<commit_before>****************************************
NIH Library Session - October 14th, 2021
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We offered a half-day online bioinformatics workshop in collaboration with the NIH Library on October 14th, 2021. The abstract below describes the topics we covered:

The ISB Cancer Gateway in the Cloud (ISB-CGC) offers multiple avenues for working with large-scale cancer data sets and provides the ability to process petabytes of data using complex workflows written in the language chosen by the user. New analyses can be developed using SQL, Python, and R to mine gene expression, protein abundance, and somatic mutation data. The instructor will demonstrate common bioinformatic workflows using Python and R while integrating various omic data types such as gene mutations, copy number, gene expression, methylation, and proteomics. Attendees will receive hands-on training on optimizing analyses to combine and interrogate cancer data sets with those available at the Cancer Research Data Commons. 

The workshop included two hours of hands-on data analysis using BigQuery. The following notebooks are snapshots of our teaching materials. These notebooks can be executed in Google Colab or other Jupyter environments. 

.. list-table:: 
   :widths: 100 10 10
   :align: center
   :header-rows: 0

   * - Exploration of BigQuery Datasets
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQueryExploration.ipynb>`_ 
   * - Large-Scale Statistical Analysis in BigQuery
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQueryCorrelations.ipynb>`_ 
   * - Survival Analysis in BigQuery
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQuerySurvival.ipynb>`_ 
   * - Introduction to BigQuery Machine Learning
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQueryMachineLearning.ipynb>`_
<commit_msg>fix table in nih page<commit_after>****************************************
NIH Library Session - October 14th, 2021
****************************************

We offered a half-day online bioinformatics workshop in collaboration with the NIH Library on October 14th, 2021. The abstract below describes the topics we covered:

The ISB Cancer Gateway in the Cloud (ISB-CGC) offers multiple avenues for working with large-scale cancer data sets and provides the ability to process petabytes of data using complex workflows written in the language chosen by the user. New analyses can be developed using SQL, Python, and R to mine gene expression, protein abundance, and somatic mutation data. The instructor will demonstrate common bioinformatic workflows using Python and R while integrating various omic data types such as gene mutations, copy number, gene expression, methylation, and proteomics. Attendees will receive hands-on training on optimizing analyses to combine and interrogate cancer data sets with those available at the Cancer Research Data Commons. 

The workshop included two hours of hands-on data analysis using BigQuery. The following notebooks are snapshots of our teaching materials. These notebooks can be executed in Google Colab or other Jupyter environments. 

.. list-table:: 
   :widths: 100 10
   :align: center
   :header-rows: 0

   * - Exploration of BigQuery Datasets
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQueryExploration.ipynb>`_ 
   * - Large-Scale Statistical Analysis in BigQuery
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQueryCorrelations.ipynb>`_ 
   * - Survival Analysis in BigQuery
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQuerySurvival.ipynb>`_ 
   * - Introduction to BigQuery Machine Learning
     - `R <https://github.com/isb-cgc/Community-Notebooks/blob/master/TeachingMaterials/2021-10-NIHLibrarySession/BigQueryMachineLearning.ipynb>`_

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