Ubuntu
bio-eagle package

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 Pocket Published Component Section
Bionic release universe misc

Builds

Bionic: [FULLYBUILT] amd64 [FULLYBUILT] i386

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

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.