bio-eagle 2.4-1 source package in Ubuntu
Changelog
bio-eagle (2.4-1) unstable; urgency=medium * New upstream release. * Restrict building architecture to x86, upstream supports only x86 arch. * Bump Standards-Version: 4.1.3 (no changes needed). * Bump debhelper compat 11. -- Dylan Aïssi <email address hidden> Fri, 12 Jan 2018 23:33:14 +0100
Upload details
- Uploaded by:
- Debian Med
- Uploaded to:
- Sid
- Original maintainer:
- Debian Med
- Architectures:
- any-amd64 any-i386 all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Bionic | release | universe | misc |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
bio-eagle_2.4-1.dsc | 2.2 KiB | 588afdc026d95dd0c012a477e5e2e7bc53ed734ac7ba80b4f60f9e194270685e |
bio-eagle_2.4.orig.tar.gz | 1.6 MiB | babf3771a7c91d16ad0155624fa66920c389b5cbcf80dd74fb122d3fa40d9ecc |
bio-eagle_2.4-1.debian.tar.xz | 7.1 KiB | 82731a42d855cd7fcaa57a6c499154f235950a955fab573a0e5904bd2da4e146 |
Available diffs
No changes file available.
Binary packages built by this source
- bio-eagle: Haplotype phasing within a genotyped cohort or using a phased reference panel
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.
.
Please note: The executable was renamed to bio-eagle because of a name clash.
Please read more about this in /usr/share/doc/bio- eagle/README. Debian.
- bio-eagle-dbgsym: debug symbols for bio-eagle
- bio-eagle-examples: 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.