Peakoscope is a python package for hierarchical analysis of peak and valley regions in numeric data.
- Peak and valley regions can be nested, for example, when a large peak region contains smaller subpeak regions.
- Based on a one-pass algorithm that finds all peak regions and orders them into a tree.
- Classes for peak/valley objects and tree objects.
- Optional interfaces to matplotlib, pandas and polars.
Compute the tree of nested peak regions in a data set:
>>> import peakoscope
>>> data = [10, 30, 40, 30, 10, 50, 70, 70, 50, 80]
>>> print(peakoscope.tree(data))
0:10
├─5:10
│ ├─9:10
│ └─6:8
└─1:4
└─2:3
From the tree, select default peak regions and print their subarrays of data:
>>> for peak in peakoscope.tree(data).size_filter():
... print(peak.subarray(data))
...
[80]
[70, 70]
[30, 40, 30]
The github repo contains tutorials and a glossary:
- Eivind Tøstesen, [email protected]
Copyright (C) 2021-2024 Eivind Tøstesen. This software is licensed under GPLv3
Citation can include one or more of:
-
Peakoscope + version
-
Github URL: https://github.com/eivindtostesen/hierarchical_peak_finding
-
PyPI URL: https://pypi.org/project/peakoscope/
-
The open-access article:
Tøstesen, E. A stitch in time: Efficient computation of genomic DNA melting bubbles. Algorithms for Molecular Biology, 3, 10 (2008). DOI: 10.1186/1748-7188-3-10