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cna bug and docs update
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README.md

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@@ -53,15 +53,16 @@ A local installation of Python (it has been tested with [version 2.7.13](https:/
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#### STEP 2: Download PCGR
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<font color="red"><b>April 12th 2017</b>: New release (v0.3)</font>
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1. Download and unpack the [latest release (v0.3)](https://github.com/sigven/pcgr/releases/latest)
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<font color="red"><b>April 12th 2017</b>: New release (0.3.1)</font>
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1. Download and unpack the [latest release (0.3.1)](https://github.com/sigven/pcgr/releases/latest)
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2. Download and unpack the data bundle (approx. 17Gb) in the PCGR directory
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* Download [the latest data bundle](https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/) from Google Drive to `~/pcgr-X.X` (replace _X.X_ with the version number, e.g `~/pcgr-0.3`)
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* Download [the latest data bundle](https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/) from Google Drive to `~/pcgr-X.X` (replace _X.X_ with the version number, e.g `~/pcgr-0.3.1`)
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* Unpack the data bundle, e.g. through the following Unix command: `gzip -dc pcgr.databundle.GRCh37.YYYYMMDD.tgz | tar xvf -`
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A _data/_ folder within the _pcgr-X.X_ software folder should now have been produced
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3. Pull the [PCGR Docker image (v0.3)](https://hub.docker.com/r/sigven/pcgr/) from DockerHub (3.1Gb):
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* `docker pull sigven/pcgr:0.3` (PCGR annotation engine)
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3. Pull the [PCGR Docker image (0.3.1)](https://hub.docker.com/r/sigven/pcgr/) from DockerHub (3.1Gb):
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* `docker pull sigven/pcgr:0.3.1` (PCGR annotation engine)
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#### STEP 3: Input preprocessing
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positional arguments:
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pcgr_dir PCGR base directory with accompanying data directory,
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e.g. ~/pcgr-0.3
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e.g. ~/pcgr-0.3.1
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output_dir Output directory
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sample_id Tumor sample/cancer genome identifier - prefix for
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output files
@@ -145,7 +146,7 @@ A tumor sample report is generated by calling the Python script __pcgr.py__ in t
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The _examples_ folder contain sample files from TCGA. A report for a colorectal tumor case can be generated through the following command:
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`python pcgr.py --input_vcf tumor_sample.COAD.vcf.gz --input_cna_segments tumor_sample.COAD.cna.tsv ~/pcgr-0.3 ~/pcgr-0.3/examples tumor_sample.COAD`
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`python pcgr.py --input_vcf tumor_sample.COAD.vcf.gz --input_cna_segments tumor_sample.COAD.cna.tsv ~/pcgr-0.3.1 ~/pcgr-0.3.1/examples tumor_sample.COAD`
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This command will run the Docker-based PCGR workflow and produce the following output files in the _examples_ folder:
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docs/_build/html/_sources/getting_started.rst.txt

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Download PCGR
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^^^^^^^^^^^^^
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**April 12th 2017**: New release (v0.3)
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**April 14th 2017**: New release (0.3.1)
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- Download and unpack the `latest release
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(v0.3) <https://github.com/sigven/pcgr/releases/latest>`__
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(0.3.1) <https://github.com/sigven/pcgr/releases/latest>`__
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- Download and unpack the data bundle (approx. 17Gb) in the PCGR
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directory
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- Download `the latest data
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bundle <https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/>`__
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from Google Drive to ``~/pcgr-X.X`` (replace *X.X* with the
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version number, e.g. ``~/pcgr-0.3``)
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version number, e.g. ``~/pcgr-0.3.1``)
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- Decompress and untar the bundle, e.g. through the following Unix
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command:
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``gzip -dc pcgr.databundle.GRCh37.YYYYMMDD.tgz | tar xvf -``
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have been produced
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- Pull the `PCGR Docker image -
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v0.3 <https://hub.docker.com/r/sigven/pcgr/>`__ from DockerHub
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0.3.1 <https://hub.docker.com/r/sigven/pcgr/>`__ from DockerHub
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(3.1Gb) :
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- ``docker pull sigven/pcgr:0.3`` (PCGR annotation engine)
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- ``docker pull sigven/pcgr:0.3.1`` (PCGR annotation engine)
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Run test - generation of clinical report for a cancer genome
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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generated by running the following command in your terminal window:
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``python pcgr.py --input_vcf examples/tumor_sample.COAD.vcf.gz --input_cna_segments``
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``examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3 ~/pcgr-0.3/examples tumor_sample.COAD``
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``examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3.1 ~/pcgr-0.3.1/examples tumor_sample.COAD``
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This command will run the Docker-based PCGR workflow and produce the
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following output files in the *examples* folder:

docs/_build/html/getting_started.html

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@@ -189,18 +189,18 @@ <h3>Python<a class="headerlink" href="#python" title="Permalink to this headline
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</div>
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<div class="section" id="download-pcgr">
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<h3>Download PCGR<a class="headerlink" href="#download-pcgr" title="Permalink to this headline"></a></h3>
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<p><strong>April 12th 2017</strong>: New release (v0.3)</p>
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<p><strong>April 14th 2017</strong>: New release (0.3.1)</p>
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<ul>
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<li><p class="first">Download and unpack the <a class="reference external" href="https://github.com/sigven/pcgr/releases/latest">latest release
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(v0.3)</a></p>
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(0.3.1)</a></p>
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</li>
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<li><p class="first">Download and unpack the data bundle (approx. 17Gb) in the PCGR
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directory</p>
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<ul class="simple">
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<li>Download <a class="reference external" href="https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/">the latest data
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bundle</a>
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from Google Drive to <code class="docutils literal"><span class="pre">~/pcgr-X.X</span></code> (replace <em>X.X</em> with the
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version number, e.g. <code class="docutils literal"><span class="pre">~/pcgr-0.3</span></code>)</li>
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version number, e.g. <code class="docutils literal"><span class="pre">~/pcgr-0.3.1</span></code>)</li>
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<li>Decompress and untar the bundle, e.g. through the following Unix
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command:
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<code class="docutils literal"><span class="pre">gzip</span> <span class="pre">-dc</span> <span class="pre">pcgr.databundle.GRCh37.YYYYMMDD.tgz</span> <span class="pre">|</span> <span class="pre">tar</span> <span class="pre">xvf</span> <span class="pre">-</span></code></li>
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have been produced</p>
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</li>
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<li><p class="first">Pull the <a class="reference external" href="https://hub.docker.com/r/sigven/pcgr/">PCGR Docker image -
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v0.3</a> from DockerHub
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0.3.1</a> from DockerHub
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(3.1Gb) :</p>
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<ul class="simple">
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<li><code class="docutils literal"><span class="pre">docker</span> <span class="pre">pull</span> <span class="pre">sigven/pcgr:0.3</span></code> (PCGR annotation engine)</li>
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<li><code class="docutils literal"><span class="pre">docker</span> <span class="pre">pull</span> <span class="pre">sigven/pcgr:0.3.1</span></code> (PCGR annotation engine)</li>
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</ul>
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</li>
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sequenced within TCGA. A report for a colorectal tumor case can be
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generated by running the following command in your terminal window:</p>
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<p><code class="docutils literal"><span class="pre">python</span> <span class="pre">pcgr.py</span> <span class="pre">--input_vcf</span> <span class="pre">examples/tumor_sample.COAD.vcf.gz</span> <span class="pre">--input_cna_segments</span></code>
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<code class="docutils literal"><span class="pre">examples/tumor_sample.COAD.cna.tsv</span> <span class="pre">~/pcgr-0.3</span> <span class="pre">~/pcgr-0.3/examples</span> <span class="pre">tumor_sample.COAD</span></code></p>
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<code class="docutils literal"><span class="pre">examples/tumor_sample.COAD.cna.tsv</span> <span class="pre">~/pcgr-0.3.1</span> <span class="pre">~/pcgr-0.3.1/examples</span> <span class="pre">tumor_sample.COAD</span></code></p>
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<p>This command will run the Docker-based PCGR workflow and produce the
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following output files in the <em>examples</em> folder:</p>
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<ol class="arabic simple">

docs/_build/html/searchindex.js

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Some generated files are not rendered by default. Learn more about customizing how changed files appear on GitHub.

docs/getting_started.md

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#### Download PCGR
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__April 12th 2017__: New release (v0.3)</font>
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__April 14th 2017__: New release (0.3.1)</font>
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* Download and unpack the [latest release (v0.3)](https://github.com/sigven/pcgr/releases/latest)
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* Download and unpack the [latest release (0.3.1)](https://github.com/sigven/pcgr/releases/latest)
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* Download and unpack the data bundle (approx. 17Gb) in the PCGR directory
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* Download [the latest data bundle](https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/) from Google Drive to `~/pcgr-X.X` (replace _X.X_ with the version number, e.g. `~/pcgr-0.3`)
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* Download [the latest data bundle](https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/) from Google Drive to `~/pcgr-X.X` (replace _X.X_ with the version number, e.g. `~/pcgr-0.3.1`)
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* Decompress and untar the bundle, e.g. through the following Unix command: `gzip -dc pcgr.databundle.GRCh37.YYYYMMDD.tgz | tar xvf -`
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A _data/_ folder within the _pcgr-X.X_ software folder should now have been produced
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* Pull the [PCGR Docker image - v0.3](https://hub.docker.com/r/sigven/pcgr/) from DockerHub (3.1Gb) :
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* `docker pull sigven/pcgr:0.3` (PCGR annotation engine)
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* Pull the [PCGR Docker image - 0.3.1](https://hub.docker.com/r/sigven/pcgr/) from DockerHub (3.1Gb) :
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* `docker pull sigven/pcgr:0.3.1` (PCGR annotation engine)
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### Run test - generation of clinical report for a cancer genome
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The _examples_ folder contain input files from two tumor samples sequenced within TCGA. A report for a colorectal tumor case can be generated by running the following command in your terminal window:
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`python pcgr.py --input_vcf examples/tumor_sample.COAD.vcf.gz --input_cna_segments `
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`examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3 ~/pcgr-0.3/examples tumor_sample.COAD`
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`examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3.1 ~/pcgr-0.3.1/examples tumor_sample.COAD`
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This command will run the Docker-based PCGR workflow and produce the following output files in the _examples_ folder:
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docs/getting_started.rst

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Download PCGR
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^^^^^^^^^^^^^
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**April 12th 2017**: New release (v0.3)
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**April 14th 2017**: New release (0.3.1)
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- Download and unpack the `latest release
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(v0.3) <https://github.com/sigven/pcgr/releases/latest>`__
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(0.3.1) <https://github.com/sigven/pcgr/releases/latest>`__
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- Download and unpack the data bundle (approx. 17Gb) in the PCGR
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directory
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- Download `the latest data
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bundle <https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/>`__
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from Google Drive to ``~/pcgr-X.X`` (replace *X.X* with the
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version number, e.g. ``~/pcgr-0.3``)
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version number, e.g. ``~/pcgr-0.3.1``)
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- Decompress and untar the bundle, e.g. through the following Unix
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command:
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``gzip -dc pcgr.databundle.GRCh37.YYYYMMDD.tgz | tar xvf -``
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have been produced
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- Pull the `PCGR Docker image -
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v0.3 <https://hub.docker.com/r/sigven/pcgr/>`__ from DockerHub
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0.3.1 <https://hub.docker.com/r/sigven/pcgr/>`__ from DockerHub
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(3.1Gb) :
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- ``docker pull sigven/pcgr:0.3`` (PCGR annotation engine)
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- ``docker pull sigven/pcgr:0.3.1`` (PCGR annotation engine)
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Run test - generation of clinical report for a cancer genome
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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generated by running the following command in your terminal window:
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``python pcgr.py --input_vcf examples/tumor_sample.COAD.vcf.gz --input_cna_segments``
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``examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3 ~/pcgr-0.3/examples tumor_sample.COAD``
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``examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3.1 ~/pcgr-0.3.1/examples tumor_sample.COAD``
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This command will run the Docker-based PCGR workflow and produce the
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following output files in the *examples* folder:

pcgr.py

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parser.add_argument('--num_vcfanno_processes', dest = "num_vcfanno_processes", default=4, type=int, help='Number of processes used during vcfanno annotation')
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parser.add_argument('--num_vep_forks', dest = "num_vep_forks", default=4, type=int, help='Number of forks (--forks option in VEP) used during VEP annotation')
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parser.add_argument('--force_overwrite', action = "store_true", help='By default, the script will fail with an error if any output file already exists. You can force the overwrite of existing result files by using this flag')
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parser.add_argument('--version', action='version', version='%(prog)s 0.3')
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parser.add_argument('pcgr_dir',help='PCGR base directory with accompanying data directory, e.g. ~/pcgr-0.3')
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parser.add_argument('--version', action='version', version='%(prog)s 0.3.1')
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parser.add_argument('pcgr_dir',help='PCGR base directory with accompanying data directory, e.g. ~/pcgr-0.3.1')
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parser.add_argument('output_dir',help='Output directory')
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parser.add_argument('sample_id',help="Tumor sample/cancer genome identifier - prefix for output files")
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docker_image_version = 'sigven/pcgr:0.3'
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docker_image_version = 'sigven/pcgr:0.3.1'
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args = parser.parse_args()
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overwrite = 0

src/Dockerfile

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ENV PACKAGE_DEV="perl debconf-utils build-essential gfortran python-dev python-pip gcc-multilib autoconf zlib1g-dev git libncurses5-dev libblas-dev liblapack-dev cpanminus libcurl4-gnutls-dev libssh2-1-dev libxml2-dev vim libssl-dev openssl libcairo2-dev"
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ENV PYTHON_MODULES="numpy cython scipy transvar bx-python pyvcf cyvcf cyvcf2 biopython crossmap pandas"
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ENV R_BASE_VERSION 3.3.2
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ENV R_BASE_VERSION 3.3.3
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USER root
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WORKDIR /

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