Merge pull request #622 from macs3-project/release/macs3/3.0.1

Release/macs3/3.0.1

.github/workflows/publish-to-anaconda.yml

@@ -62,6 +62,7 @@ jobs:
       run: |
         source /usr/share/miniconda/etc/profile.d/conda.sh
         conda activate MACS3
+        conda install -q pytest
         pytest --runxfail
         cd test
         ./cmdlinetest macs3

ChangeLog

@@ -1,4 +1,4 @@
-2024-02-16  Tao Liu  <[email protected]>
+2024-02-19  Tao Liu  <[email protected]>
 	MACS 3.0.1
 
 	* Bugs fixed
@@ -10,27 +10,38 @@
 	system. (it's needed for building the package). #606 #612
 
 	3) Relax the testing script while comparing the peaks called from
-	current codes and the standard peaks. #615. To implement this, we
-	added 'intersection' function to 'Regions' class to find the
+	current codes and the standard peaks. To implement this, we added
+	'intersection' function to 'Regions' class to find the
 	intersecting regions of two Regions object (similar to PeakIO but
 	only recording chromosome, start and end positions). And we
 	updated the unit test 'test_Region.py' then implemented a script
 	'jaccard.py' to compute the Jaccard Index of two peak files. If
 	the JI > 0.99 we would think the peaks called and the standard
 	peaks are similar. This is to avoid the problem caused by
-	different Numpy libraries, when the certain peak coordinates may
-	have 1bp difference.
+	different Numpy/SciPy/sci-kit learn libraries, when certain peak
+	coordinates may have 10bps difference. #615 #619
+
+	4) Due to the changes in scikit-learn 1.3.0:
+	https://scikit-learn.org/1.3/whats_new/v1.3.html: The way hmmlearn
+	0.3 uses Kmeans will end up with inconsistent results between
+	sklearn <1.3 and sklearn >=1.3. Therefore, we patched the class
+	hmm.GaussianHMM and adjusted the standard output from `hmmratac`
+	subcommand. The change is based on
+	https://github.com/hmmlearn/hmmlearn/pull/545. The idea is to do
+	the random seeding of KMeans 10 times. Now the `hmmratac` results
+	should be more consistent (at least JI>0.99). #615 #620
 
 	* Other
-	
+
 	1) We added some dependencies to MACS3. `hmmratc` subcommand needs
 	`hmmlearn` library, `hmmlearn` needs `scikit-learn` and
 	`scikit-learn` needs `scipy`. Since major releases have happened
 	for both`scipy` and `scikit-learn`, we have to set specific
 	version requirements for them in order to make sure the output
 	results from `hmmratac` are consistent.
 
-	2) We updated our documentation website using Sphinx.
+	2) We updated our documentation website using
+	Sphinx. https://macs3-project.github.io/MACS/
 
 2023-11-15  Tao Liu  <[email protected]>
 	MACS 3.0.0

README.md

@@ -8,6 +8,7 @@ download](https://img.shields.io/pypi/dm/macs3?label=pypi%20downloads)](https://
 Latest Release:
 * Github: [![Github Release](https://img.shields.io/github/v/release/macs3-project/MACS)](https://github.com/macs3-project/MACS/releases)
 * PyPI: [![PyPI Release](https://img.shields.io/pypi/v/macs3.svg) ![PyPI Python Version](https://img.shields.io/pypi/pyversions/MACS3) ![PyPI Format](https://img.shields.io/pypi/format/macs3)](https://pypi.org/project/macs3/)
+* Anaconda:[![Anaconda-Server Badge](https://anaconda.org/macs3/macs3/badges/version.svg)](https://anaconda.org/macs3/macs3)
 
 ## Introduction
 
@@ -27,38 +28,57 @@ applied to any "DNA enrichment assays" if the question to be asked is
 simply: *where we can find significant reads coverage than the random
 background*.
 
-## Changes for MACS (3.0.1)
+## Changes for MACS (3.0.1) 
 
 *Bugs fixed*
 
-1) Fixed a bug that the `hmmatac` can't correctly save the
-	digested signal files. #605 #611
+1) Fixed a bug that the `hmmatac` can't correctly save the digested
+	signal
+	files. [#605](https://github.com/macs3-project/MACS/issues/605)
+	[#611](https://github.com/macs3-project/MACS/pull/611)
 
 2) Applied a patch to remove cython requirement from the installed
-	system. (it's needed for building the package). #606 #612
+	system. (it's needed for building the
+	package). [#606](https://github.com/macs3-project/MACS/issues/606)
+	[#612](https://github.com/macs3-project/MACS/pull/612)
 
 3) Relax the testing script while comparing the peaks called from
-	current codes and the standard peaks. #615. To implement this, we
-	added 'intersection' function to 'Regions' class to find the
+	current codes and the standard peaks. To implement this, we added
+	'intersection' function to 'Regions' class to find the
 	intersecting regions of two Regions object (similar to PeakIO but
 	only recording chromosome, start and end positions). And we
 	updated the unit test 'test_Region.py' then implemented a script
 	'jaccard.py' to compute the Jaccard Index of two peak files. If
 	the JI > 0.99 we would think the peaks called and the standard
 	peaks are similar. This is to avoid the problem caused by
-	different Numpy libraries, when the certain peak coordinates may
-	have 1bp difference.
+	different Numpy/SciPy/sci-kit learn libraries, when certain peak
+	coordinates may have 10bps
+	difference. [#615](https://github.com/macs3-project/MACS/issues/615)
+	[#619](https://github.com/macs3-project/MACS/pull/619)
+
+4) Due to [the changes in scikit-learn
+	1.3.0](https://scikit-learn.org/1.3/whats_new/v1.3.html), the way
+	hmmlearn 0.3 uses Kmeans will end up with inconsistent results
+	between sklearn <1.3 and sklearn >=1.3. Therefore, we patched the
+	class hmm.GaussianHMM and adjusted the standard output from
+	`hmmratac` subcommand. The change is based on [hmmlearn
+	PR#545](https://github.com/hmmlearn/hmmlearn/pull/545). The idea
+	is to do the random seeding of KMeans 10 times. Now the `hmmratac`
+	results should be more consistent (at least
+	JI>0.99). [#615](https://github.com/macs3-project/MACS/issues/615)
+	[#620](https://github.com/macs3-project/MACS/pull/620)
 
 *Other*
 
-1) We added some dependencies to MACS3. `hmmratc` subcommand needs
-	`hmmlearn` library, `hmmlearn` needs `scikit-learn` and
-	`scikit-learn` needs `scipy`. Since major releases have happened
-	for both`scipy` and `scikit-learn`, we have to set specific
-	version requirements for them in order to make sure the output
-	results from `hmmratac` are consistent.
-
-2) We updated our documentation website using Sphinx.
+1) We added some dependencies to MACS3. `hmmratc` subcommand needs 
+	`hmmlearn` library, `hmmlearn` needs `scikit-learn` and 
+	`scikit-learn` needs `scipy`. Since major releases have happened 
+	for both`scipy` and `scikit-learn`, we have to set specific 
+	version requirements for them in order to make sure the output 
+	results from `hmmratac` are consistent. 
+
+2) We updated our documentation website using 
+    Sphinx. https://macs3-project.github.io/MACS/
 
 ## Changes for MACS (3.0.0)
 

conda/macs3/meta.yaml

@@ -16,30 +16,31 @@ build:
 requirements:
   build:
     - {{ compiler('c') }}
+    - zlib
     - python >=3.11
     - numpy >=1.25
-    - scipy>=1.10
+    - scipy >=1.12
     - Cython ~=3.0
-    - cykhash >=2.0
+    - cykhash >=2.0,<3.0
     - setuptools >=68.0
     - hmmlearn >=0.3
     - scikit-learn >=1.3
   host:
     - python >=3.11
+    - zlib
     - numpy >=1.25
-    - scipy>=1.10
-    - Cython ~=3.0    
-    - cykhash >=2.0
+    - scipy >=1.12
+    - Cython ~=3.0
+    - hmmlearn >=0.3
+    - scikit-learn >=1.3
+    - cykhash >=2.0,<3.0
   run:
     - python >=3.11
     - numpy >=1.25
-    - scipy>=1.10
+    - scipy >=1.12
     - hmmlearn >=0.3
-
-test:
-  commands:
-    - macs3 -h
-    - pytest
+    - scikit-learn >=1.3
+    - cykhash >=2.0,<3.0
 
 about:
   home: http://github.com/macs3-project/MACS/

docs/source/index.md

@@ -8,6 +8,7 @@ download](https://img.shields.io/pypi/dm/macs3?label=pypi%20downloads)](https://
 Latest Release:
 * Github: [![Github Release](https://img.shields.io/github/v/release/macs3-project/MACS)](https://github.com/macs3-project/MACS/releases)
 * PyPI: [![PyPI Release](https://img.shields.io/pypi/v/macs3.svg) ![PyPI Python Version](https://img.shields.io/pypi/pyversions/MACS3) ![PyPI Format](https://img.shields.io/pypi/format/macs3)](https://pypi.org/project/macs3/)
+* Anaconda:[![Anaconda-Server Badge](https://anaconda.org/macs3/macs3/badges/version.svg)](https://anaconda.org/macs3/macs3)
 
 ## Introduction
 
@@ -27,38 +28,57 @@ applied to any "DNA enrichment assays" if the question to be asked is
 simply: *where we can find significant reads coverage than the random
 background*.
 
-## Changes for MACS (3.0.1)
+## Changes for MACS (3.0.1) 
 
 *Bugs fixed*
 
-1) Fixed a bug that the `hmmatac` can't correctly save the
-	digested signal files. #605 #611
+1) Fixed a bug that the `hmmatac` can't correctly save the digested
+	signal
+	files. [#605](https://github.com/macs3-project/MACS/issues/605)
+	[#611](https://github.com/macs3-project/MACS/pull/611)
 
 2) Applied a patch to remove cython requirement from the installed
-	system. (it's needed for building the package). #606 #612
+	system. (it's needed for building the
+	package). [#606](https://github.com/macs3-project/MACS/issues/606)
+	[#612](https://github.com/macs3-project/MACS/pull/612)
 
 3) Relax the testing script while comparing the peaks called from
-	current codes and the standard peaks. #615. To implement this, we
-	added 'intersection' function to 'Regions' class to find the
+	current codes and the standard peaks. To implement this, we added
+	'intersection' function to 'Regions' class to find the
 	intersecting regions of two Regions object (similar to PeakIO but
 	only recording chromosome, start and end positions). And we
 	updated the unit test 'test_Region.py' then implemented a script
 	'jaccard.py' to compute the Jaccard Index of two peak files. If
 	the JI > 0.99 we would think the peaks called and the standard
 	peaks are similar. This is to avoid the problem caused by
-	different Numpy libraries, when the certain peak coordinates may
-	have 1bp difference.
+	different Numpy/SciPy/sci-kit learn libraries, when certain peak
+	coordinates may have 10bps
+	difference. [#615](https://github.com/macs3-project/MACS/issues/615)
+	[#619](https://github.com/macs3-project/MACS/pull/619)
+
+4) Due to [the changes in scikit-learn
+	1.3.0](https://scikit-learn.org/1.3/whats_new/v1.3.html), the way
+	hmmlearn 0.3 uses Kmeans will end up with inconsistent results
+	between sklearn <1.3 and sklearn >=1.3. Therefore, we patched the
+	class hmm.GaussianHMM and adjusted the standard output from
+	`hmmratac` subcommand. The change is based on [hmmlearn
+	PR#545](https://github.com/hmmlearn/hmmlearn/pull/545). The idea
+	is to do the random seeding of KMeans 10 times. Now the `hmmratac`
+	results should be more consistent (at least
+	JI>0.99). [#615](https://github.com/macs3-project/MACS/issues/615)
+	[#620](https://github.com/macs3-project/MACS/pull/620)
 
 *Other*
 
-1) We added some dependencies to MACS3. `hmmratc` subcommand needs
-	`hmmlearn` library, `hmmlearn` needs `scikit-learn` and
-	`scikit-learn` needs `scipy`. Since major releases have happened
-	for both`scipy` and `scikit-learn`, we have to set specific
-	version requirements for them in order to make sure the output
-	results from `hmmratac` are consistent.
-
-2) We updated our documentation website using Sphinx.
+1) We added some dependencies to MACS3. `hmmratc` subcommand needs 
+	`hmmlearn` library, `hmmlearn` needs `scikit-learn` and 
+	`scikit-learn` needs `scipy`. Since major releases have happened 
+	for both`scipy` and `scikit-learn`, we have to set specific 
+	version requirements for them in order to make sure the output 
+	results from `hmmratac` are consistent. 
+
+2) We updated our documentation website using 
+    Sphinx. https://macs3-project.github.io/MACS/
 
 ## Changes for MACS (3.0.0)