Briefly, the goal of metaseq is to tie together lots of existing software into a framework for exploring genomic data. It focuses on flexibility and interactive exploration and plotting of disparate genomic data sets.
The main documentation for metaseq can be found at http://packages.python.org/metaseq/.
There are multiple ways of viewing this example, depending on how you are viewing this document:
- Latest release version on PyPI: Example 1
- Reading this on GitHub? See Example 1.
- IPython notebook: View on nbviewer
- Compiled Sphinx docs:
[relative link within this documentation] <example_session>,
There are multiple ways of viewing this example, depending on how you are viewing this document.
- Latest release version on PyPI: Example 2
- Reading this on GitHub? See Example 2.
- IPython notebook: View on nbviewer
- Compiled Sphinx docs:
[relative link within this documentation] <example_session_2>,
In addition, metaseq offers:
- A format-agnostic API for accessing "genomic signal" that allows you to work with BAM, BED, VCF, GTF, GFF, bigBed, and bigWig using the same API.
- Parallel data access from the file formats mentioned above
- "Mini-browsers", zoomable and pannable Python-only figures that show genomic signal and gene models and are spawned by clicking on features of interest
- A wrapper around pandas.DataFrames to simplify the manipulation and plotting of tabular results data that contain gene information (like DESeq results tables)
- Integrates data keyed by genomic interval (think BAM or BED files) with data keyed by gene ID (e.g., Cufflinks or DESeq results tables)
Check out the full documentation for more.