Metadata-Version: 2.1
Name: igv-notebook
Version: 0.5.1
Summary: Package for embedding the igv.js genome visualization in IPython notebooks
Home-page: https://github.com/igvteam/igv-notebook
Author: Jim Robinson
License: MIT
Description: # igv.js notebook module
        
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/igvteam/igv-notebook/main?filepath=examples)   _**Jupyter Notebook**_
        
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/igvteam/igv-notebook/main?urlpath=lab/tree/examples)  _**JupyterLab**_
        
        [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1-4P_r07Dq-WxaOVUevlbHvVhC9Y11FWC?usp=sharing)    _**Google Colab**_
        
        [![PyPI](https://img.shields.io/pypi/v/igv-notebook?label=pypi%20package)](https://pypi.org/project/igv-notebook/)
        
        ============
        
        igv-notebook is a Python package which wraps [igv.js](https://github.com/igvteam/igv.js) for embedding in an IPython notebook.
        Both Jupyter and Google Colab platforms are supported. 
        
        ### Related projects
        
        Other projects enabling embedding igv.js in notebooks include
        
        * [igv-jupyter](https://github.com/g2nb/igv-jupyter)  (wrapper around igv-notebook that adds g2nb integration)
        * [igv-jupyterlab](https://github.com/epi2me-labs/igv-jupyterlab)
        * [ipyigv](https://github.com/QuantStack/ipyigv)
        
        The main differences between igv-notebook and these other projects are: 
        
        * igv-notebook is a Python package, while the projects listed above are Jupyter extensions;
        * igv-notebook works with Google Colab, in addition to Jupyter and JupyterLab; and 
        * igv-notebook supports loading data files from any location on the local or mounted file system when used with Jupyter Notebook or 
        Google Colab.  **_NOTE_**: General local file paths do not work with JupyterLab, for JupyterLab the files must be in the JupyterLab file tree.
        
        
        ### Examples
        
        Example notebooks are available in the github repository, and can be run from the Binder and Colab links above. 
        To download examples without cloning the repository use this 
        [link](https://github.com/igvteam/igv-notebook/archive/master.zip). Notebooks are available in the
        "examples" directory.
        
        ## Usage
        
        Typical usage proceeds as follow
        
        1. Install igv-notebook
        2. Initialize igv-notebook
        3. Create igv "browser" object
        4. Add tracks to browser 
        5. Navigate to loci of interest
        
        **Installation**
        
        ```bash
        pip install igv-notebook
        ```
        
        **Initialization**
        
        After installing, import and intialize igv_notebook as follows. 
        
        ```python
        import igv_notebook
        igv_notebook.init()
        ```
        For a Jupyter notebook this should be done once per notebook.   Colab notebooks display output in a sandboxed iFrame 
        for each cell, so initialization must be repeated for each cell in which  igv-notebook is used.
        `
        
        ### Browser creation
        
        The Browser initializer takes a configuration dictionary which is converted to JSON and passed to the igv.js
        createBrowser function. The configuration options are described in the
        [igv.js documentation](https://github.com/igvteam/igv.js/wiki/Browser-Configuration-2.0).
        
        **Example:**
        
        ```python
        import igv_notebook
        igv_notebook.init()
        igv_browser= igv_notebook.Browser(
            {
                "genome": "hg19",
                "locus": "chr22:24,376,166-24,376,456",
                "tracks": [{
                    "name": "BAM",
                    "url": "https://s3.amazonaws.com/igv.org.demo/gstt1_sample.bam",
                    "indexURL": "https://s3.amazonaws.com/igv.org.demo/gstt1_sample.bam.bai",
                    "format": "bam",
                    "type": "alignment"
                }],
                "roi": [
                    {
                        "name": "ROI set 1",
                        "url": "https://s3.amazonaws.com/igv.org.test/data/roi/roi_bed_1.bed",
                        "indexed": False,
                        "color": "rgba(94,255,1,0.25)"
                    }
                ]
            }
        )
        ```
        
        ### URLS and paths
        
        Configuration objects for igv.js have properties to specify URLs to files for data and indexes.  These properties are 
        supported in igv-notebook, however igv-notebook also provides equivalent ```path``` properties for specfiying paths to 
        local files when used with Jupyter Notebook or Colab.  (_**Note**_: The ```path``` properties cannot be used with JupyterLab, however local files can
        be loaded by URL if they are in the Jupyter file tree).  The ```path``` properties are useful for:
        
        * loading data in a Colab notebook from the local Colab file system or a mounted Google Drive; and
        * loading data in Jupyter Notebook from the local file system that is outside the Jupyter file tree. 
        
        **URL and Path properties**
        | igv.js url property  | igv-notebook path property |
        | --------- | ----------- |
         | url  | path |
         | indexURL | indexPath |
         | fastaURL | fastaPath |
         | cytobandURL | cytobandPath |
         | aliasURL | aliasPath | 
        
        
        For Jupyter servers (Notebook and Lab), local files can be also be loaded via the url property if the file is in the Jupyter 
        startup directory tree.  This will usually yield better performance than using ```path``` properties.  URL paths 
        that begin with a "/" are relative to the Jupyter server startup directory, i.e. the directory from where you 
        started Jupyter Notebook or JupyterLab.  For Jupyter Notebook, URL paths without a leading slash can be used and are 
        assumed to be relative to the notebook  directory.  See below for examples.  You can also use the "download url" for 
        the file, obtainable through the JupyterLab UI, as the URL for igv.
        
        ### Tracks
        
        To load a track, pass a track configuration object to ```igv_browser.load_track()```. Track configuration
        objects are described in the [igv.js documentation](https://github.com/igvteam/igv.js/wiki/Tracks-2.0), however
        see the note on _URLs and paths_ above. The configuration object will be converted to JSON and passed to the igv.js browser instance.
        
        Data for the track can be loaded by URL, file path, or passed directly as an array of JSON objects.
        
        
        **Examples:** 
        
        Local file - Jupyter. URL relative to the location of the notebook 
        
        ```python
        igv_browser.load_track(
            {
                "name": "Local BAM",
                "url": "data/gstt1_sample.bam",
                "indexURL": "data/gstt1_sample.bam.bai",
                "format": "bam",
                "type": "alignment"
            })
        
        ```
        
        Local file - Jupyter.  URL relative to root of Jupyter file tree
        
        ```python
        igv_browser.load_track(
            {
                "name": "Local BAM",
                "url": "/examples/data/gstt1_sample.bam",
                "indexURL": "/examples/data/gstt1_sample.bam.bai",
                "format": "bam",
                "type": "alignment"
            })
        
        ```
        
        Local file - Jupyter.  Absolute file path, potentially outside the Jupyter file tree.  Note the use of ```path``` and ```indexPath```.
        
        ```python
        igv_browser.load_track(
            {
                "name": "Local BAM",
                "path": "/any_path_you_like/data/gstt1_sample.bam",
                "indexPath": "/any_path_you_like/data/gstt1_sample.bam.bai",
                "format": "bam",
                "type": "alignment"
            })
        
        ```
        
        
        
        Local file - Colab.  In Colab files are loaded by file path.
        
        ```python
        igv_browser.load_track(
            {
                "name": "Local BAM",
                "path": "/content/igv-notebook/examples/data/gstt1_sample.bam",
                "indexPath": "/content/igv-notebook/examples/data/gstt1_sample.bam.bai",
                "format": "bam",
                "type": "alignment"
            })
        ```
        
        Remote file - Jupyter.   
        
        ```python
        igv_browser.load_track(
            {
                "name": "BAM",
                "url": "https://s3.amazonaws.com/igv.org.demo/gstt1_sample.bam",
                "indexURL": "https://s3.amazonaws.com/igv.org.demo/gstt1_sample.bam.bai",
                "format": "bam",
                "type": "alignment"
            })
        
        ```
        
        
        ### API
        
        Most IGV options can be specified in the initial browser configuration, including specifying genome, locus, tracks, and regions-of-interest.  Additional methods are provided to perform actions on the browser post-creation.  These are described below
        
        #### Load a track**
        
        To load a track
        
        ```
        igv_browser.load_track(track_config)
        ```
        
        See example track configurations above.   Also [igv.js  wiki](https://github.com/igvteam/igv.js/wiki/Tracks-2.0)
        
        
        Example:
        
        ```python
        igv_browser.load_track(
            {
                "name": "Local BAM",
                "url": "data/gstt1_sample.bam",
                "indexURL": "data/gstt1_sample.bam.bai",
                "format": "bam",
                "type": "alignment"
            })
        
        ```
        
        #### Load regions of interest**  (version >= 0.4.0)
        
        Regions-of-interest are overlays marking genomic ranges of interest.  They are defined by track configurations, often backed by a "bed" file, and usually with a translucent color.  These can be specified at browser creation with the "roi" property, or loaded afterwards with the ```loadROIs`` function.  This function takes an array of track configuration objects.   See the notebook examples/ROI.ipynb for example usage.
        
        ```
        igv_browser.loadROIs([roi_configs])
        ```
        
        
        #### Navigation
        
        Jump to a specific genomic range
        
        ```python
        igv_browser.search('chr1:3000-4000')
        
        ```
        
        Jump to a specific gene. This uses the IGV search web service, which currently supports a limited number of 
        [genomes](https://s3.amazonaws.com/igv.org.genomes/genomes.json).  To customize the search, load a non-indexed annotation
        track with the "searchable" property set to true (see [igv.js documentation](https://github.com/igvteam/igv.js/wiki/Annotation-Track#configuration-options)).
        
        
        ```python
        igv_browser.search('myc')
        
        ```
        
        Zoom in by a factor of 2
        
        ```python
        igv_browser.zoom_in()
        ```
        
        Zoom out by a factor of 2
        
        ```python
        igv_browser.zoom_out()
        ```
        
        ### SVG conversion - Jupyter Notebook only
        
        To convert the current igv view to a static SVG image 
        
        ```python
        igv_browser.to_svg()
        ```
        
        This action can also be invoked with the "To SVG" button on the igv.js command bar.  This is useful when converting 
        the notebook to formats such as HTML and PDF.  
        
        
        **Note: This action is not reversible.**
        
        
        #### Version
        
        To verify the currently installed igv-notebook version (versions >= 0.3.1 only)
        
        ```python
        igv_notebook.version()
        ```
        
        To verify the current version of igv.js (igv-notebook versions >= 0.4.0 only)
        
        ```python
        igv_notebook.igv_version()
        ```
        
        ## Development 
        
        requires python >= 3.9.1
        
        ### Development install
        
        ```bash
        pip install -e .
        ```
        
        ### Build 
        ```bash
        python setup.py build  
        ```
        
        ### Updating igv.js version
        
        1. Edit VERSION_IGV - enter igv.js version with no line feed.  Visit [npmjs.com](https://www.npmjs.com/package/igv) to find latest version
        2. Run ```python updateIGV.py``` 
        
        ## Release Notes
        
        **0.5.1**
        
        * Update igv.js version to 2.15.7
        
        **0.5.0**
        
        * Add support for loading an igv session
        * Generate links to igv-web
        
        **0.4.5**
        
        * Fix path/url problems when using JupyterLab
        
        **0.4.4**
        
        * Add missing requirements to setup.py
        * Update igv.js version to 2.13.10
        
        **0.4.3**
        
        * Fix file-not-found error with version() and igv_version() functions
        
        **0.4.1**
        
        * Update documentation
        
        **0.4.0**
        
        * Add support for regions-of-interest
        * Add ```igv_notebook.igv_version()``` function.
        
        **0.3.1**
        
        * Update ```browser.to_svg()``` function to support Python 3.6.
        * Add ```igv_notebook.version()``` function.
        
        **0.3.0**
        
        * Add ```browser.to_svg()``` function to convert igv instance to static SVG image (Jupyter Notebook only).
        
        
Keywords: igv,bioinformatics,genomics,visualization,ipython,jupyter
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Framework :: IPython
Description-Content-Type: text/markdown
