CompName="Matrix_Of_Ratios") # List of 2, 3 or 4 matrix w/wo modulations and w/wo profils data # data(data_lists) # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4")], annot=true, # display=yndisplay, CompName="Lists_4") # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4")], ud=true, # annot=true, display=yndisplay, CompName="Lists_4_UD") # evenn(matlists=data_lists[c("list_1", "List_2", "List_3", "List_4", "DataMoy")], # ud=true, annot=true, Profils=TRUE, display=yndisplay, CompName="Lists_4_UD_Profils")

9 man.evenn 9 man.evenn Quick manual for evenn Help for quick start informations. man.evenn() Author(s) Author & Maintainer: Nicolas Cagnard <nicolas.cagnard@gmail.com>

10 Index Topic datasets Data_Binary_Matrix, 4 Data_Lists, 4 Data_Matrix_Of_Folds, 5 Data_Matrix_Of_Ratios, 6 Topic package evenn-package, 2 autoevenn, 3 Data_Binary_Matrix, 4 Data_Lists, 4 Data_Matrix_Of_Folds, 5 Data_Matrix_Of_Ratios, 6 evenn (evenn-package), 2 evenn, 7 evenn-package, 2 man.evenn, 9 10