Add Eagle2

recipes/eagle2/build.sh

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+#!/bin/bash
+set -euo pipefail
+
+echo "Building Eagle2 version ${PKG_VERSION}"
+
+make \
+    -e -j ${CPU_COUNT} \
+    DYN_LIBS="-lz -lpthread -lbz2 -lopenblas -lm -msse -msse2 -fopenmp -Wall" \
+    CXX="$CXX -std=c++11" \
+    CXXFLAG="$CXXFLAGS" \
+    LDFLAG="$LDFLAGS" \
+    PREFIX="${PREFIX}" \
+    HTSLIB_INC="$PREFIX" \
+    HTSLIB_LIB="-lhts" \
+    BOOST_INC="$PREFIX/include" \
+    BOOST_LIB_IO="-lboost_iostreams" \
+    BOOST_LIB_PO="-lboost_program_options" \
+    BOOST_LIB_SE="-lboost_serialization" || exit 1
+
+echo "Installing Eagle2..."
+mkdir -p "${PREFIX}/bin"
+install -m 755 bin/eagle "${PREFIX}/bin/"
+echo "Eagle2 installation completed successfully"

recipes/eagle2/conda_build_config.yaml

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+# current version does not build with newer compilers
+cxx_compiler_version:
+  - 11  # [osx]
+c_compiler_version:
+  - 11  # [osx]

recipes/eagle2/meta.yaml

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+{% set version = "2.4.1" %}
+
+package:
+  name: eagle2
+  version: {{ version }}
+
+build:
+  number: 0
+  run_exports:
+    - {{ pin_subpackage('eagle2', max_pin='x.x.x') }}
+
+source:
+  url: https://github.com/poruloh/Eagle/archive/refs/tags/v{{ version }}.tar.gz
+  sha256: 85804bfe972186ccb66e602856d6e04044302e5c0dbf9309849b0cde981e3432
+
+requirements:
+  build:
+    - make
+    - {{ compiler('c') }}
+    - {{ compiler('cxx') }}
+  host:
+    - htslib >=1.9
+    - bzip2
+    - zlib
+    - boost-cpp >=1.58
+    - openblas >=0.2.19
+  run:
+    - {{ pin_compatible('htslib') }}
+    - {{ pin_compatible('bzip2') }}
+    - {{ pin_compatible('boost-cpp') }}
+    - {{ pin_compatible('zlib') }}
+    - {{ pin_compatible('openblas') }}
+
+test:
+  commands:
+    - eagle --help
+
+about:
+  home: https://github.com/poruloh/Eagle
+  license: GPLv3
+  summary: The Eagle software estimates haplotype phase either within a genotyped cohort or using a phased reference panel.
+  description:
+    Eagle2 is now the default phasing method used by the Sanger and Michigan imputation servers and uses a new
+    very fast HMM-based algorithm that improves speed and accuracy over existing methods via two key ideas;
+    a new data structure based on the positional Burrows-Wheeler transform and a rapid search algorithm that
+    explores only the most relevant paths through the HMM. Compared to the Eagle1 algorithm, Eagle2 has similar
+    speed but much greater accuracy at sample sizes <50,000; as such, we have made the Eagle2 algorithm the default option.
+    (The Eagle1 algorithm can be accessed via the --v1 flag.) Eagle v2.3+ supports phasing sequence data with or without
+    a reference and also supports phasing chrX.