Update README and remove old quick start.

README.md

@@ -7,29 +7,31 @@
 [![Documentation Status](https://readthedocs.org/projects/driverpower/badge/?version=latest)](http://driverpower.readthedocs.io/en/latest/?badge=latest)
 
 [Installation](https://driverpower.readthedocs.org/en/latest/install.html) |
-[Quick start](https://driverpower.readthedocs.org/en/latest/quick_start.html) |
+[Tutorial](https://driverpower.readthedocs.org/en/latest/tutorial.html) |
 [Documentation](https://driverpower.readthedocs.org)
 
 DriverPower is a tool used to discover potential coding and non-coding cancer driver elements from tumour whole-genome or whole-exome somatic mutations.
-## Installation
 
-DriverPower requires Python >= 3.5 and some other packages. If you don't have Python 3.5 or higher, we recommend to install Python with [Anaconda](https://www.continuum.io/downloads).
+## How to use DriverPower
+If you only have somatic mutations (in hg19) at hand and
+would like to find drivers in well-annotated regions. Please use our [example data](https://figshare.com/projects/DriverPower_Dataset/36065)
+and follow the [tutorial](https://driverpower.readthedocs.org/en/latest/tutorial.html).
 
-To install DriverPower, you can either download and install it from [Python Package Index (PyPI)](https://pypi.python.org/pypi/DriverPower/) by typing the following command in your terminal
-```bash
-$ pip install driverpower
-```
-or download the [latest source](https://github.com/smshuai/DriverPower/releases/latest/) to install. For example, to install version 1.0.0:
-```console
-$ tar -xzf DriverPower-1.0.1.tar.gz
-$ cd DriverPower-1.0.1/ && pip install .
-```
-See more details at [installation](https://driverpower.readthedocs.org/en/latest/install.html).
+## Citation
+Please cite our paper when you use DriverPower in your study:
+
+- Shuai, S., Gallinger, S., Stein, L. D., PCAWG Drivers and Functional Interpretation Group & ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Net. **DriverPower: Combined burden and functional impact tests for cancer driver discovery**. bioRxiv 215244 (2017).
+[doi:10.1101/215244](https://doi.org/10.1101/215244])
+
+Please cite the PCAWG driver paper as well when you use our example data in your study:
+
+- Rheinbay, E. et al. **Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes**. bioRxiv 237313 (2017). [doi:10.1101/237313](https://doi.org/10.1101/237313)
 
 ## License
 DriverPower is distributed under the terms of the [GNU General Public License 3.0](https://www.gnu.org/licenses/gpl-3.0.txt).
 
 ## Change log
+- 2018/09/12: Release version 1.0.2, which has minor modification.
 - 2017/11/22: Release version 1.0.1, which has bugs fixes and improved performance.
 - 2017/08/03: Release version 1.0.0, which is used in our manuscript.
 - 2017/03/02: Release version 0.4.0, which is used in the PCAWG driver analysis.

docs/source/index.rst

@@ -7,7 +7,6 @@ DriverPower: a tool for computational cancer driver discovery
 
     tutorial
     install
-    quick_start
     command_line
     data_format
 

docs/source/tutorial.rst

@@ -165,7 +165,7 @@ Here we show how to score 1,000 mutations and calculate per-element score:
     # We omit INDELs here; but CADD can score INDELs in VCF format
     zcat ./random_mutations.tsv.gz | \
     awk 'BEGIN{OFS="\t"} $4 != "-" && $5 != "-" {print $1,$3,".",$4,$5}' | \
-    head -100000 | gzip > random_mutations.1K.vcf.gz
+    head -1000 | gzip > random_mutations.1K.vcf.gz
     # Upload formatted variants (random_mutations.1K.vcf.gz) to CADD's web interface
     # and download the result file (something like GRCh37-v1.4_f8600bd0c0aa23d4f6abc99eb8201222.tsv.gz).
     #####