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CHANGELOG.md

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## 2.0.0
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Major update to accomodate the scverse :cite:`scverse` template.
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Major update to accomodate the scverse template.
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All functions have been rewritten to follow the new API, errors when running previous versions (`1.X.X`) are expected if `decoupler >= 2.0.0` is installed.
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- Use `decoupler.mt.<method_name>` to call a method
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- `min_n` argument has been renamed `tmin`
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- New argument `bsize` allows to run a method with batches in case excessive memory usage is an issue
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- :math:`p_{values}` of the enrichment scores are now corrected by Benjamini-Hochberg
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- `mdt` and `udt` are now based on `xgboost` instead of `sklearn` for better scalability. `udt` statistic is now the coefficient of determination :math:`R^2` instead of the importance of a single decision tree.
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- $p_{values}$ of the enrichment scores are now corrected by Benjamini-Hochberg
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- `mdt` and `udt` are now based on `xgboost` instead of `sklearn` for better scalability. `udt` statistic is now the coefficient of determination $R^2$ instead of the importance of a single decision tree.
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- `ora` now returns the odds ratio of the contingency table as a statistic, and computes a two-sided Fisher exact test instead of a one-sided one
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- `viper` now correctly estimates shadow regulons when network weights are values other than -1 or +1
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- `wsum` and `wmean` are deprecated, instead now the method `waggr` allows to run both methods and any custom function. This makes it easier to quickly test new enrichment methods without having to deal with `decoupler`'s implementation
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- `plot_associations` to `obsm`
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- `plot_targets` to `source_targets`
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- Preprocessing functions are now in the new `pp` module
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- Renamed `check_corr` to `net_corr`, now also returns adjusted :math:`p_{values}`
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- Renamed `check_corr` to `net_corr`, now also returns adjusted $p_{values}$
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- Renamed `get_acts` to `get_obsm`
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- Renamed `get_pseudobulk` to `pseudobulk`. Now it does not automatically remove low quality samples, this is now done with the function `filter_samples`
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- Deprecated `get_contrast`, `get_top_targets` and `format_contrast_results`. `PyDESeq2` should be used instead

docs/api.md

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docs/api/bm.md

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# Benchmark
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## Pipeline
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```{eval-rst}
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.. module:: decoupler.bm
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.. currentmodule:: decoupler
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.. autosummary::
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:toctree: generated
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bm.benchmark
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```
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## Metrics
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```{eval-rst}
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.. module:: decoupler.bm.metric
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.. currentmodule:: decoupler
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.. autosummary::
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:toctree: generated
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bm.metric.auc
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bm.metric.fscore
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bm.metric.qrank
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bm.metric.hmean
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```
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## Plotting
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```{eval-rst}
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.. module:: decoupler.bm.pl
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.. currentmodule:: decoupler
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.. autosummary::
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:toctree: generated
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bm.pl.auc
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bm.pl.fscore
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bm.pl.qrank
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bm.pl.bar
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bm.pl.summary
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```

docs/api/ds.md

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# Datasets
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## Bulk
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```{eval-rst}
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.. module:: decoupler.ds
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.. currentmodule:: decoupler
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.. autosummary::
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:toctree: generated
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ds.hsctgfb
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ds.knocktf
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```
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## Single-cell
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```{eval-rst}
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.. autosummary::
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:toctree: generated
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ds.covid5k
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ds.erygast1k
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ds.pbmc3k
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```
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## Spatial
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```{eval-rst}
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.. autosummary::
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:toctree: generated
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ds.msvisium
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```
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## Toy
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```{eval-rst}
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.. autosummary::
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:toctree: generated
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ds.toy
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ds.toy_bench
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```
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## Utils
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```{eval-rst}
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.. autosummary::
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:toctree: generated
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ds.ensmbl_to_symbol
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```

docs/api/index.md

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# API
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Import decoupler as:
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```
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import decoupler as dc
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```
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```{toctree}
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:maxdepth: 2
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bm
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ds
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mt
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op
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pp
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```
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```{toctree}
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:maxdepth: 1
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pl
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tl
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```

docs/api/mt.md

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# Methods
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## Single methods
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```{eval-rst}
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.. module:: decoupler.mt
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.. currentmodule:: decoupler
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.. autosummary::
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:toctree: generated
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mt.aucell
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mt.gsea
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mt.gsva
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mt.mdt
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mt.mlm
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mt.ora
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mt.udt
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mt.udt
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mt.ulm
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mt.viper
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mt.waggr
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mt.zscore
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```
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## Multiple methods
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```{eval-rst}
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.. autosummary::
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:toctree: generated
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mt.decouple
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mt.consensus
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```

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