Gseapy

This version still cause memory error, when using ``gsea`` with big array.


All existed APIs will no be deleted any longer.

New feature:
* add ``no_plot`` keyword to all modules to skip plotting
- this is useful only if output data are interested
- also useful when re-run your analysis by skip plotting
* docs are more clear now, particularly ``ssgsea``
- ``ssgsea`` output file improvement.
- see docs and [Examples](http://gseapy.readthedocs.io/en/master/gseapy_example.html)

Note: if you have limited RAM (1 core needs 1G), use v0.8.11.

* Fixed ``stack overflow`` bug in module ``ssgsea`` with v0.9.0.
- drop high dimensional numpy array for computing while using ``ssgsea``, but need more running time.
- ssgsea source code: revert back to old version of 0.8.11, which with multiprocessing support.

Notes about ssGSEA
-----------------------

* ES values from ``ssgsea`` are consistent with GSVA:gsva(method='ssgsea'), see [here](https://www.bioconductor.org/packages/release/bioc/html/GSVA.html).

* download **comparison.zip** and, run these two files to compare ``gseapy.ssgsea`` and GSVA:gsva(method='ssgsea')
- test.ssgesa.gseapy.py
- test.ssgesa.R.r


[comparison.zip](https://github.com/BioNinja/GSEApy/files/1592594/comparison.zip)

Next generation of GSEApy

``ssgsea`` using too much memory. Please use >=0.9.1

* Using high dimension numpy arrays to accelerate computation.
* drop multiprocessing, but reserved the keyword argument for future development.
* docs more clear
* APIs and internal structure of gseapy become more consistent and easier to maintain.
* minor bugs fixed

update some docs

* change matplotlib to export Type 2/TrueType fonts.
* add --no-scale option in command line
* add comments to the output raw.es, nes file
* ES values from ``ssgsea`` now are consistence with GSVA:gsva(method='ssgsea'), see [here](https://www.bioconductor.org/packages/release/bioc/html/GSVA.html)

bug fixed version

* improved the output file in ``ssgsea``:
- samples.raw.es.txt: enrichment score for all samples
- samples.normalized.es.txt: normalized enrichment score (nes) for all samples
- subfolders of each sample: nes, fdr, p-values are calculated by original GSEA method.
- **note**: enrichment plot only shows es

* ssgsea: scaled ES, add ``sample_norm_type`` argument to specify rank method. 36, rank method including:
- rank
- log_rank
- log
how these methods rank genes, see [ssGSEAprojection](http://rowley.mit.edu/caw_web/ssGSEAProjection/ssGSEAProjection.Library.R) , line 86.
* improved gct file input for ssgsea, gsea
- reset_index for pandas series index after sorting values (gct input)
* enrichr: fixed bug in single column input of dataframe
* docs improvement: new links, and more examples, see http://gseapy.rtfd.io/