Summary

SeqPlots is a user-friendly exploratory data analysis (EDA) and visualization software for genomics. After choosing groups of signal and feature files and defining plotting parameters, users can generate profile plots of average signal or heat maps clustered using different algorithms in a matter of seconds through the graphical user interface (GUI) controls. SeqPlots accepts all major genomic file formats as input and can also generate and plot user defined motif densities. Profile plots and heatmaps are highly configurable and batch operations can be used to generate a large number of plots at once. SeqPlots is available as a GUI application for Mac or Windows and Linux, or as an R/Bioconductor package. It can also be deployed on a server for remote and collaborative usage. The analysis features and ease of use of SeqPlots encourages wide data exploration, which should aid the discovery of novel genomic associations.

Availability

SeqPlots is distributed as user-friendly stand-alone applications for Mac and Windows or Linux. SeqPlots is also available as an R/Bioconductor package or can be deployed as a server application, which is useful for data sharing within laboratories, collaborative usage and remote work. The source code and open development tools, including wiki, bug tracker, and pull requests, are available via GitHub at https://github.com/Przemol/seqplots.

Key features

• Easy to use web interface (R or shell expertise not required)
• Web server or desktop versions
• Generates publication quality plots out of the box
• Plots average signals or heatmaps
• Accepts Wiggle, BedGraph, BigWiggle, BAM and GFF, BED GTF formats
• Calculates motif density from reference genomes
• Tracks and features are searchable and previous calculations can be saved
• Converts tracks to binary BigWiggle format for rapid data extraction and efficient storage
• Implemented using Shiny R framework providing internet browser reactive GUI and session based connectivity (websocets)

Video presentation

Issues and bugs

Please visit issue tracker to view currently know issues. To report a new issue/bug/feature request please click here. If the issue is connected to file upload please attach the file in the form.

Installation

Downbaload and installer from: https://github.com/Przemol/seqplots_electron/releases

Follow the installation instructions.

How to start on macOS (bypass Gatekeeper warning)

Start SeqPlots from Applications. If run for the first time the operating system security notice might be shown.

To run the application right-click on SeqPlots icon and choose “Open”, followed by clicking “Open” button in popup window. This need to be done only once, later SeqPlots can be started as usual Mac OS X application.

Package content

• The Electron framework (https://github.com/electron/electron)
• Platypus (http://www.sveinbjorn.org/platypus) wrapper
• R (http://www.r-project.org/)
• SeqPlots dependency packages (including Shiny, rtracklayer and BSgenome)
• Full genome sequences
• SeqPlots package

How to install

To install SeqPlots package, start R and enter:

source("http://bioconductor.org/biocLite.R")
          biocLite("seqplots")

How to start

To start SeqPlots web interface, start R and enter:

library(seqplots)
          run()

After a successful initiation the user interface will be opened in your default web browser. For further usage please refer to Quick start guide or specific chapters.

The run function accepts “root” argument, which allows to change the data location folder (by default your home directory will be used), e.g.:

run(root='/path/to/data/location')

source("http://bioconductor.org/biocLite.R")
          biocLite("BSgenome.Hsapiens.UCSC.hg19")

Installation

1. Install and configure the Shiny Server by following the instructions on https://github.com/rstudio/shiny-server

2. Install SeqPlots R package and dependences by following the instruction here

3. Copy SeqPlots files to Shiny Server application folder:

cp -r $(Rscript -e "cat(system.file('seqplots', package='seqplots'))") /srv/shiny-server/

4. Set up SeqPlots data location by running from R:

seqplots(root='/path/to/data/location')

5. Edit first line of /srv/shiny-server/shiny/server_config.R, so the environment variable root matches the data location; for example:

Sys.setenv('root'='/var/shiny-server/DATA')

Usage

After successful installation the SeqPlost web GUI will be available at your_server_name:3838/seqplots/.

For further usage please refer to quick start guide or specific chapters of documentation.

source("http://bioconductor.org/biocLite.R")
          biocLite("BSgenome.Hsapiens.UCSC.hg19")

Alternative installation

SeqPlots can be directly cloned into Shiny Server application folder from git repository by using git clone https://github.com/Przemol/seqplots.git. The data location can be set up with following R code:

root <- "/data/location"
          dir.create(root)
          setwd(root)
          require(RSQLite)
          sqlite <- dbDriver("SQLite")
          con <- dbConnect(sqlite, dbname = "files.sqlite")
          dbGetQuery(con, "CREATE TABLE files (id INTEGER PRIMARY KEY ASC, name TEXT UNIQUE, 
            ctime TEXT, type TEXT, format TEXT, genome TEXT, user TEXT, comment TEXT)")
          if (!dbListTables(con) == "files") 
              warning("Database not created!")
          dbDisconnect(con)
          if (!all(sapply(c("removedFiles", "files", "publicFiles", "tmp"), dir.create))) 
              warning("Folders not created!")
          message("\nData loaction: ", root)

The following dependencies must be installed in R:

              package  version
          1              shiny   0.10.0
          2             fields      7.1
          3           parallel    3.1.0
          4          multicore      0.2
          5           BSgenome   1.32.0
          6      GenomicRanges   1.16.3
          7            plotrix    3.5-7
          8        rtracklayer   1.24.2
          9            RJSONIO  1.2-0.2
          10           RSQLite   0.11.4
          11           kohonen   2.0.14
          12             Cairo    1.5-5
          13            digest    0.6.4
          14           methods    3.1.0
          15             tools    3.1.0
          16             utils    3.1.0
          17            httpuv    1.3.0
          18           caTools     1.17
          19            xtable    1.7-3
          20         htmltools    0.2.4
          21            bitops    1.0-6
          22              Rcpp   0.11.2
          23              spam   0.41-0
          24              maps    2.3-7
          25              grid    3.1.0
          26         grDevices    3.1.0
          27      BiocGenerics   0.10.0
          28           IRanges   1.22.9
          29        Biostrings   2.32.0
          30           XVector    0.4.0
          31         Rsamtools   1.16.1
          32          graphics    3.1.0
          33             stats    3.1.0
          34          zlibbioc   1.10.0
          35      GenomeInfoDb    1.0.2
          36            stats4    3.1.0
          37               XML 3.98-1.1
          38             RCurl 1.95-4.1
          39 GenomicAlignments    1.0.1
          40      BiocParallel    0.6.1
          41           foreach    1.4.2
          42         BatchJobs      1.2
          43            BBmisc      1.7
          44               DBI    0.2-7
          45         sendmailR    1.1-2
          46              brew    1.0-6
          47              plyr    1.8.1
          48           stringr    0.6.2
          49              fail      1.2
          50         checkmate      1.0
          51         codetools    0.2-8
          52         iterators    1.0.7
          53         base64enc    0.1-1
          54             class   7.3-10
          55              MASS   7.3-33

Supported file formats

Tracks:

• BigWig (.bw) - http://genome.ucsc.edu/FAQ/FAQformat.html#format6.1
• Wiggle (.wig) - http://genome.ucsc.edu/goldenPath/help/wiggle.html
• BedGraph (with .wig extension) - http://genome.ucsc.edu/goldenPath/help/bedgraph.html

Features:

• BED - http://genome.ucsc.edu/FAQ/FAQformat.html#format1
• GFF - http://genome.ucsc.edu/FAQ/FAQformat.html#format3
• GTF (with .gff extension) - http://genome.ucsc.edu/FAQ/FAQformat.html#format4

Files must be formatted according to UCSC guidelines. All widely used chromosome names conventions are accepted, e.g. for human files either ‘chr1’ or ‘1’ can be used, however these conventions should not be mixed within single files.

Adding files

Press the Add files button to bring up the file upload panel.

File upload panel

You can drag and drop files here or press the Add files... button to open a file selection menu. Before starting the upload the following mandatory information must be provided about each file:

• User ID
• Reference genome - drop-down menu containing reference genome package currently installed in R

Comments are optional.

The contents of the text field can be copied to all files by clicking the icon at the left of the field. The default values can be set using Set defaults... button. Default values are stored using the browser cookies, and the settings will be remembered across different sessions as long as the same web browser is used. File extensions that are not supported will raise an error.

File upload panel with 4 files selected

Individual files can be uploaded by pressing ‘start’ next to the file name or all files can be uploaded at once by pressing the Start upload button at the top of file upload panel.

During the upload process a progress bar is displayed. After upload SeqPlots gives a message that upload was successful or or gives an error message. Common errors are misformatted file formats or chromosome names do not matched the reference genome. For more information please refer to Error explained chapter.

A feedback on successfully upload files

To dismiss the upload window, click on X or outside the window.

Downloading and removing files

Clicking the New plot set button brings up the file collection window. The primary function of this window is to choose signal tracks and feature files to use for calculating the plots. However, it also provides basic file management capabilities. Information on files can be reviewed and files can be downloaded or deleted. Fields can be searched, filtered and sorted by any column. The red x button on the right site of file table removes a single file from the collection, while Remove selected files button will erase all selected files.

The file collection window

Selecting files

The Tracks and Features tabs displays information about the files and allows you to filter and sort by any column. The “Search:” dialog allows you to find any keyword in any field, while dropdowns below the file grid allow for more advanced filtering on specific columns.

Select files by clicking on the file name or any other part of the row beside Show comment and Download or Remove buttons. Chosen files are highlighted in light blue. Clicking the file name again will cancel the selection. At least one signal track or motif and one feature file must be selected before starting the calculation.

Setting up plot options

Options controlling the plot settings is found below the file selection window:

1. Bin track @ [bp]: - this numeric input determines the resolution of data acquisition; the default value 10 means that 10bp intervals within the plotting range will be summarized by calculating the mean. Higher values increases the speed of calculation, but decreases resolution. See the explanations.
2. Choose the plot type - there are three options:
   • Point Features - anchor plot on the start of a feature. By default, plot will be directional if strand information is present (i.e, use start position and plot on positive strand for + strand features and use end position and plot on negative strand for minus strand features). If strand information is not present in the feature file (or if the “ignore strand” option is chosen), plot will use start position of feature and be plotted on the positive strand (see explanations). User chooses length of upstream and downstream sequence to plot.
   • Midpoint Features - similar to point feature, but plot is centered on the midpoint of the feature.
   • Endpoint Features - similar to point feature, but plot is centered on the end of the feature. Strand information is used by default to determine the end side.
   • Anchored Features - features are anchored at start and stop positions and given pseudo-length chosen by the user. Additionally, the user chooses the length of sequence upstream of the start and downstream of the end to plot.
3. Ignore strand - the directionality (strand) will be ignored all features plotted on the positive strand.
4. Ignore zeros - signal values of 0 in the track will be be excluded from calculations
5. Calculate heatmap - selecting this generates and saves a heat map matrix. Select if you wish to generate heatmap; uncheck if you only wish to generate average plots, as this will speed calculations.
6. Plotting distances in [bp] - the distances in to be plotted:
   • Upstream - the plotting distance in base pairs upstream to the feature
   • Anchored - the pseudo-length, to which the features will be extended or shrunk using linear approximation (only for anchored plots)
   • Downstream - the plotting distance in base pairs downstream to the feature

Plotting sequence motif density

The Sequence features tab allows you to calculate and plot the density of any user-defined motif around the chosen genomic feature using the reference sequence package. Motif plots can be mixed with track files’ signal plots. The following options can be set:

1. DNA motif - the DNA motif
2. Sliding window size in base pairs [bp] - the size of the sliding window for motif calculation. The value (number of matching motifs within the window) is reported in the middle of the window, e.g. if window is set to 200bp, DNA motif is “GC” and there are 8 CpGs in first 200 bp of the chromosome the value 8 will be reported at 100th bp.
3. Display name - The name of the motif that will be shown in key and heatmap labels. Leave blank to use DNA motif value.
4. Plot heatmap or error estimates - this checkbox determines if heatmap matrix and error estimates should be calculated. If unchecked much faster algorithm will be used for motif density calculation, but only the average plot without the error estimates will be available.
5. Match reverse complement as well - select if reverse complement motif should be reported as well. For example the TATA motif will report both TATA and ATAT with this option selected.

Sequence motifs selection tab

Clicking Add button adds the motif to plot set, while Reset All clears the motif selection. On the right side of the motif setting panel gives a list summary of included motifs.

Starting the plot set calculation

The options are executed by pressing the Run calculation button. This dismisses the file collection window and brings up the calculation dialog, which shows the progress. On Linux and Mac OS X (systems supporting fork based parallelization) the calculation can be stopped using the Cancel button - this will bring back all settings in file collection window.

The calculation progress dialog

After successful execution the plot array and plot preview panel will appear. In case of error an informative error pop-up will explain the problem. Please refer to the error section for further information.

The plot array

Previewing plot

After calculating or loading a plot set, a plot array of checkboxes is displayed to select the desired pairs of features and tracks/motifs. Clicking on the column name (tracks/motifs) or row name (features) selects/deselects the whole column or row. Clicking on top-left most cell of plot array toggles the selection of whole array.

Plot preview plus Line plot, Heatmap and refresh buttons

If at least one pair on plot array is selected pressing the Line plot button produces an average plot preview and the Heatmap button produces a heatmap preview. Alternatively, pressing the [RETURN] key will also produce the new selection and options. These operations are done automatically in reactive mode (see Advanced options chapter). Plots can be downloaded as PDF files using the Line plot and Heatmap buttons next to Download (at the top of the panel).

Below the plotting buttons are options for labeling plots and setting axes. On application start the first panel responsible for bringing file upload, management and plot set calculation modals is active. The further three panels hold common plot settings.

Titles and axis panel

The view on titles and axis panel

This panel groups settings influencing the plot main title, axis labels, various font sizes plus vertical and horizontal plot limits.

• Title - The main title of the plot, shown in top-center part of the figure; default empty
• X-axis label - Label shown below horizontal axis; default empty
• Y-axis label - Label shown below vertical axis; default empty
• Title font size - Font size of the title in points (point = ~1/72 an inch for standard A4 output); default 20 points
• Labels font size - Font size of axis labels in points; default 16 points
• Axis font size - Controls axis ticks font size, that is size of the numbers indicating position in base pairs on X-axis and means signal value on X-axis; default 14 points
• Set X-axis limits - Set hard plotting limits for X-axis; default values are whole range chosen during plot set calculation
• Set Y-axis limits - Set hard plotting limits for Y-axis; default values are a range between lowest and highest mean signal extended by error estimate

Guide lines and data scaling

The view on guide lines and data scaling

Controls in this panel controls the display of guide lines and error estimates, and allows to log scale the signal prior to plotting.

• Transform signal - if set to Log2 transform performs log2 transformation of the signal prior to plotting; default setting is Do not transform
• Show vertical guide line - show the vertical line at point 0 - beginning of the feature or midpoint and end of the pseudo-length scaled features (only for anchored plots); turn on by default
• Show horizontal guide line - show the horizontal line at user determined height; turn off by default
• Show error estimates - show error standard error and 95% confidence interval as fields, if turned off only the line representing the mean signal is shown; turn on by default

Keys, labels and colors panel

The view on keys, labels and colors panel (left). Color picker, label text input and Priority/Order checkboxes reviled on plot set grid (right).

This panel groups two types of controls. Colors, Label and Priority/Order are a checkboxes revealing further controls on plot set grid, specific for a feature-track pair or sub-heatmap. Show plot key, Show error estimate key and Legend font size re global controls specific for average plots. Inputs on plot set grid do not have specific labels, but the tooltip explaining their meaning is shown on mouse cursor hover.

• Colors - checkboxes revealing a color picker on plot set grid. This input allows to control the colors of specific feature-track pair average plots or sub-heatmaps. In browser supporting the color picker ‘e.g Chrome’ the system dialog will show up. In other browsers (e.g. Firefox) the javaScript color picker will be initialized.
• Label - checkboxes revealing a label text input plot set grid. This controls the names shown on the key with average plots or the heatmap top labels.
• Priority/Order - checkboxes revealing numeric input on plot set grid. These number determine the order of average plots and hetamaps. Feature-track pair with the highest priority will be listed on the top of key for average plots and left-most for heatmaps.
• Show plot key - shows the key giving the color to feature-track pair label mapping. If turned on the additional drop-down allows to choose the position on the plot, top-right by default
• Show error estimate key - shows the key gexplaining the meaning of error fields. If turnedon the additional drop-down allows to choose the position on the plot, top-left by default
• Legend font size - set the size of font used to plot the keys; 12 default

Heatmap setup tab

This tab has heatmap specific options for data processing and display.

The view on Heatmap setup tab (left). Color picker, Label text input, Priority/Order checkboxes, Choose individual heatmaps for sorting/clustering control and Set individual color key limits numric inputs reviled on plot set grid (right).

• Sort heatmap rows by mean signal - sorts the heatmap rows based on the mean value of each row across included sub-heatmps. Can be set to increasing or decreasing order. Turned off by default.

• Clustering algorithm - choose clustering algorithm (k-means, hierarchical or SupreSOM). If clustering is not desired, choose do not cluster, which uses the feature file in the uploaded order . K-means by default.

• Make cluster calculation repeatable - enforces, that clustering with non-deterministic algorithms, like k-means or SupreSOM will generate the same results as most recently plotted heatmap. This is achieved by re-using R random number generator seed.

• Plot selected cluster - this option is available only if Make cluster calculation repeatable is turned on. Allows to select one of the clusters and zoom it to whole plot height. Plot all clusters by default.

• Choose individual heatmaps for sorting/clustering - this checkbox brings up a new control panel on the plot set grid to determine if a given sub-heatmap should be included in plotting and/or clustering. The excluded sub-plots will be plotted in the order of the other sub-heatmaps, but their values will not influence the clustering/sorting. By default all sub-heatmaps are included.

• Heatmaps have individual color keys - by default all sub-heatmap have their own color keys. This option determines if each sub-heatmap should have a separate color key (plotted below the heatmap) or a single, common key should be calculated for all sub-plots (plotted rightmost). The example below show the difference between separate (left) and common (right) color keys:

  

  Heatmaps have individual color keys usage example: separate (left) and common (right) color keys

• Set default color key limits - this option determines the limits in mapping the numerical values to the colors. The range of colors generated is dependent on these options. Values lower or higher than the given limits will be plotted in the limit value color. If this checkbox is not selected, limits are auto-generated using Color key scaling parameter. If this option it turned off two numerical fields, min and max, are shown to manually set the limits.

  • Color key scaling - this slider influences how color key limits are generated. For example, 0.01 (default value) calculates limits using data ranging from 1-99 percentile of available data points. 0.1 uses data ranging from 10-90 percentile. The general formula for limit is: [quantile(data, Color key scaling); quantile(data, 1-Color key scaling)]
  • min and max numeric inputs - enter values to manually specify color key limits as numeric values.

• Set individual color key limits - this option is similar to manual set up of color key limits, but this allows one to specify different values for individual sub-heatmaps. When this checkbox is selected min and max numeric input menu is shown on the plot set grid

• Set colorspace - This input allows to use color palettes from RColorBrewer package, which would replace default color palette for heatmaps. By selecting Reverse checkbox the reversed color palette will be used. Here are available color pallets (click here to see example heatmap plotted with different color palettes):

  

  Color palettes from RColorBrewer

  When the Custom option is selected three-color pickers are shown to setup custom color mappings for heatmaps. The following example below shows standard jet colors (left), default blue color mapping after selecting the checkbox (middle) and custom color selection (right):

  

  Set default colorspace usage example: standard jet colors (left), default blue color mapping after selecting the checkbox (middle) and custom color selection (right)

Other options controlling heatmap appearance

The heatmap output shares many display options from other tabs. Here we provide a list of these inputs, please refer to “Viewing and manipulating plots” for further reference.

• Titles and axis panel
  • X-axis label - Label shown below horizontal axis, drawn separately for each sub-heatmap; default empty
  • Y-axis label - Label shown next to vertical axis, drawn separately for each sub-heatmap; default empty
  • Labels font size - Font size for axis labels and main labels of sub-heatmaps; default 16 points
  • Axis font size - Controls axis ticks font size; default 14 points
  • Set X-axis limits - Set hard plotting limits for X-axis; default values are whole range chosen during plot set calculation
• Guide lines and data scaling panel
  • Transform signal - if set to Log2 transform performs log2 transformation of the signal prior to plotting; default setting is Do not transform
  • Show vertical guide line - show the vertical line at point 0 - beginning of the feature or midpoint and end of the pseudo-length scaled features (only for anchored plots); turn on by default
• Keys, labels and colors panel
  • Colors - for hetmaps this input allows to control the color mapping of specific sub-heatmaps. The map starts with white (for low color key limit) and finishes with selected color (for high color key limit).
  • Label - allows to set up custom sub-heatmap top labels
  • Priority/Order - Use this to place heatmaps in your desired order. The feature-track pairs with the highest priority will be plotted as left-most sub-heatmaps.
  • Legend font size - control the font size of common color key, inactive if heatmaps have individual color keys; 12 default

PDF output size

The last tab (Batch operation and setup) on the tool panel includes batch operations and various other settings including PDF output size. By default the output PDF will be A4 landscape. This can be changed using the drop-down list to following settings:

• user defined - this option reveals two numeric inputs that allows to set output PDF width and height. The values must be given in inches.
• Legal rotated - US Legal landscape: 14" by 8.5"
• A4 - A4 portrait: - 8.27" × 11.69"
• Letter - US Letter portrait: 8.5" × 11"
• Legal - US Legal portrait: 8.5" × 14"
• Executive - a.k.a Monarch paper: 7.25 × 10.5"

The view on top part of batch operation and setup panel

Load or save plotset

Controls available on the “Load or save plotset” panel:

• Load saved plot set - drop-down list to select a plotset. Once the Rdata binary file is selected the plot grid will be displayed. Selecting the file reveals two additional buttons:
  • Remove dataset - this button deletes the selected saved plot set from user data.
  • Download plotset - this button saves a copy of the plotset in selected location.
• Save current plot set - Enter desired name and press the Save button (appears after input of name). It is also possible to save a copy of loaded plot sets. The plot set binary files can be renamed simply by loading them, saving a copy and deleting original source file.

All saved dataset can be found in data location/publicFiles. Any SeqPlots Rdata binaries put in the folder will become available for loading in Load saved plot set control.

The view on the “Load or save plotset” panel

Plot set files structure

The plot sets files can be also directly loaded in R. This allows further processing and customization of the plots. Data structure is a nested list, which elements be accessed by [[ R operator. The nesting goes as follow:

• feature - R list
  • track - R list
    • means - numeric vector giving mean signal value for each (binned) genomic position
    • stderror - numeric vector giving standard error for each (binned) genomic position
    • conint - numeric vector giving 95% confidence interval for each (binned) genomic position
    • all_ind - numeric vector giving the genomic position in base pairs
    • e - character string giveing numeric vector giving the indicates of anchored distance, NULL for point features plots
    • desc - auto generated title of the plot
    • heatmap - numeric matrix, (binned) signal values for each genomic position (columns) and each feature (rows)

The example structure:

List of 2
           $ HTZ1_Differential_genes_TOP100_v2.gff:List of 2
            ..$ HTZ1_JA00001_IL1andIL2_F_N2_L3_NORM_linear_1bp_IL010andIL009_averaged.bw    :List of 7
            .. ..$ means   : num [1:501] 2.52 2.52 2.52 2.53 2.54 ...
            .. ..$ stderror: num [1:501] 0.114 0.112 0.111 0.11 0.109 ...
            .. ..$ conint  : num [1:501] 0.226 0.223 0.221 0.218 0.217 ...
            .. ..$ all_ind : num [1:501] -1000 -995 -990 -985 -980 -975 -970 -965 -960 -955 ...
            .. ..$ e       : NULL
            .. ..$ desc    : chr "HTZ1_JA00001_IL1andIL2...\n@HTZ1_Differential_genes_TOP100_v2"
            .. ..$ heatmap : num [1:100, 1:501] 2.36 5.25 2.2 3.48 4.32 ...
            ..$ HTZ1_JA00001_IL3andIIL5_F_lin35_L3_NORM_linear_1bp_IL008andIL011_averaged.bw:List of 7
            .. ..$ means   : num [1:501] 2.36 2.35 2.35 2.36 2.38 ...
            .. ..$ stderror: num [1:501] 0.126 0.125 0.125 0.126 0.125 ...
            .. ..$ conint  : num [1:501] 0.249 0.249 0.247 0.251 0.249 ...
            .. ..$ all_ind : num [1:501] -1000 -995 -990 -985 -980 -975 -970 -965 -960 -955 ...
            .. ..$ e       : NULL
            .. ..$ desc    : chr "HTZ1_JA00001_IL3andIIL5...\n@HTZ1_Differential_genes_TOP100_v2"
            .. ..$ heatmap : num [1:100, 1:501] 2.61 3.17 1.42 2.46 4.26 ...
           $ HTZ1_Differential_genes_BOTTOM100.gff:List of 2
            ..$ HTZ1_JA00001_IL1andIL2_F_N2_L3_NORM_linear_1bp_IL010andIL009_averaged.bw    :List of 7
            .. ..$ means   : num [1:501] 1.57 1.57 1.58 1.6 1.62 ...
            .. ..$ stderror: num [1:501] 0.0996 0.0985 0.1003 0.1022 0.1018 ...
            .. ..$ conint  : num [1:501] 0.198 0.195 0.199 0.203 0.202 ...
            .. ..$ all_ind : num [1:501] -1000 -995 -990 -985 -980 -975 -970 -965 -960 -955 ...
            .. ..$ e       : NULL
            .. ..$ desc    : chr "HTZ1_JA00001_IL1andIL2...n@HTZ1_Differential_genes_BOTTOM100"
            .. ..$ heatmap : num [1:100, 1:501] 1.64 1.37 1.61 1.77 1.86 ...
            ..$ HTZ1_JA00001_IL3andIIL5_F_lin35_L3_NORM_linear_1bp_IL008andIL011_averaged.bw:List of 7
            .. ..$ means   : num [1:501] 1.94 1.94 1.95 1.96 1.97 ...
            .. ..$ stderror: num [1:501] 0.123 0.123 0.124 0.126 0.128 ...
            .. ..$ conint  : num [1:501] 0.244 0.245 0.246 0.251 0.253 ...
            .. ..$ all_ind : num [1:501] -1000 -995 -990 -985 -980 -975 -970 -965 -960 -955 ...
            .. ..$ e       : NULL
            .. ..$ desc    : chr "HTZ1_JA00001_IL3andIIL5...\n@HTZ1_Differential_genes_BOTTOM100"
            .. ..$ heatmap : num [1:100, 1:501] 1.61 1.37 1.29 3.04 3.77 ...

Old Mac OS X app

The Mac OS X bundle is an easy way to use SeqPlots for Mac OS X users. It contains all R binaries and packages that SeqPlots depends on. Additionally, test tracks and genome annotations, and reference sequences for Homo sapiens, Drosophila melanogaster and Caenorhabditis elegans are included. Sequences for other organisms can be downloaded using a graphical user interface.

System requirements

• Mac OS X 10.6 (Snow Leopard) or higher

Docker image

SeqPlots is available as Docker image, which can be easily run on Mac OS, Windows and Linux systems. The image can be obtained from Docker Hub: https://hub.docker.com/r/przemol/seqplots/

System requirements: Windows, Mac OS X, Linux or any other system supporting the Docker software. Refer to https://www.docker.com/ for details.

chmod -R a+w ~/SeqPlots_data

CHANGES IN VERSION 1.4.1

PACKAGE:

• RJSONIO replaced with jsonlite package for encoding/decoding JSON
• Sub-heatmaps accepts multilevel color palettes in plotHeatmap function
• Better dendrogram positioning for heatmaps with hclust and single sub-heatmap

GUI:

• “Load saved plot set” select input replaced with searchable selectize input
• Tracks and feature names are shown without extensions
• Plot Preview GUI elements are shown directly after calculation finishes or save dataset si loaded, even if no pair is selected.
• Download buttons moved to bottom of side panel
• Color palettes from RColorBrewer package can be selected in GUI
• Web interface tab for managing the reference genomes

BUGFIX:

• Plot Preview shows up when needed with shiny 0.12.0 (issue #6)
• Heatmap top labels and color key font sizing works properly
• Clustering report download works when source feature file were deleted

CHANGES IN VERSION 1.3.0

• New package version for Bioconductor 3.1 release

CHANGES IN VERSION 1.2.0

PACKAGE:

• plot a dendrogram as first panel on heatmap plot clustered with hierarchical clustering
• heatmap can be plotted as vector graphics (default for R scripting) or raster graphics (default for web GUI)
• heatmaps can be sorted in increasing or decreasing order
• y-axis is annotated with cluster IDs and number of data rows (heatmap)
• x-axis is annotated with base pairs, e.g. 10bp, 1kb, 1.2Mb, etc.
• heatmaps can be plotted using GGplot2 package instead of R base graphics system
• speed-up in motif plots thanks to faster, vectored implementation of motif density data acquisition
• code simplification - seqplots in Shiny GUI mode use all functions from package core

GUI:

• feature-track pairs selection grid have UI elements to multi-select and batch change labels/colors/etc.
• option to make a clustering repeatable (works by reusing a .Random.seed)
• option to plot selected cluster only as heatmap
• SeqPlots GUI updated to work with Bootstrap v3.3.1

BUGFIX:

• lines separating the clusters are drawn in correct places on grDevices::quartz devices
• proper positioning of 3’ ends of anchored region in motif plot
• fixed error with anchored plots and genomic feature width equals 1bp
• y-axis does respect cex.axis parameter
• GUI fixed to work with shiny 0.11.0 and above

CHANGES IN VERSION 1.0.0

PACKAGE:

• plotHeatmap function returns cluster report as GRanges structure
• redundant parameters removed from plotting functions
• plotHeatmap function have “embed” parameter for plotHeatmap - allows to plot 1st heatmap without using grid system, intended to use with complex plots

BUGFIX:

• motif plot orientation properly dependents on strand
• GUI - reordering the heatmap respects previously set include/exclude parameters

CHANGES IN VERSION 0.99.1

PACKAGE:

• heatmap plotting function returns cluster report ad data.table
• getPlotSetArray function have “verbose” parameter that controls messages and warnings output
• references added to documentation

BUGFIX:

• plotHeatmap and plotAverage generic methods for SeqPlots-classes respect the parameters
• package passes tests and check on 32bit Windows (plotting only, because no rtrackalyer::BigWigFile support for Win32)

CHANGES IN VERSION 0.99

GENERAL:

• Anchored plots and heatmaps uses [downstream]–0–0–[upstream] X-axis coordinate system instead [downstream]–0–[anchored]-[upstream+anchored]

PACKAGE:

• package really on reference class system including MotifSetup, PlotSetArray, PlotSetList and PlotSetPair
• generic subset and data manipulation methods for SeqPlots-classes including ‘[’, “[[” and “unlist”, which allows to switch between classes
• automatic tests for class system, calculations and plotting functions
• documentation for all functions and classes
• PDF vignette engine replaced by HTML one
• QuickStart vignette added

GUI:

• automated GUI tests using Rselenium package

BUGFIX:

• issue #1: some server instances loads empty .Rdata file on startup

CHANGES IN VERSION 0.9.3

• The web GUI and R package projects merged into singe project distributed as Bioconductor compatible R package
• The command line interface have the same capabilities as GUI version
• Web GUI vignette added

CHANGES IN VERSION 0.9.2

GENERAL:

• use Cairo package for plotting, X11 installation no longer required
• colors in plot grid are initiated automatically (same color palette as for auto-generated average plots), white color is allowed
• more informative error messages during file upload
• documentation is integrated with SeqPlots GUI help
• Web GUI debug console added
• Exit button, that closes web interface and background R process

BUGFIX:

• fixed errors reporting in singe core/Windows mode
• the custom color gradient controls for hetmap (three color pickers) work correctly now
• heatmap main title no longer overlaps with sub-plot labels

CHANGES IN VERSION 0.9.1

GENERAL:

• inputs and features sorted alphabetically
• DataTables v1.10.0 with pagination, selection number indicator and infinite row selections
• buttons for heatmap and lineplots, PDF default sizes,
• changes in GUI layout
• default PDF output paper size set to A4 horizontal,
• Font sizes are in points
• preview is compatible with A4 PDF output (at 100 DPI)
• color key for heatmap are always generated using image.plot function that provides better labeling
• batch plots do not override individual labels if set
• option to keep 1:1 aspect ratio (default for batch plots)
• miscellaneous options renamed for clarity

CHANGES IN VERSION 0.9.0

FEATURES:

• Multi-plot grid option in batch mode - many line plots on single page

GENERAL:

• R 3.1 and BioC 2.14 compatibility
• faster BigWig signal retrieval, no need for modified rtracklayer C code in the package
• warning message if JS File API is not supported (old browsers)
• improved the performance of heatmap plotting by using list of matrices instead concatenated matrix

BUGFIX:

• application start properly without any BSGenome genomic packages installed
• cluster report - the final order agrees with cluster indicates

CHANGES IN VERSION 0.8.2

FEATURES:

• Hierarchical and super self-organizing network clustering added for heatmaps
• Anchored motif plots
• The row order of the heatmap is exported along with cluster report

GENERAL:

• JS color picker added for browsers, that do not support select input type=“color” i.e. Firefox (checked with modernizr.js library)
• Single process mode and Microsoft Windows compatibility (running without fork parallelization)
• Shiny 0.9.1 compatibility
• Saved datasets can be downloaded for local usage
• Clicking row or column name in plot grid toggles the checkboxes
• Minor GUI changes

CHANGES IN VERSION 0.8.1

GENERAL:

• GUI redesign: plot matrix incorporates sub-plot/heatmap specific controls, all heatmap options gathered in single tab
• warning before closing/refreshing a webpage with active session
• cookie based default options: user, genome and deactivate page exit warning
• heat-map clusters provided as cluster report - a CSV file containing original features, annotations and cluster information, see more: https://bitbucket.org/przemol/seqplots/wiki/Heatmaps#markdown-header-cluster-report
• Wiggle files processing: correct for multiple header definitions and roman/arabic chromosome names correction
• Optimised keyboard shortcuts: plot - RETUTRN or ctrl/cmd+SPACE, switch heatmap - ctrl/cmd+H, switch reactive plotting - ctrl/cmd+R
• minor speed improvement

BUGFIX:

• Motif density plots and heatmaps: flip rows on (-) strand

CHANGES IN VERSION 0.8.0

GENERAL:

• GUI redesign, option partitioned to more tabs
• preview plot is zoomed on click rather than on mouse hover
• possibility to remove multiple files
• comments visible as popup in file managmed window
• all chromosome naming conventions (most notably chrX/X and variants of chrM/M/MtDNA/MT etc.) are accepted (http://www.bioconductor.org/packages/release/data/annotation/html/seqnames.db.html)
• incoming featurefiles (GFF and BED) are not processed, just chacked for errors
• explicit error handling for incoming flies, the line with problem or unexpected chromosome(s) are indentified to the user
• motif density tracks can be binned (defoult at 10bp)
• tracks amd motif densities cna be mixed together in plots

SERVER:

• server_config.R added - a configuration file that allows to set up server varaiables, e.g. the user data location

MAC OS X APP:

• interface to insrall new genomes from Bioconductor and local resources (R BSgemome format: http://www.bioconductor.org/packages/release/bioc/html/BSgenome.html)
• option to set up data location

CHANGES IN VERSION 0.7.0

• SeqPlots for Mac OS X relesed - an user frienddly wrapper app containig R, packages and SeqPlots coede
• heatmap plotting added
• motif denstty plotting added for lineplot and heatmap
• minior interface redesign
• reactive interface can be turn off for plottting, user plots on demend
• adding files from jQuery File Upload (http://blueimp.github.io/jQuery-File-Upload/) is handled directly by R eliminating additional node.js server application and making proper file handling for desktop version
• computationally expensive operations (calculating plot matrix and plotting) are handeled by new R process (parallel R library) - many proces can run simmutainously in same Shiny instance, user can get fedback from the calcualtion can be cancelled

CHANGES IN VERSION 0.6.0

• Shiny (https://github.com/rstudio/shiny) used as R web fraimwork, support for Rserver/EXT JS version dropped
• support for 145 genomes from UCSC database (via user provideing valid genome symbol)
• new reactive user interface
• new plot type: midpoint features - it calculates the middle of given features and centres the summary on it
• the option to ignore the strand (plot always in the same direction)
• the option to remove the zeros (0 value of score in Wiggle track) from mean and error estimate calculations
• the support for BED feature files (in addition to GFF, Wiggle (all variants), BigWiggle)
• automatic chromosome name correction for C. elegans genomes (I => chrI, MtDNA => chrM, etc.)
• accepts wiggle with overlapping ranges (e.g. microarray experiments processed using MA2C)
• basic user management for uploaded files
• option to download the features and track files directly from application

CHANGES IN VERSION 0.5.0

• Initial test and alpha releases