Merge pull request #52 from a-slide/dev

Dev

README.md

@@ -41,7 +41,15 @@ Ideally, before installation, create a clean **Python 3** virtual environment to
 
 ## Dependencies
 
-pycoQC relies on a few robustly maintained third party libraries (numpy, scipy, pandas, plotly, jinja2). The correct versions of the packages are installed together with the software when using pip.
+pycoQC relies on a few robustly maintained third party libraries listed below. The correct versions of the packages are installed together with the software when using pip.
+
+* numpy>=1.13
+* scipy>=1.1
+* pandas>=0.23
+* plotly>=3.4
+* jinja2>=2.10
+* h5py>=2.8.0
+* tqdm>=4.23'
 
 ## Option 1: Direct installation with pip from pipy (recommended)
 
@@ -57,7 +65,7 @@ To update the package:
 
 With this option, the package will be locally installed in “editable” or “develop” mode. This allows the package to be both installed and editable in project form. This is the recommended option if you wish to modify the code and/or participate to the development of the package (see [contribution guidelines](https://github.com/a-slide/pycoQC/blob/master/CONTRIBUTING.md)).
 
-`git clone https://github.com/a-slide/pycoQC.git`
+`git clone https://github.com/a-slide/pycoQC.git` or bleeding edge `git clone --branch dev https://github.com/a-slide/pycoQC.git`
 
 `cd pycoQC`
 
@@ -269,6 +277,18 @@ optional arguments:
                         (default: 0)
 ```
 
+## Alternative and complementary packages
+
+Here is a non-exhaustive list of alternative/complementary packages that could also be used to QC Nanopore sequencing data:
+
+* [Nanoplot](https://github.com/wdecoster/NanoPlot): Generic QC. Part of NanoPack metapackage which offers a broad range of functionalities. *(Python)*
+* [MinION-QC](https://github.com/roblanf/minion_qc): Generic QC with additional interesting plots such as `flowcell_overview`. *(R)*
+* [toullig-QC](https://github.com/GenomicParisCentre/toulligQC): Generic QC. Requires additional input files but gives base resolution information *(Python)*
+* [flowcellvis](https://github.com/mattloose/flowcellvis): Animated GIF of flow cell performance. *(Python)*
+* [Basic QC Tutorial](https://github.com/nanoporetech/ont_tutorial_basicqc): Provided by ONT. Step by step hands-on guide to perform a basic quality control of sequencing data. *(R)*
+
+pycoQC results are consistent with other packages. Reports of the same datasets generated by Nanoplot, MinIONQC and pycoQC are available at the following URL: https://www.ebi.ac.uk/~aleg/data/pycoQC_test/comparison/
+
 ## Contributing
 
 Thanks for considering contributing to our_package!

paper/codemeta.json

@@ -26,5 +26,5 @@
   "keywords": "python3, metrics, plots, nanopore sequencing, interactive, quality control",
   "license": "GPL v3.0",
   "title": "pycoQC, interactive quality control for Oxford Nanopore Sequencing",
-  "version": "v2.2.0"
+  "version": "v2.2.1"
 }

pycoQC/__init__.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 
 # Define self package variable
-__version__ = '2.2.0'
+__version__ = '2.2.1'
 __all__ = ["pycoQC", "common"]
 __description__="""
 PycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data

pycoQC/cli.py

@@ -229,7 +229,7 @@ def generate_report(
             titles.append(plot_title)
 
         except pycoQCError as E:
-            logger.info(E)
+            logger.info("\t\t{}".format(E))
 
     logger.warning("WRITE HTML REPORT")
 

pycoQC/pycoQC.py

@@ -948,7 +948,7 @@ def _check_columns (self, df, required_colnames, optional_colnames):
         return col_found
 
     def _compute_N50 (self, data):
-        data = data.values
+        data = data.values.copy()
         data.sort()
         half_sum = data.sum()/2
         cum_sum = 0