Merge pull request #12 from vivekbhr/develop

getting close to a new release with glmPCA

.github/workflows/pypi.yml

@@ -0,0 +1,36 @@
+name: pypi
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+jobs:
+  pypi:
+    name: upload to pypi
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        shell: bash -l {0}
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v2
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v2
+    - name: Create env
+      run: |
+        conda create -n upload -c conda-forge -q --yes python=3.8 twine hatch
+    - name: sdist
+      run: |
+        conda activate upload
+        conda info
+        rm -f dist/*
+        hatch build -t sdist
+    - name: upload
+      if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags')
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        twine upload dist/*

.github/workflows/test.yml

@@ -0,0 +1,55 @@
+name: test
+
+on:
+  push:
+    branches:
+      - develop
+  pull_request:
+    branches:
+      - develop
+      - main
+
+jobs:
+  build:
+    name: Test installation
+    runs-on: ${{ matrix.os }}
+    defaults:
+      run:
+        shell: bash -l {0}
+    strategy:
+      max-parallel: 5
+      matrix:
+        os: [ubuntu-latest, macos-latest]
+        python-version: [ "3.8" ]
+
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v2
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v2
+      with:
+        channels: conda-forge,bioconda,defaults
+        auto-activate-base: false
+        activate-environment: sincei
+        environment-file: requirements.yml
+    - name: Check environment
+      run: |
+        conda info
+    - name: List tools
+      run: |
+        conda list
+    - name: Install sincei
+      run: |
+        pip install .
+        which sincei
+        sincei --help
+    - name: Test with pytest
+      run: |
+        conda install pytest
+        pytest
+
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: psf/black@stable

.gitignore

@@ -3,3 +3,6 @@ bin/__pycache__
 notebooks
 .DS_Store
 .ipynb_checkpoints/
+.pytest_cache
+build
+docs/_build

.readthedocs.yml

@@ -0,0 +1,16 @@
+# yaml file to configure readthedocs build
+version: 2
+build:
+    os: ubuntu-20.04
+    tools:
+        python: "3.8"
+sphinx:
+    configuration: docs/conf.py
+    # disable this for more lenient docs builds
+    fail_on_warning: false
+python:
+    install:
+        - method: pip
+          path: .
+          extra_requirements:
+              - doc

LICENCE.txt

@@ -1,6 +1,6 @@
 MIT license:
 
-Copyright 2021 
+Copyright 2021 Vivek Bhardwaj
 
 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
 

README.md

@@ -1,23 +1,29 @@
 
-<img src="./sincei.png" alt="sincei logo" style="height: 200px; width:400px;"/>
-
-Bhardwaj V. (2022) sincei: A user-friendly toolkit for QC, counting, clustering and plotting of single-cell (epi)genomics data. [![DOI](https://zenodo.org/badge/271841139.svg)](https://zenodo.org/badge/latestdoi/271841139)
+## sincei: A user-friendly toolkit for QC, counting, clustering and plotting of single-cell (epi)genomics data.
 
+[![DOI](https://zenodo.org/badge/271841139.svg)](https://zenodo.org/badge/latestdoi/271841139) [![Documentation Status](https://readthedocs.org/projects/sincei/badge/?version=latest)](https://sincei.readthedocs.io/en/latest/?badge=latest) [![PyPI Version](https://img.shields.io/pypi/v/sincei.svg?style=plastic)](https://pypi.org/project/sincei/) [![test](https://github.com/vivekbhr/sincei/actions/workflows/test.yml/badge.svg)](https://github.com/vivekbhr/sincei/actions/workflows/test.yml) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 
+## [Full Documentation](http://sincei.rtfd.io/).
 
 ## Installation
 
 sincei is a command line toolkit based on python3, and can be installed using [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html).
 
-Create a new conda environment and install sincei using:
+Create a new conda environment and install sincei stable release from github using:
 
 ```
-cd <programs_folder>
-conda create -n sincei -c bioconda -c conda-forge scanpy deeptools
+cd <your_programs_folder>
+conda create -n sincei -c conda-forge -c bioconda scanpy deeptools
 conda activate sincei
 (sincei): pip install --editable=git+https://github.com/vivekbhr/sincei.git@master#egg=sincei
 ```
 
+For the development version, try:
+
+```
+(sincei): pip install --editable=git+https://github.com/vivekbhr/sincei.git@develop#egg=sincei
+```
+
 ## Usage
 
 **Get the tool list with `sincei --help`**
@@ -26,14 +32,4 @@ Each tool begins with the prefix sc<tool_name>, such as:
 
  $ scBulkCoverage -b file1.bam -g groupinfo.txt -o coverage
 
-[ Tools for a typical single-cell analysis workflow ] (WIP: work in progress/not available yet)
-
-    scFilterBarcodes        Identify and filter cell barcodes from BAM file (for droplet-based single-cell seq)
-    scFilterStats           Produce per-cell statistics after filtering reads by user-defined criteria.
-    scCountReads            Counts reads for each barcode on genomic bins or user-defined features.
-    scCountQC               Perform quality control and filter the output of scCountReads.
-    scCombineCounts         [WIP] Concatenate/merge the counts from different samples/batches or modalities
-    scClusterCells          Perform dimensionality reduction and clustering on the output of scCountReads.
-    scFindMarkers           [WIP] Find marker genes per group, given the output of scCountReads and a user-defined group.
-    scBulkCoverage          Get pseudo-bulk coverage per group using a user-supplied cell->group mapping (output of scClusterCells).
-    scFeaturePlot           [WIP] Plot the counts for a given feature on a UMAP or on a (IGV-style) genomic-track.
+