Generating iToL annotations from Spreadsheet or CSV files
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README.md

table2itol

About

Interactive Tree of Life (iTOL) is a popular tool for displaying phylogenetic trees and associated information. The table2itol.R script makes it easy to generate iTOL annotations from spreadsheet files.

Features

  • Works with CSV, OpenOffice, LibreOffice and Microsoft Excel files.
  • Supports iTOL domains, colour strips, simple bars, gradients, binary data, heat maps, and texts.
  • Partially supports iTOL branch annotation (currently work in progress).
  • By default selects the appropriate visualisation from the data type of each input column but this can be modified by the user.
  • Provides carefully chosen colour vectors for up to 40 levels and optionally combines them with symbols for maximizing contrast.
  • The default colour vectors can be replaced by user-defined colour vectors.
  • Can be used either interactively on any operating system on which R is running, or non-interactively using the command line of a UNIX-like system.

Prerequisites

  • A recent (>= 3.2.0) version of R.
  • The optparse package for R if you want to run the script in non-interactive mode or if you want to read the help message (which is placed in tests/table2itol_help.txt, too).
  • The plotrix package for R if you want to generate branch annotations from continuous numeric data.
  • The readxl package for R if you want to apply the script to Microsoft Excel files.
  • The readODS package for R if you want to apply the script to Libreoffice or Openoffice ods files.
  • The yaml package for R if you want to define colour vectors yourself.

Please note that explaining how to correctly install R is beyond the scope of this manual, and please do not contact the table2itol.R authors about this issue. There is plenty of online material available elsewhere. As for the installation of R packages see the FAQ below.

Installation

First, obtain the script as indicated on its GitHub page.

Command-line use

The following explanations are for non-experts; there is nothing special with running this script in command-line mode on UNIX-like systems. First, if necessary make the script executable:

chmod +x table2itol.R

Then call:

./table2itol.R

to obtain the help message. If this yields an error, see the troubleshooting chapter.

Optionally place the script in a folder that is contained in the $PATH variable, e.g.

install table2itol.R ~/bin

or even

sudo install table2itol.R /usr/local/bin

if you have sudo permissions. Then you can call the script by just entering

table2itol.R

Interactive use

Open R or RStudio or whatever interface to R you are using, then enter at the console:

source("table2itol.R")

provided the script is located in the current working directory as given by getwd(). Alternatively, first use setwd() to move to the directory in which table2itol.R resides or enter the full path to the location of the script.

When loading the script it shows the usual help message and an indication that you are running it in interactive mode. When doing so, you might need to modify the arguments of the function much like command-line users might need to apply certain command-line options. For instance, in analogy to entering:

./table2itol.R --na-strings X --identifier Tip --label Name ann1.tsv ann2.tsv

on the command line of a UNIX-like system, you would enter within R the following:

source("table2itol.R")
create_itol_files(infiles = c("ann1.tsv", "ann2.tsv"),
  identifier = "Tip", label = "Name", na.strings = "X")

The analogy should be obvious, hence for details on the arguments of create_itol_files see the help message. The arguments of the function are identical to the long version of the arguments of the script, subjected to the replacement of dashes by dots to yield syntactic names. The sole mandatory argument of the function is infiles, whose value is identical to the positional arguments of the script. With some basic knowledge of R it is thus easy to set up customized scripts that set the arguments for your input files and generate the intended output.

Examples

Exemplars for input table files are found within the tests/INPUT folder. A list of examples for calling table2itol.R is found in tests/examples.txt.

Experts only: On a UNIX-like system you can run these examples by calling tests/run_tests.sh provided a modern Bash is installed. The versions of R and the R packages used for testing by the maintainer are found in the file tests/R_settings.txt.

Troubleshooting

Some commonly encountered error messages are mentioned in the following. Note that you might actually get these error messages in a language other than English (e.g., your own language) or with other minor modifications.

Command-line use

Bad interpreter

/usr/local/bin/Rscript: bad interpreter: No such file or directory

Solution: Enter

locate Rscript

and watch the output. If it is empty, you must install R first. If you instead obtained a location such as /usr/bin/Rscript you could do the following:

sudo ln -s /usr/bin/Rscript /usr/local/bin/Rscript

if you had sudo permissions. Alternatively, within the first line of the script replace /usr/local/bin/Rscript by /usr/bin/Rscript or wherever your Rscript executable is located. A third option is to leave the script as-is and enter Rscript table2itol.R instead of ./table2itol.R or whatever location of the script you are using. But this is less convenient in the long run.

Please note that explaining how to correctly install R is beyond the scope of this manual, and please do not contact the table2itol.R authors about this issue. There is plenty of online material available elsewhere.

Command-line or interactive use

Missing R package

there is no package called 'optparse'

Solution: Install the optparse package for R. (It is not an absolute requirement in interactive mode but without it you would not see the help message. However, this message is placed in tests/table2itol_help.txt anyway.)

there is no package called 'plotrix'

Solution: Install the plotrix package for R. (It is only needed if you want to create branch annotations from continuous numeric data.)

there is no package called 'readODS'

Solution: Install the readODS package for R. (It is only needed if you want to apply the script to ods files.)

there is no package called 'readxl'

Solution: Install the readxl package for R. (It is only needed if you want to apply the script to Microsoft Excel files.)

there is no package called 'yaml'

Solution: Install the yaml package for R. (It is only needed if you want to use the script in conjunction with your own colour vectors.)

Please note that explaining how to correctly install R is beyond the scope of this manual, and please do not contact the table2itol.R authors about this issue. There is plenty of online material available elsewhere. As for the installation of or R packages see the FAQ below.

Outdated R version

need a newer version of R, 3.2.0 or higher

Solution: Install a newer version of R.

Please note that explaining how to correctly install R is beyond the scope of this manual, and please do not contact the table2itol.R authors about this issue. There is plenty of online material available elsewhere.

The script generates not enough output files

Solution: Watch the warnings and error messages generated by the script. Without any input files, the script should not generate any output. The script would also skip input files or single tables if they failed to contain columns you have requested. You can use the --abort option to let the script immediately stop in such cases, then look up the last error message in this manual. But even without --abort the script generates warnings when data sets get skipped.

The script generates too many output files

Solution: Accept as a design decision that the scripts generates one file for each input column (except for the tip identifier column and when a heatmap is created). Since you can still decide to not upload (some of) the generated files to iTOL and also deselect data sets within iTOL, we believe it would not make much sense to also include a selection mechanism within the table2itol.R script. As last resort you could also reduce the number of input columns. However, if you are mainly concerned about the script cluttering up your working directory with files, simply consider using the --directory option to place all output files in a dedicated directory. An empty argument to this option causes the script to place every output file in the directory in which the respective inout file resides.

A column is requested but missing

selected column 'ID' does not exist

Solution: Use the --identifier option to set the name of the tip identifier column.

selected column 'Label' does not exist

Solution: Use the --label option to set the name of the tip label column.

A name clash of output file names occurs

name clash: file [...] has already been generated

Solution: Name the columns distinctly in distinct tables within the same file and/or call the table2itol.R script individually for each input file, maybe best with distinct values of --directory.

Since the name of each output file is generated from the name of the respective input column and the resulting kind of visualisation, columns from distinct input tables but with the same name and the same resulting kind of visualisation would yield only a single output file. Instead of silently overwriting the earlier ones, the script stops with an informative error message.

Frequently asked questions

How can I install the required R packages?

There are several ways to obtain, install and update R packages. From within R, we found the following approach to be convenient:

source("http://bioconductor.org/biocLite.R")
biocLite(c("optparse", "plotrix", "readODS", "readxl", "yaml"))

This should under normal circumstances install or update all R packages recommended for table2itol.R.

Please note that explaining in greater detail how to correctly install R packages is beyond the scope of this manual, and please do not contact the table2itol.R authors about this issue. There is plenty of online material available elsewhere. The table2itol.R authors cannot guarantee that the script provided by BioConductor works as expected.

How can I generate other kinds of visualisation from integer columns?

For generating distinct kinds of visualisation from distinct integer columns, run the script several times with distinct values of --conversion. Since the name of each output file is generated from the name of the respective input column and the resulting kind of visualisation, nothing of importance will be overwritten (but see the section on name clashes between distinct spreadsheets).

How can I generate other kinds of visualisation from non-integer numbers?

You can create bar charts instead of gradients from numbers with decimal points by using the --double-to-bars option. Note that the number of decimal points of the range as shown in the legend can be modified using the --precision option, as usual.

How can I define my own colour vectors?

For replacing the default colour vectors by other colour vectors, use the --colour-file option. Its argument must be the name of a file in YAML format. The tests/INPUT folder contains an example file with user-defined colours.

Names for the colour vectors are optional in such files but increase readability. Not all colour vectors need to be defined, only those that should replace certain default colour vectors. Assignment is solely by vector length.

An attempt is made to standardize the input colours, yielding hexadecimal codes understood by iTOL. Thus all kinds of colour specifications can be used that are accepted by the col2rgb function. Non-interpretable and duplicate colours yield an error. Call colors() to obtain the list of human-readable colour names accepted by R. You might also want to visit the colorbrewer web site for generating useful colour vectors.

How can I distinctly assign symbols?

For assigning symbols (to be used in combinations of symbols and colours) according to certain groups, use the --emblems option. This does not individually assign symbols but the symbols will then be consistently assigned according to some column. For triggering the earlier use of symbols (instead of using more colours), play around with --favour and --max-size.

How can I assign specific colours to binary data?

Binary data are interpreted by the script either as factors with two levels or as logical vectors. Logical vectors yield distinct kinds of output files, and the script already picks distinct colours and symbols for distinct logical vectors in turn. To get columns understood as logical vectors their fields must (in addition to NA values, if any) only contain values from one of the following pairs: 0/1, true/false, t/f, yes/no, y/n or on/off. This considerably extends the values recognized by base R as logical vectors on input. Moreover, case differences do not matter, but you cannot mix any of these variants. These conversions get turned off when using --conversion keep or --conversion double.

Colours defined using --colour-file only play a role for columns treated as factor, not for those yielding a logical vector. To set the colours used for end points as gradients as well as for binary data, use the --gradient-file argument. In contrast, one cannot modify the symbols used; this would not make much sense though, since iTOL understands only certain symbols anyway.

How can I generate a heat map?

A heat map is automatically generated from a data frame when all columns (except for the special columns addressed using --identifier, --label and --background) are numeric (uniformly of mode double or uniformly of mode integer). These columns get merged into a single file whose name is derived from the name of the identifier column. You might need the --conversion argument to obtain columns that are uniformly numeric.

The colours appear too strong. What can I do?

The argument --opacity can be used to defined the so-called alpha channel of each colour. Set the opacity to a value between 0 and 1 to obtain more transparent colours (1 means fully opaque and 0 means fully transparent, which is not normally very useful). Also note that some colours can be modified with few clicks in iTOL itself. But instead of attempting to modify the files generated by table2itol.R with tools such as sed or by hand we suggest to contact the table2itol.R authors with an according feature request.