Merge pull request #107 from pepkit/dev

V0.11.2

README.md

@@ -5,6 +5,7 @@
 [![docs-badge](https://readthedocs.org/projects/geofetch/badge/?version=latest)](https://geofetch.databio.org/en/latest/)
 [![pypi-badge](https://img.shields.io/pypi/v/geofetch)](https://pypi.org/project/geofetch)
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/geofetch/README.html)
 
 `geofetch` is a command-line tool that downloads sequencing data and metadata from GEO and SRA and creates [standard PEPs](https://pep.databio.org/). `geofetch` is hosted at [pypi](https://pypi.org/project/geofetch/). You can convert the result of geofetch into unmapped `bam` or `fastq` files with the included `sraconvert` command.
 

docs/README.md

@@ -18,13 +18,16 @@ Key geofetch advantages:
 
 - Works with GEO and SRA metadata
 - Combines samples from different projects
+- ![](./img/meta_integration.svg)
 - Standardizes output metadata
 - Filters type and size of processed files (from GEO) before downloading them
 - Easy to use
 - Fast execution time
 - Can search GEO to find relevant data
 - Can be used either as a command-line tool or from within Python using an API
 
+
+
 ## Quick example
 
 `geofetch` runs on the command line. This command will download the raw data and metadata for the given GSE number.

docs/changelog.md

@@ -1,5 +1,12 @@
 # Changelog
 
+## [0.11.2] -- 2022-12-25
+- Changed sample_name of PEP of processed files to file oriented
+- Added `--max-soft-size` argument, that sets size limit of soft files
+- - Added functionality that skips downloading GEO tables that are in soft files
+- Fixed bug of creating unwanted empty folders
+- Fixed problem with missing data
+
 ## [0.11.1] -- 2022-11-28
 - Fixed requirements file
 - Fixed bug in expanding metadata list