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@ -9,7 +9,7 @@
[![The MIT License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE.txt) [![The MIT License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE.txt)
[![DOI](https://zenodo.org/badge/283230219.svg)](https://zenodo.org/badge/latestdoi/283230219) [![DOI](https://zenodo.org/badge/283230219.svg)](https://zenodo.org/badge/latestdoi/283230219)
YouPlot is a command line tool that draws plots in a terminal. YouPlot is a command line tool that draws plots in the terminal.
:bar_chart: Powered by [UnicodePlot](https://github.com/red-data-tools/unicode_plot.rb) :bar_chart: Powered by [UnicodePlot](https://github.com/red-data-tools/unicode_plot.rb)
@ -23,8 +23,7 @@ gem install youplot
## Quick Start ## Quick Start
* `cat data.tsv | uplot <command> [options]` or `uplot <command> [options] <data.tsv>`
* `uplot <command> [options] <data.tsv>`
### barplot ### barplot
@ -103,10 +102,6 @@ curl -sL https://git.io/IRIStsv \
### count ### count
In this example, YouPlot counts the number of chromosomes where the gene is located from the human gene annotation file and it creates a bar chart. The human gene annotation file can be downloaded from the following website.
* https://www.gencodegenes.org/human/
```sh ```sh
cat gencode.v35.annotation.gff3 \ cat gencode.v35.annotation.gff3 \
| grep -v '#' | grep 'gene' | cut -f1 \ | grep -v '#' | grep 'gene' | cut -f1 \
@ -117,13 +112,16 @@ cat gencode.v35.annotation.gff3 \
<img alt="count" src="https://user-images.githubusercontent.com/5798442/101999832-30b1ae80-3d24-11eb-96fe-e5000bed1f5c.png"> <img alt="count" src="https://user-images.githubusercontent.com/5798442/101999832-30b1ae80-3d24-11eb-96fe-e5000bed1f5c.png">
</p> </p>
In this example, YouPlot counts the number of chromosomes where genes are located.
* [GENCODE - Human Release](https://www.gencodegenes.org/human/)
Note: `count` is not very fast because it runs in a Ruby script. Note: `count` is not very fast because it runs in a Ruby script.
This is fine in most cases, as long as the data size is small. If you want to visualize huge data, it is faster to use a combination of common Unix commands as shown below. This is fine in most cases, as long as the data size is small. If you want to visualize huge data, it is faster to use a combination of common Unix commands as shown below.
```sh ```sh
cat gencode.v35.annotation.gff3 | grep -v '#' | grep 'gene' | cut -f1 \ cat gencode.v35.annotation.gff3 | grep -v '#' | grep 'gene' | cut -f1 \
| sort | uniq -c | sort -nrk2 | awk '{print $2,$1}' \ | sort | uniq -c | sort -nrk1 \
| uplot bar -d ' ' -t "The number of human gene annotations per chromosome" -c blue | uplot bar --fmt yx -d ' ' -t "The number of human gene annotations per chromosome" -c blue
``` ```
## Usage ## Usage
@ -143,18 +141,7 @@ YouPlot is a command line tool for this purpose. With YouPlot, you can continue
| `uplot <command> [options] data.tsv ...` | Take input from files | | `uplot <command> [options] data.tsv ...` | Take input from files |
| `pipeline1 \| uplot <command> -O \| pipeline2` | Outputs data from stdin to stdout | | `pipeline1 \| uplot <command> -O \| pipeline2` | Outputs data from stdin to stdout |
### Where to output the plot? ### Subcommands
By default, the plot is output to *standard error output*.
The output file or stream for the plot can be specified with the `-o` option.
### Where to output the input data?
By default, the input data is not shown anywhere.
The `-O` option, with no arguments, outputs the input data directly to the standard output.
This is useful when passing data to a subsequent pipeline.
### What types of plots are available?
The following sub-commands are available. The following sub-commands are available.
@ -174,6 +161,17 @@ See Quick Start for `count`.
|-----------|-------|----------------------------------------------------------| |-----------|-------|----------------------------------------------------------|
| count | c | draw a barplot based on the number of occurrences (slow) | | count | c | draw a barplot based on the number of occurrences (slow) |
### Where to output the plot?
By default, the plot is output to *standard error output*.
The output file or stream for the plot can be specified with the `-o` option.
### Where to output the input data?
By default, the input data is not shown anywhere.
The `-O` option, with no arguments, outputs the input data directly to the standard output.
This is useful when passing data to a subsequent pipeline.
### What if the header line is included? ### What if the header line is included?
If your input data contains a header line, you need to specify the `-H` option. If your input data contains a header line, you need to specify the `-H` option.