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 https://daler.github.io/metaseq.
If you use metaseq in your work, please cite the following publication:
Dale, R. K., Matzat, L. H. & Lei, E. P. metaseq: a Python package for integrative genome-wide analysis reveals relationships between chromatin insulators and associated nuclear mRNA. Nucleic Acids Res. 42, 9158–9170 (2014). http://www.ncbi.nlm.nih.gov/pubmed/25063299
Example 1 walks you through the creation of the following heatmap and line-plot figure:
Example 2 walks you through the creation of the following scatterplot and marginal histogram figure:
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.