Recent Releases of cooltools
cooltools - v0.7.0
New features
- Add pool decorator to functions for supporting multiprocess
expected_cisnow accepts unbalanced cool file too
API changes
expected_cis- output cvd table now also includes "distbp", "contactfrequency", and "n_valid" columns
- now returns "count.avg.smoothed" and "count.avg.smoothed.agg", when
clr_weight_name=None, smooth=True, aggregate_smoothed=True
Maintenance
- Replaced np.int with int in adaptive_coarsegrain
- OE update in sandbox
- Cross score sandbox fixes
- Support for pandas 2
- Jupyter Notebook
Published by Yaoyx almost 2 years ago
cooltools - v0.6.0
New features
- New function/tool
rearrange_coolerto reorder/subset/flip regions of the genome in a cooler - New test dataset for micro-C from hESCs
API changes
- snipping: reorder the axes of the output snipper array to (snippet_idx, i, j).
Maintenance
- snipping: fix spurious nan->0 conversion of bad bins in on-diagonal pileups
- snipping: fix snipping without provided view
- snipping: fix for storing the stack in a file
- virtual4c: fix for the case when viewpoint has no contacts
- fix: Fix numba deprecation warnings by adding
nopython=True - Other small bugfixes
- Jupyter Notebook
Published by nvictus over 2 years ago
cooltools - v0.5.2
API changes
- remove custom bad_bins from expected & eigdecomp #336
- coverage can store total cis counts in the cooler, and sampling can use cis counts #332
- can now calculate coverge for balanced data #385
- new droptrackna argument for aligntrackwith_cooler, allows calcultions that that missing data in tracks as absent #360
- multi-thread insulation by chromosome (TODO: by chunk)
- Virtual 4C tool #378
CLI changes
- CLI tool for
coverage()
Documentation
- snipping documentation
- dots tutorial
- CLI tutorial
Maintenance
- Dropped support for Python 3.7 (due to Pandas compatability issues)
Added support for Python 3.10
Minor bugfixes and compatibility updates
- Pandas compatibility, pinned above 1.5.1
- bioframe compatability
- scikit-learn, pinned above >=1.1.2
- saddle binedges, value limits #361
- pileup CLI bugfix for reading features
Other
- Jupyter Notebook
Published by gfudenberg over 3 years ago
cooltools - v0.5.0
NOTE: THIS RELEASE BREAKS BACKWARDS COMPATIBILITY!
This release addresses two major issues: * Integration with bioframe viewframes defined as of bioframe v0.3. * Synchronization of the CLI and Python API
Additionally, the documentation has been greatly improved and now includes detailed tutorials that show how to use the cooltools API in conjunction with other Open2C libraries. These tutorials are automatically re-built from notebooks copied from https://github.com/open2c/open2c_examples repository.
API changes
More clear separation of top-level user-facing functions and low-level API.
- Most standard analyses can be performed using just the user-facing functions which are imported into the top-level namespace. Some of them are new or heavily modified from earlier versions.
cooltools.expected_cisandcooltools.expected_transfor average by-diagonal contact frequency in intra-chromosomal data and in inter-chromosomal data, respectivelycooltools.eigs_cisandcooltools.eigs_transfor eigenvectors (compartment profiles) of cis and trans data, repectivelycooltools.digitizeandcooltools.saddlecan be used together for creation of 2D summary tables of Hi-C interactions in relation to a digitized genomic track, such as eigenvectorscooltools.insulationfor insulation score and annotation of insulating boundariescooltools.directionalityfor directionality indexcooltools.pileupfor average signal at 1D or 2D genomic features, including APAcooltools.coveragefor calculation of per-bin sequencing depthcooltools.samplefor random downsampling of cooler files- For non-standard analyses that require custom algorithms, a lower level API is available under
cooltools.api
Most functions now take an optional
view_dfargument. A pandas dataframe defining a genomic view (https://bioframe.readthedocs.io/en/latest/guide-technical-notes.html) can be provided to limit the analyses to regions included in the view. If not provided, the analysis is performed on whole chromosomes according to what’s stored in the cooler.All functions apart from
coveragenow take aclr_weight_nameargument to specify how the desired balancing weight column is named. Providing aNonevalue allows one to use unbalanced data (except theeigs_cis,eigs_transmethods, since eigendecomposition is only defined for balanced Hi-C data).The output of
expected-cisfunction has changed: it now containsregion1andregion2columns (with identical values in case of within-region expected). Additionally, it now allows smoothing of the result to avoid noisy values at long distances (enabled by default and result saved in additional columns of the dataframe)The new
cooltools.insulationmethod includes a thresholding step to detect strong boundaries, using either the Li or the Otsu method (fromskimage.thresholding), or a fixed float value. The result of thresholding for each window size is stored as a boolean in a new columnis_boundary_{window}.New subpackage
sandboxfor experimental codes that are either candidates for merging into cooltools or candidates for removal. No documentation and tests are expected, proceed at your own risk.New subpackage
libfor auxiliary modules
CLI changes
- CLI tools are renamed with prefixes dropped (e.g.
diamond-insulationis nowinsulation), to align with names of user-facing API functions. - The CLI tool for expected has been split in two for intra- and inter-chromosomal data (
expected-cisandexpected-trans, repectively). - Similarly, the compartment profile calculation is now separate for cis and trans (
eigs-cisandeigs-trans). - New CLI tool
cooltools pileupfor creation of average features based on Hi-C data. It takes a .bed- or .bedpe-style file to create average on-diagonal or off-diagonal pileups, respectively.
Maintenance
Support for Python 3.6 dropped
- Jupyter Notebook
Published by Phlya over 4 years ago
cooltools - v0.5.0rc2
NOTE: THIS RELEASE BREAKS BACKWARDS COMPATIBILITY!
This release addresses two major issues: * Integration with bioframe viewframes defined as of bioframe v0.3. * Synchronization of the CLI and Python API
Additionally, the documentation has been greatly improved and now includes detailed tutorials that show how to use the cooltools API in conjunction with other Open2C libraries. These tutorials are automatically re-built from notebooks copied from https://github.com/open2c/open2c_examples repository.
API changes
More clear separation of top-level user-facing functions and low-level API.
- Most standard analyses can be performed using just the user-facing functions which are imported into the top-level namespace. Some of them are new or heavily modified from earlier versions.
cooltools.expected_cisandcooltools.expected_transfor average by-diagonal contact frequency in intra-chromosomal data and in inter-chromosomal data, respectivelycooltools.eigs_cisandcooltools.eigs_transfor eigenvectors (compartment profiles) of cis and trans data, repectivelycooltools.digitizeandcooltools.saddlecan be used together for creation of 2D summary tables of Hi-C interactions in relation to a digitized genomic track, such as eigenvectorscooltools.insulationfor insulation score and annotation of insulating boundariescooltools.directionalityfor directionality indexcooltools.pileupfor average signal at 1D or 2D genomic features, including APAcooltools.coveragefor calculation of per-bin sequencing depthcooltools.samplefor random downsampling of cooler files- For non-standard analyses that require custom algorithms, a lower level API is available under
cooltools.api
Most functions now take an optional
view_dfargument. A pandas dataframe defining a genomic view (https://bioframe.readthedocs.io/en/latest/guide-technical-notes.html) can be provided to limit the analyses to regions included in the view. If not provided, the analysis is performed on whole chromosomes according to what’s stored in the cooler.All functions apart from
coveragenow take aclr_weight_nameargument to specify how the desired balancing weight column is named. Providing aNonevalue allows one to use unbalanced data (except theeigs_cis,eigs_transmethods, since eigendecomposition is only defined for balanced Hi-C data).The output of
expected-cisfunction has changed: it now containsregion1andregion2columns (with identical values in case of within-region expected). Additionally, it now allows smoothing of the result to avoid noisy values at long distances (enabled by default and result saved in additional columns of the dataframe)The new
cooltools.insulationmethod includes a thresholding step to detect strong boundaries, using either the Li or the Otsu method (fromskimage.thresholding), or a fixed float value. The result of thresholding for each window size is stored as a boolean in a new columnis_boundary_{window}.New subpackage
sandboxfor experimental codes that are either candidates for merging into cooltools or candidates for removal. No documentation and tests are expected, proceed at your own risk.New subpackage
libfor auxiliary modules
CLI changes
- CLI tools are renamed with prefixes dropped (e.g.
diamond-insulationis nowinsulation), to align with names of user-facing API functions. - The CLI tool for expected has been split in two for intra- and inter-chromosomal data (
expected-cisandexpected-trans, repectively). - Similarly, the compartment profile calculation is now separate for cis and trans (
eigs-cisandeigs-trans). - New CLI tool
cooltools pileupfor creation of average features based on Hi-C data. It takes a .bed- or .bedpe-style file to create average on-diagonal or off-diagonal pileups, respectively.
Maintenance
Support for Python 3.6 dropped
- Jupyter Notebook
Published by Phlya over 4 years ago
cooltools - v0.4.0
Maintenance * Make saddle strength work with NaNs * Add output option to diamond-insulation * Upgrade bioframe dependency * Parallelize random sampling * Various compatibility fixes to expected, saddle and snipping and elsewhere to work with standard formats for "expected" and "regions": https://github.com/open2c/cooltools/issues/217
New features
* New dataset download API
* New functionality for smoothing P(s) and derivatives (API is not yet stable): logbin_expected, interpolate_expected
- Jupyter Notebook
Published by nvictus almost 5 years ago
cooltools - v0.4.0rc1
Date: 2021-04-05
Maintenance * Make saddle strength work with NaNs * Add output option to diamond-insulation * Upgrade bioframe dependency * Parallelize random sampling * Various compatibility fixes to expected, saddle and snipping and elsewhere to work with standard formats for "expected" and "regions": https://github.com/open2c/cooltools/issues/217
New features
* New dataset download API
* New functionality for smoothing P(s) and derivatives (API is not yet stable): logbin_expected, interpolate_expected
- Jupyter Notebook
Published by nvictus almost 5 years ago
cooltools - v0.3.2
Updates and bug fixes * Error checking for vmin/vmax in compute-saddle * Various updates and fixes to expected and dot-caller code
Project health * Added docs on RTD, tutorial notebooks, code formatting, linting, and contribution guidelines.
- Jupyter Notebook
Published by nvictus almost 6 years ago
cooltools - v0.3.0
Several library utilities added:
plotting.gridspec_inches,adaptive_coarsegrain, singleton interpolation, and colormaps.New tools:
cooltools samplefor random downsampling,cooltools coveragefor marginalization.compute-saddlenow saves saddledata without transformation, and thescaleargument (with optionslogorlinear) now only determines how the saddle is plotted. Consequently,saddleplotfunction now expects untransformedsaddledata, and plots it directly or with log-scaling of the colormap. (https://github.com/mirnylab/cooltools/pull/105)
- Jupyter Notebook
Published by nvictus over 6 years ago