Skip to main content
This is a pre-production deployment of Warehouse. Changes made here affect the production instance of PyPI (
Help us improve Python packaging - Donate today!

Integrative analysis of high-thoughput sequencing data

Project Description

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

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).

Example 1: Average ChIP-seq signal over promoters

Example 1 walks you through the creation of the following heatmap and line-plot figure:

Top: Heatmap of ATF3 ChIP-seq signal over transcription start sites (TSS) on chr17 in human K562 cells. Middle: average ChIP enrichment over all TSSs +/- 1kb, with 95% CI band. Bottom: Integration with ATF3 knockdown RNA-seq results, showing differential enrichment over transcripts that went up, down, or were unchanged upon ATF3 knockdown.

Example 2: Differential expression scatterplots

Example 2 walks you through the creation of the following scatterplot and marginal histogram figure:

Control vs knockdown expression (log2(FPKM + 1)) for an ATF3 knockdown experiment. Each point represents one transcript on chromosome 17. Marginal distributions are shown on top and side. 1:1 line shown as a dotted line. Up- and downregulated genes determined by a simple 2-fold cutoff.

Other features

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.

Release History

This version
History Node


History Node

History Node

History Node

History Node

History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, Size & Hash SHA256 Hash Help File Type Python Version Upload Date
(1.3 MB) Copy SHA256 Hash SHA256
Source None Nov 15, 2015

Supported By

Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Google Google Cloud Servers DreamHost DreamHost Log Hosting