From 5dc036afc750eda004e9f43b0be9990e69f01edd Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Tue, 19 Dec 2017 18:36:36 -0500
Subject: [PATCH] update readme
---
docs/Makefile | 3 ++-
docs/_readme.md | 23 +++++++++++------------
docs/intro.rst | 8 ++++----
3 files changed, 17 insertions(+), 17 deletions(-)
diff --git a/docs/Makefile b/docs/Makefile
index 9cc3f347..89582cd0 100644
--- a/docs/Makefile
+++ b/docs/Makefile
@@ -59,8 +59,9 @@ rst:
--out-models-architecture-png _models_architecture.png \
--out-models-info-rst _models_info.rst \
--out-models-supported-alleles-rst _models_supported_alleles.rst
+ tail -n +2 intro.rst > intro.first_two_lines_removed.rst
pandoc -f rst -t markdown_github -B readme_header.md --base-header-level 2 \
- intro.rst \
+ intro.first_two_lines_removed.rst \
commandline_tutorial.rst \
python_tutorial.rst \
_models_supported_alleles.rst \
diff --git a/docs/_readme.md b/docs/_readme.md
index 00d2a726..a86a417b 100644
--- a/docs/_readme.md
+++ b/docs/_readme.md
@@ -7,10 +7,9 @@ Open source peptide/MHC I binding affinity prediction
<!-- DO NOT EDIT README.md, EDIT FILES in docs/ INSTEAD -->
<!-- Then run "make rst" in the docs/ directory to regenerate -->
-Introduction and setup
-----------------------
+------------------------------------------------------------------------
-MHCflurry is a peptide/MHC I binding affinity prediction package written in Python. It aims to provide state of the art accuracy with a documented, fast, and open source implementation.
+MHCflurry is a Python package for peptide/MHC I binding affinity prediction. It provides competitive accuracy with a fast, documented, open source implementation.
MHCflurry users may download trained predictors fit to affinity measurements deposited in IEDB. See the "downloads\_generation/models\_class1" directory in the repository for the workflow used to train these predictors. It is also easy for users with their own data to fit their own models.
@@ -22,7 +21,8 @@ If you find MHCflurry useful in your research please cite:
> O'Donnell, T. et al., 2017. MHCflurry: open-source class I MHC binding affinity prediction. bioRxiv. Available at: <http://www.biorxiv.org/content/early/2017/08/09/174243>.
-### Installation (pip)
+Installation (pip)
+------------------
Install the package:
@@ -37,7 +37,8 @@ From a checkout you can run the unit tests with:
pip install nose
nosetests .
-### Using conda
+Using conda
+-----------
You can alternatively get up and running with a [conda](https://conda.io/docs/) environment as follows. Some users have reported that this can avoid problems installing tensorflow.
@@ -49,10 +50,10 @@ Then continue as above:
pip install mhcflurry
mhcflurry-downloads fetch
-Using MHCflurry from the command-line
--------------------------------------
+### Using MHCflurry from the command-line
-### mhcflurry-predict
+mhcflurry-predict
+-----------------
The `mhcflurry-predict` command generates predictions from the command-line.
@@ -73,13 +74,11 @@ Your exact predictions may vary slightly from these (up to about 1 nM) depending
You can also specify the input and output as CSV files. Run `mhcflurry-predict -h` for details.
-Using MHCflurry as a library
-----------------------------
+### Using MHCflurry as a library
xxx
-Supported peptides and alleles
-------------------------------
+### Supported peptides and alleles
Models released with the current version of MHCflurry (1.0.0) support peptides of length 8-15 and the following 124 alleles:
diff --git a/docs/intro.rst b/docs/intro.rst
index 0ed0cff9..e6268f02 100644
--- a/docs/intro.rst
+++ b/docs/intro.rst
@@ -1,11 +1,11 @@
Introduction and setup
=======================
-MHCflurry is a peptide/MHC I binding affinity prediction package written in
-Python. It aims to provide state of the art accuracy with a documented, fast, and
-open source implementation.
+MHCflurry is a Python package for peptide/MHC I binding affinity prediction. It
+provides competitive accuracy with a fast, documented, open source
+implementation.
-MHCflurry users may download trained predictors fit to affinity measurements
+We provide downloadable MHCflurry predictors fit to affinity measurements
deposited in IEDB. See the "downloads_generation/models_class1" directory in the
repository for the workflow used to train these predictors. It is also easy
for users with their own data to fit their own models.
--
GitLab