GCC BOSC 2018

→ Tutorial

Key:  BB | XB |  -  |  -  | GG |  -

This workshop will focus on introducing the Galaxy user interface and how it can be used to analyze large datasets. We will cover the basic features of Galaxy, including where to find tools, how to import and use your data, and an introduction to workflows. This session is recommended for anyone who has not used, or only rarely uses Galaxy.
First of 3 sessions in the Introduction to Using Galaxy series.
Prerequisites:

• Little or no experience using Galaxy.
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best.

→ Training Material

Key:  -  |  -  | IP |  -  |  -  | CL

These 3 workshops introduce Galaxy administration, including

• installing and configuring your own server
• customizing your set of reference genomes
• installing tools from the Galaxy Tool Shed
• defining custom tools with Planemo
• users and groups
• storage management and quotas
• and more 

Prerequisites:

• Knowledge and comfort with the Unix/Linux command line interface and a text editor. If you don't know what cd, mv, rm, mkdir, chmod, grep and so on can do then you will struggle in these workshops

Computational infrastructure for this workshop is generously provided by Jetstream, NSF's user-friendly cloud computing environment  for researchers.

→ Training Material

Key:  -  |  -  | IP |  -  |  -  | CL

These 3 workshops introduce Galaxy administration, including

• installing and configuring your own server
• customizing your set of reference genomes
• installing tools from the Galaxy Tool Shed
• defining custom tools with Planemo
• users and groups
• storage management and quotas
• and more 

Prerequisites:

• Knowledge and comfort with the Unix/Linux command line interface and a text editor. If you don't know what cd, mv, rm, mkdir, chmod, grep and so on can do then you will struggle in these workshops

Computational infrastructure for this workshop is generously provided by Jetstream, NSF's user-friendly cloud computing environment  for researchers.

Key:  BB | XB |  -  |  -  | GG |  -

This workshop will introduce the concepts behind transcriptomics with NGS data and how to analyze this data in Galaxy. Specifically, this workshop will focus on de novo transcriptome reconstruction of RNA-seq data with the following goals:

• comprehensive identification of all transcripts across an experiment
• appropriately annotating classes of transcripts
• generating abundance estimates across a transcriptome
• significance testing of differentially expressed transcripts
• visualisation of reads and transcript structures

Second of 3 sessions in the Introduction to Using Galaxy series.
Prerequisites:

• a general knowledge of Galaxy (for example, you should be familiar with the material in Galaxy 101 or have attended Introduction to Galaxy).
• a wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best.

→ Workshop Slides
→ Workshop Tutorial
→ Workshop Server (will go away at some point)

Key:  BB | XB |  -  |  -  | GG |  -

Large-scale ‘omics’ data generation is driven by high throughput genome and transcriptome sequencing, and proteome characterization using mass spectrometry. As a result, many researchers are turning to generating integrative analysis of these ‘multi-omics’ datasets given the great potential to provide novel biological insights. These multi-omics applications are particularly challenging for data analysis, as they require the use of multiple, domain-specific software programs on scalable infrastructure capable of handling the computing and storage needs of this large-scale data.

Galaxy has been shown to solve the problems of software integration and scalability for multi-omics analysis, and additionally offer benefits for sharing complete workflows in a user-friendly environment accessible by wet-bench scientists. In this workshop, we will introduce the use of Galaxy platform for multi-omics data analysis applications. As a representative example, we will focus on the maturing field of proteogenomic applications. Proteogenomics most commonly integrates RNA-Seq data, for generating customized protein sequence databases, with mass spectrometry-based proteomics data, which are matched to these databases to identify novel protein sequence variants. (Cancer Res. (2017); 77(21):e43-e46. doi: 10.1158/0008-5472.CAN-17-0331.)

Workshop Content:
The course will include a basic introduction to proteomics and will include a hands-on session that will cover use of analytical workflows to generate proteomic databases from RNASeq data. The use and understanding of modules for analytical workflows for proteogenomics analysis will be discussed.

Workshop Schedule:

• Introduction to multi-omic studies
• RNASeq Data Processing: Generating protein sequence search databases using Galaxy platform
• Hands-on session for proteomics data analysis using Galaxy
• Identification of novel proteoforms and visualization

Workshop Goals:

• Introduce the Galaxy framework as a solution for data analysis across ‘omics’ domains
• Demonstrate use of Galaxy for a proteogenomic analysis (RNA-seq and proteomic integrative analysis)
• Lay the foundation for attendees to implement Galaxy at their own facility or institution to meet ‘omics’ data analysis and informatics needs

Third of 3 sessions in the Introduction to Using Galaxy series.

Prerequisites:

• a general knowledge of Galaxy (for example, you should be familiar with the material in Galaxy 101 or have attended Introduction to Galaxy).
• a wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best.

Computational infrastructure for this workshop is generously provided by Jetstream, NSF's user-friendly cloud computing environment  for researchers.

→ Training Material

Key:  -  |  -  | IP |  -  |  -  | CL

These 3 workshops introduce Galaxy administration, including

• installing and configuring your own server
• customizing your set of reference genomes
• installing tools from the Galaxy Tool Shed
• defining custom tools with Planemo
• users and groups
• storage management and quotas
• and more 

Prerequisites:

• Knowledge and comfort with the Unix/Linux command line interface and a text editor. If you don't know what cd, mv, rm, mkdir, chmod, grep and so on can do then you will struggle in these workshops

Computational infrastructure for this workshop is generously provided by Jetstream, NSF's user-friendly cloud computing environment  for researchers.

→ Slides

Key:  -  | XB | IP |  -  | GG |  -

Galaxy with its flexibility, reproducibility, and scalability is an ideal environment for teaching and training diverse scientific topics.
The Galaxy Training Network is a community initiative dedicated to high-quality Galaxy-based training around the world. One of its objectives is to support trainers with complete training material and recommendations about bioinformatics training. Templates and best training practices were defined to help trainers create new material, unify the different material, and make training materials more accessible and easy for users to learn and for teachers to teach (https://training.galaxyproject.org).
This workshop will introduce participants to the infrastructure of the GTN training materials and describe how to generate training materials following best practices. Participants will be introduced to the generation of Galaxy Interactive Tours and Docker Galaxy flavors dedicated to teaching and training sessions. The workshop will also cover best practices for running Galaxy-based workshops - how to plan a training session based on number of attendees, time constraints, resource availability, etc.

→ Slides

Key:  -  | XB | IP |  -  |  -  | CL

bcbio is community built analyses for germline and somatic variant calling, RNA-seq, single cell, smallRNA and ChIP-seq. This workshop will focus on using bcbio to run analysis pipelines in heterogenous environments -- local machines, HPC, cloud providers and commercial services (and also hopefully Galaxy). Attendees will learn how to practically run their analyses on their platform of choice, while discussing how the community can contribute to building, sharing and maintaining workflows across multiple platforms. Recent presentations of bcbio show some of the topics we plan to cover.

Prerequisites

→ Tool Dependencies and Conda:          Slides, PDF
→ Tool Dependencies and Containers:  Slides, PDF

Key:  -  |  -  | IP | TD |  -  | CL

This workshop is aimed at people with some desire to develop dependencies for tools (either Galaxy or Common Workflow Language (CWL) tools).
We believe the best practice for declaring dependencies for either Galaxy or the CWL is using Conda and Bioconda. Conda is a cross platform package manager that has minimal requirements to use which makes it ideal for HPC. It can also build isolated environments ideal for platforms like Galaxy or CWL implementations. The Bioconda project is a set of Conda recipes for bioinformatics. The BioContainers project builds best practice containers automatically for all Bioconda recipes, so building a BioConda recipe for a package allows the same binaries to be used by both Galaxy (inside or outside a container) and by any conformant CWL implementation.
We will go through the process of creating, testing, and publishing a Bioconda package and we will work through an example of connecting these packages to a real world tool. Participants will be able to work through the examples using either Galaxy or CWL tools.
Prerequisites

• Some knowledge of tool development - either CWL or Galaxy.
• Knowledge and comfort with the Unix/Linux command line interface and a text editor. If you don't know what cd, mv, rm, mkdir, chmod, grep and so on can do then you will struggle in these workshops

Key:  BB | XB |  -  |  -  | GG | CL

This is the first session of a 3 session series.

The goal of this one-day, three-part tutorial is to teach participants the fundamental data management and analysis skills and needed to conduct genomics research including: best practices for organization of bioinformatics projects and data as well as use of command line utilities for managing large volumes of genomic data. This tutorial is derived from the Data Carpentry Genomics Workshop, focused on the organization and intro to command line lessons. The tutorial uses active learning and hands-on practice to teach participants the skills and perspectives needed to work effectively with genomic data. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.
Lessons:

• http://www.datacarpentry.org/organization-genomics/
• http://www.datacarpentry.org/shell-genomics/

The tutorial assumes no prior experience with the tools covered. However, learners are expected to have some familiarity with biological concepts, including nucleotide abbreviations. Participants should bring their laptops and plan to participate actively.
Prerequisites

→ Tutorial and slides

Key:  BB | XB |  -  |  -  | GG | CL

This tutorial will guide you through loading and analyzing integrated biological data (generally genomic or proteomic) in InterMine via an API in Python or R. Topics covered will include automatically generating code to perform queries, customising the code to meet your needs, and automated analysis of sets, e.g gene sets, including enrichment statistics. Skills gained can be re-used in any of the dozens of InterMines available, covering a broad range of organisms and dedicated purposes, from model organisms to plants, drug targets, and mitochondrial DNA.
Prerequisites

• Basic Python or R skills are advantageous but not required.
• WiFi-enabled laptop with Python or R Studio.

→ Training Materials

Key:  -  | XB | IP | TD |  -  | CL

The advent of open, portable workflow languages is an exciting development which allows for the definition of a workflow to be decoupled from the execution. One can create workflows which can run unmodified on local compute, HPC clusters, or the cloud. As these languages are not tied to a specific execution environment, the descriptions can easily be shared, discovered and even composed together to form more complex workflows. The Workflow Description Language (WDL) is an open, community driven standard that is designed from the ground up as a human-readable and -writable way to express portable tasks and workflows.
In this session we’ll walk through the lifecycle of writing, sharing and discovering portable workflows in WDL. We’ll introduce the WDL syntax. You’ll learn how to write and run a workflow locally. We’ll demonstrate how to use EPAM’s Pipeline Builder toolto visualize WDL workflows. We’ll look at Dockstore, an open platform where one can publish, share and discover workflows. Finally we’ll put everything together and see how we can compose workflows we find on Dockstore together with our own additions to create new, more powerful workflows.
Prerequisites:

• Mac or Linux computer
• Java 8 installed and runnable from the command line
• A workshop bundle downloaded from TBD

Key:  BB | XB |  -  |  -  | GG | CL

This is the second session of a 3 session series.

The goal of this one-day, three-part tutorial is to teach participants the fundamental data management and analysis skills and needed to conduct genomics research including: best practices for organization of bioinformatics projects and data as well as use of command line utilities for managing large volumes of genomic data. This tutorial is derived from the Data Carpentry Genomics Workshop, focused on the organization and intro to command line lessons. The tutorial uses active learning and hands-on practice to teach participants the skills and perspectives needed to work effectively with genomic data. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.
Lessons:

• http://www.datacarpentry.org/organization-genomics/
• http://www.datacarpentry.org/shell-genomics/

The tutorial assumes no prior experience with the tools covered. However, learners are expected to have some familiarity with biological concepts, including nucleotide abbreviations. Participants should bring their laptops and plan to participate actively.
Prerequisites

Key:  -  |  -  | IP |  -  |  -  | CL

In this session you will get in-depth introduction to Interactive Environments (IE). You will learn how to setup and secure IE’s (Jupyter, RStudio, etc.) in a production Galaxy instance. Moreover, we will create an IE on-the-fly to get you started in creating your own Interactive Environments.In this session you will get an introduction to Interactive Environments (IE) as an easy and powerful way to integrate arbitrary interactive web services into Galaxy. We will demonstrate the IPython Galaxy Project and the general concept of IE’s.
Prerequisites:

• Basic understanding of Galaxy from a developer point of view.
• General knowledge about Docker
• Knowledge and comfort with the Unix/Linux command line interface and a text editor. If you don't know what cd, mv, rm, mkdir, chmod, grep and so on can do then you will struggle in this workshop.
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best.

→ Slides

Key:  -  | XB | IP | TD |  -  | CL

Common Workflow Language (http://commonwl.org) is a standard for writing portable scientific workflows that can execute on a variety of compute environments and workflow systems.

• What is CWL, history
• Status of CWL implementations (Arvados, Toil, Rabix, Galaxy, Cromwell, cwtool, ...)
• Wrapping bioinformatics tools in CWL
• Connecting tools together into workflows
• Best practices for writing portable workflows
• Hands on "bring your own pipeline" session
• Q&A on advanced topics based on audience

Prerequisites

• Unix command line experience
• Experience with Docker

→ Slides
→ All Training Material

Key:  -  | XB | IP | TD |  -  | CL

How to use the Galaxy API to automate workflows.
Galaxy has an always-growing API that allows for external programs to upload and download data, manage histories and datasets, run tools and workflows, and even perform admin tasks. This session will cover various approaches to access the API, in particular using the BioBlend Python library.
Prerequisites

• Unix command line
• Basic understanding of Galaxy from a developer point of view.
• Python programming.
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best.

→ Training Materials

Key:  BB | XB |  -  |  -  |  -  |  -

Note: This is the first session of a two-session workshop.

This two-part workshop is geared towards researchers who are thinking about conducting an RNA-seq experiment and are interested in knowing more about what is involved. The planning process requires taking a step back to evaluate various factors and ultimately assess the feasibility of the experiment, including thinking about potential pitfalls and how to avoid them. The workshop will go into detail about the different strategies for working with RNA-seq data depending on the biological question being addressed. Specific topics include:

• Best practice guidelines for experimental design (Biological replicates, Paired-end vs Single-end, Sequencing depth).
• Data storage and computational requirements.
• Overview of commonly used workflows for differential gene expression, de-novo assembly, isoform quantification and other uses of RNA sequencing.

The focus of this workshop is to outline current standards and required resources for the analysis of RNA sequencing data. This workshop will not provide an exhaustive list of software tools or pipelines available; rather it aims to provide a fruitful discussion on how best to prepare for performing RNA-seq data analysis from the lab to manuscript preparation.
Prerequisites:

• None

→ Snakemake Tutorial

Key:  -  | XB | IP | TD |  -  | CL

This session introduces command line and text based workflow management systems by the examples of Snakemake and Nextflow. We will start with an overview of concepts and challenges then spend an hour on each of these platforms.
Snakemake
We will show how to define a workflow in the Snakemake workflow language, and how to execute it using the Snakemake command line interface. In particular, we will show how Snakemake enables reproducible science by allowing

• automation of every step of a data analysis from raw data to final figures
• scalability of the workflow to any major computing architecture (compute server, cluster, grid, cloud) without having to modify the workflow definition
• portability of the workflow by integration with the Conda package manager and Singularity containers.

Nextflow
This session will introduce the Nextflow framework, the tool basic concepts and how it enables the definition and the deployment of large-scale distributed computational pipeline in a portable and reproducible manner across cloud and clusters. In particular it will be discussed:

• installation and introduction to the dataflow processing model
• workflows parallelisation and scalability
• portable workflows containerisation with Docker, Singularity and Shifter
• cloud deployment strategies

Prerequisites

• Linux command line experience

Key:  BB | XB |  -  |  -  | GG | CL

This is the third session of a 3 session series.

The goal of this one-day, three-part tutorial is to teach participants the fundamental data management and analysis skills and needed to conduct genomics research including: best practices for organization of bioinformatics projects and data as well as use of command line utilities for managing large volumes of genomic data. This tutorial is derived from the Data Carpentry Genomics Workshop, focused on the organization and intro to command line lessons. The tutorial uses active learning and hands-on practice to teach participants the skills and perspectives needed to work effectively with genomic data. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.
Lessons:

• http://www.datacarpentry.org/organization-genomics/
• http://www.datacarpentry.org/shell-genomics/

The tutorial assumes no prior experience with the tools covered. However, learners are expected to have some familiarity with biological concepts, including nucleotide abbreviations. Participants should bring their laptops and plan to participate actively.
Prerequisites

→ Prep
→ Tutorial

Key:  BB | XB |  -  |  -  | GG | CL

GATK4 is the brand new version of the Genome Analysis Toolkit (GATK), an open-source genomics software package focused on variant discovery. This workshop will highlight the key changes and updates in the new 4.0 version which was released in January 2018 (see https://software.broadinstitute.org/gatk/gatk4).

The goal of the workshop is to equip participants with the essential know-how to get started with GATK4, whether they have previously used GATK or not. We will walk participants through hands-on exercises aimed at developing familiarity with the GATK4 command line. We will also guide participants through several different ways of running GATK4 tools and pipelines on publicly available platforms including but not limited to Galaxy. We hope this will help participants understand what are their options and choose the platform that best suits their needs and abilities.

The workshop will cover the following topics:

1. Introduction to GATK and the Best Practices:

• Purpose, variant calling basics and standard data types

2. What's new in GATK4:

• New syntax/invocations, performance improvements and tips & tricks for using GATK effectively
• Expanded scope of analysis:
  • Scaling germline variant discovery with GenomicsDB
  • Calling somatic short variants with the new and improved Mutect2
  • Calling somatic copy number variants with GATK CNV

3. Options for running GATK

• Running tools individually on a laptop (with Docker)
• Running Spark-capable tools individually on a Spark cluster (via Google Dataproc)
• Running pipelines on a laptop using Cromwell
• Running pipelines on Google Cloud using Cromwell + Pipelines API
• Running pipelines on the FireCloud analysis portal through the web GUI
• Running pipelines on FireCloud through the API + Python bindings
• Running tools and pipelines on Galaxy

Free credits will be provided for running on Google Cloud. For more information on FireCloud, see https://software.broadinstitute.org/firecloud.

Prerequisites:

• Basic familiarity with terms and concepts of genetics and genomics, including high-level understanding of high-throughput sequencing technologies and file formats used in genomic analysis.
• Basic familiarity with the command line environment and usage of command line tools.
• NO familiarity is expected with Spark or cloud computing concepts.

Key:  BB | XB |  -  |  -  |  -  |  -

Note: This is the second session of a two-session workshop.

This two-part workshop is geared towards researchers who are thinking about conducting an RNA-seq experiment and are interested in knowing more about what is involved. The planning process requires taking a step back to evaluate various factors and ultimately assess the feasibility of the experiment, including thinking about potential pitfalls and how to avoid them. The workshop will go into detail about the different strategies for working with RNA-seq data depending on the biological question being addressed. Specific topics include:

• Best practice guidelines for experimental design (Biological replicates, Paired-end vs Single-end, Sequencing depth).
• Data storage and computational requirements.
• Overview of commonly used workflows for differential gene expression, de-novo assembly, isoform quantification and other uses of RNA sequencing.

The focus of this workshop is to outline current standards and required resources for the analysis of RNA sequencing data. This workshop will not provide an exhaustive list of software tools or pipelines available; rather it aims to provide a fruitful discussion on how best to prepare for performing RNA-seq data analysis from the lab to manuscript preparation.
Prerequisites:

• None