套件： python3-pybigwig (0.3.17-1build2)
python3-pybigwig 的相關超連結
Trisquel 的資源：
下載原始碼套件 pybigwig：
維護者：
Original Maintainers:
- Debian Med Packaging Team (郵件存檔)
- Diane Trout
外部的資源：
- 主頁 [github.com]
相似套件：
Python 3 module for quick access to bigBed and bigWig files
This is a Python extension, written in C, for quick access to bigBed files, and access to and creation of bigWig files.
The bigWig format was originally created in the context of genome browsers. There, computing exact summary statistics for a given interval is less important than quickly being able to compute an approximate statistic. Because of this, bigWig files contain not only interval-value associations, but also `sum of values`/`sum of squared values`/`minimum value`/`maximum value`/`number of bases covered` for equally sized bins of various sizes. These different sizes are referred to as "zoom levels". The smallest zoom level has bins that are 16 times the mean interval size in the file and each subsequent zoom level has bins 4 times larger than the previous. This methodology is used in Kent's tools and, therefore, likely used in almost every currently existing bigWig file.
When a bigWig file is queried for a summary statistic, the size of the interval is used to determine whether to use a zoom level and, if so, which one. The optimal zoom level is that which has the largest bins no more than half the width of the desired interval. If no such zoom level exists, the original intervals are instead used for the calculation.
其他與 python3-pybigwig 有關的套件
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- dep: libbigwig0 (>= 0.4.4+dfsg)
- C library for handling bigWig files
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- dep: libc6 (>= 2.29)
- GNU C Library: Shared libraries
同時作為一個虛擬套件由這些套件提供： libc6-udeb
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- dep: libpython3.8 (>= 3.8.0~a1)
- Shared Python runtime library (version 3.8)
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- dep: python3
- interactive high-level object-oriented language (default python3 version)
- dep: python3 (<< 3.9)
- dep: python3 (>= 3.8~)
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- dep: python3-numpy (>= 1:1.16.0~rc1)
- Fast array facility to the Python 3 language
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- dep: python3-numpy-abi9
- 本虛擬套件由這些套件提供： python3-numpy