How to Install and Uninstall bio-eagle-examples Package on Kali Linux
Last updated: November 22,2024
1. Install "bio-eagle-examples" package
Please follow the step by step instructions below to install bio-eagle-examples on Kali Linux
$
sudo apt update
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$
sudo apt install
bio-eagle-examples
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2. Uninstall "bio-eagle-examples" package
Here is a brief guide to show you how to uninstall bio-eagle-examples on Kali Linux:
$
sudo apt remove
bio-eagle-examples
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the bio-eagle-examples package on Kali Linux
Package: bio-eagle-examples
Source: bio-eagle
Version: 2.4.1-3
Installed-Size: 1518
Maintainer: Debian Med Packaging Team
Architecture: all
Enhances: bio-eagle
Size: 1525704
SHA256: 1c7eee0c242366251e275dd8043a158f54a46cc261c991e2415a1e4dcb36ad44
SHA1: 3f1d282cfed4a63617f8574b94f8c4091264708d
MD5sum: 8fd94a776fcf06a6d8ce74b72c51d3f0
Description: Examples for bio-eagle
Eagle estimates haplotype phase either within a genotyped cohort or using a
phased reference panel. The basic idea of the Eagle1 algorithm is to harness
identity-by-descent among distant relatives—which is pervasive at very large
sample sizes but rare among smaller numbers of samples—to rapidly call phase
using a fast scoring approach. In contrast, the Eagle2 algorithm analyzes a
full probabilistic model similar to the diploid Li-Stephens model used by
previous HMM-based methods.
.
This package provides some example data for eagle.
Description-md5:
Multi-Arch: foreign
Homepage: https://data.broadinstitute.org/alkesgroup/Eagle/
Section: science
Priority: optional
Filename: pool/main/b/bio-eagle/bio-eagle-examples_2.4.1-3_all.deb
Source: bio-eagle
Version: 2.4.1-3
Installed-Size: 1518
Maintainer: Debian Med Packaging Team
Architecture: all
Enhances: bio-eagle
Size: 1525704
SHA256: 1c7eee0c242366251e275dd8043a158f54a46cc261c991e2415a1e4dcb36ad44
SHA1: 3f1d282cfed4a63617f8574b94f8c4091264708d
MD5sum: 8fd94a776fcf06a6d8ce74b72c51d3f0
Description: Examples for bio-eagle
Eagle estimates haplotype phase either within a genotyped cohort or using a
phased reference panel. The basic idea of the Eagle1 algorithm is to harness
identity-by-descent among distant relatives—which is pervasive at very large
sample sizes but rare among smaller numbers of samples—to rapidly call phase
using a fast scoring approach. In contrast, the Eagle2 algorithm analyzes a
full probabilistic model similar to the diploid Li-Stephens model used by
previous HMM-based methods.
.
This package provides some example data for eagle.
Description-md5:
Multi-Arch: foreign
Homepage: https://data.broadinstitute.org/alkesgroup/Eagle/
Section: science
Priority: optional
Filename: pool/main/b/bio-eagle/bio-eagle-examples_2.4.1-3_all.deb