#+BLOG: smallchangebio
#+POSTID: 97
#+DATE: [2015-07-11 Sat 12:04]
#+BLOG: smallchangebio
#+TITLE: Notes: Bioinformatics Open Source Conference 2015 day 2 afternoon: Translational, Visualization and Lightning Talks
#+CATEGORY: conference
#+TAGS: bioinformatics, open-bio, open-source
#+OPTIONS: toc:nil num:nil

I'm at the [[http://www.open-bio.org/wiki/BOSC_2015][2015 Bioinformatics Open Source Conference (BOSC)]] in Dublin, Ireland.
BOSC is a two day community conference devoted to open source and open science.
These are notes about translational biology, visualization and last minute
lightning talks.

My other notes from the conference:

- [[https://smallchangebio.wordpress.com/2015/07/10/bosc2015day1a/][Holly Bik and Data Science]]
- [[https://smallchangebio.wordpress.com/2015/07/11/bosc2015day1b/][Standards, Interoperability and Diversity Panel]]
- [[https://smallchangebio.wordpress.com/2015/07/11/notes-bioinformatics-open-source-conference-2015-day-2-morning-ewan-birney-open-science-and-reproducibility/][Ewan Birney, Open Science and Reproducibility]]

* Translational Bioinformatics

** CIViC: Crowdsourcing the Clinical Interpretation of Variants in Cancer
/Malachi Griffith/

Large scale cancer genome sequencing is becoming routine. We can get lots of
mutations but bottleneck is in visualization and interpretation of events. Shows
example sample interpretations from
[[http://www.foundationmedicine.com/][Foundation Medicine]] done by paid curators. We should be doing this in public,
and need resources to support this. Resources at WashU: [[http://docm.genome.wustl.edu/][DoCM]] and [[https://civic.genome.wustl.edu/#/home][CIViC]].
Issue is that there are many hospitals and researchers building up lists of
variants we should care about in cancer -- this needs to be done together.
Existing resources aren't meant to be programmable and have non open licenses so
hard to use. Principles of CIViC: interpretations should be freely available and
debated openly. Content needs to be transparent and kept up to date. Need
interface for both API and web interface. Access should remain free. Hope is
that CIViC will end up in a precision medicine treatment cycle: capture
information from trying to help late stage cancer patients who are fine with
experimental treatments. CIViC is trying to capture known clinically actionable
genes, so very specific goals to avoid going in two many directions. Currently
has 500 evidence statements from 230 published sources.

** From Fastq To Drug Recommendation - Automated Cancer Report Generation using OncoRep & Omics Pipe
/Tobias Meissner/

Tobias talks about work on defining actionable targets that can get prescribed
to the patient. Aim for 2 week turnaround for sequencing and analysis. Most time
spent in analysis so benefits from automation and reproducibility improvements.
[[https://bitbucket.org/sulab/omics_pipe][Omics Pipe]] does the process work and [[https://bitbucket.org/sulab/oncorep][OncoRep]] prepares the clinical report.
Introduces example of real patient that has been through multiple rounds of drug
treatments. Omics Pipe implements best practice pipelines that run out of the
box. OncoRep prepares a HTML patient report based on calls generated using
knitr. Links back to evidence. Provides a PDF patient report, generated with sweave.

** Cancer Informatics Collaboration and Computation: Two Initiatives of the U.S. National Cancer Institute
/Ishwar Chandramouliswaran/

Ishwar from the [[http://www.cancer.gov/][National Cancer Institute (NCI)]] presenting the
collaborative [[https://nciphub.org/][NCIP Hub]] intitiatve. Idea is to make tools available for
biologists. The idea is to fit these in with MOOCs for learning and training.
NCIP Hub provides a home for content and keep transparent metrics about usage.
The second initiative is the [[https://cbiit.nci.nih.gov/ncip/nci-cancer-genomics-cloud-pilots][Cancer Cloud Initiative]]
with three implementations: Seven Bridges, Broad and Institute for Systems
Biology. Please partitipate in the evaluation with $2 million in cloud credits.

* Bioinformatics Open Source Project Updates
** Biopython Project Update 2015
/João Rodrigues/

João talking about [[http://biopython.org/wiki/Main_Page][Biopython project]]. Mentions all of the diverse conitributions
to the source code. Also talks about the benefit of
[[https://developers.google.com/open-source/gsoc/][Google Summer of Code (GSoC)]] for
recruiting and retaining contributors. Eric Talevich was a student, then mentor,
then administrator for GSoC -- open source career prorgression. João talks about
improvements in Biopython the last year, demos some cool functionality from
KEGG. Beyond the code: Docker containers with Biopython + dependencies that
supports IPython notebooks. Tiago wrote a book: [[http://shop.oreilly.com/product/9781782175117.do][Bioinformatics with Python Cookbook]].

** The biogems community: Challenges in distributed software development in bioinformatics
/George Githinji and Pjotr Prins/

BioRuby migrated into [[http://biogems.info/][BioGems]]. The idea is to decentralize the contribution
process so there is no longer a central idea, and instead promote and rank the
new packages. Show a lot of metrics of downloads, GitHub issues, mailing list
activity: good question about how to measure success. Published paper on
[[https://github.com/lomereiter/sambamba][sambamba]], saw a big uptick in downloads and GitHub issues: both bug reports and
feature requests.

** Apache Taverna: Sustaining research software at the Apache Software Foundation
/Stian Soiland-Reyes/

[[http://taverna.incubator.apache.org/][Apache Taverna]] is a workflow system that has been in development since 2001.
Since 2006, productionized Taverna to make it easier to install and run. Since
2014 moved to Apache incubating project. Stian describes the typical evolution of
research software: incidentally open source and then developed ad-hoc over time
in different directions than initially expected. There is a strong need for open
development so original starters aren't leaders of the project. Move the focus
towards the people that are doing things; move towards a [[http://www.communitywiki.org/DoOcracy][do-ocracy]]. Looked at
ways to change the legal ownwership of Taverna. Decided to move towards Apache
-- they favor community over code and move towards longer term sustainability.

* Visualization

** Simple, Shareable, Online RNA Secondary Structure Diagrams
/Peter Kerpedjiev/

Peter is talking about making it easy to show RNA secondary structure: tool
called [[https://github.com/pkerpedjiev/forna][forna]] with d3 goodness. Goal of making these is to show things that are
hard to visualize. Simplify 3d structures back to 2d to make them easier to see.
Convert 1d to 2d to make them obvious. Nice examples. Another tool that does
this is [[http://www.lix.polytechnique.fr/Labo/Pauline.Pommeret/RNA/doc/_build/html/index.html][RNA-PDB]]. Can make more complex applications with d3 and [[https://github.com/pkerpedjiev/rnaplot][rnaPlot]] layout.
Container component is [[https://github.com/pkerpedjiev/fornac][fornac]].

** BioJS 2.0: an open source standard for biological visualization
/Guy Yachdav/

[[http://biojs.net/][BioJS]] is a set of reusable blocks for representing biological data on the web.
Have an [[http://biojs.io/][online registry]] to make it easy to discover new packages. Uses npm for
installation. Looking for new components and contributors.

** Visualising Open PHACTS linked data with widgets
/Ian Dunlop/

[[http://www.openphacts.org/][OpenPHACTS]] brings together a large number of pharmaceutical resources into an
integrated infrastructure. Uses RDF under the covers but has an API to query.
Lots of nice [[https://github.com/openphacts/ops-html-widgets][visualization widgets]] and [[https://github.com/openphacts/openphacts-vis-compoundinfo][compound displays]]
included with BioJS.

* Late-Breaking Lightning Talks
** Biospectra-by-sequencing genetic analysis platform
/Aurelie Laugraud/

Originally called Genotyping by Sequencing (GBS) -- cheap and easy way to
sequence only part of a genome. Used first on maize because they have lots of
population data and a massive genome. Analysis pipeline called TASSEL with both
reference and non-reference pipelines. BioSpectra-by-Sequencing (BSS). Brings
together a community to make tools available for existing data.

** hyloToAST: Bioinformatics tools for species-level analysis and visualization of complex microbial communities
/Shareef Dabdoub/

Shareef highlight issues found with QIMME that led them to develope [[https://github.com/smdabdoub/phylotoast][PhyloToAST]]
which modifies and extends the main pipeline. Includes new plots through
matplotlib -- nice 2d + 3d on same data to readily distinguish. Also added
automatic export of data into the [[http://itol.embl.de/][the interactive tree of life (iTOL)]].

** Otter/ZMap/SeqTools: A productive alternative to web browser genome visualisation
/Gemma Guest/

Gemma talks about visualization and annotation tools from the Sanger.
[[https://www.sanger.ac.uk/resources/software/otterlace/][Otter]] does interactive graphical annotation.
[[http://www.sanger.ac.uk/resources/software/zmap/][ZMap]] is a high performace genome browser.
[[http://www.sanger.ac.uk/resources/software/seqtools/][SeqTools and Blixem]] provides a tool for visualizing sequence alignments at a
higher level of detail compared to ZMap. Dotter provides detailed comparisons of
two sequences.

** bioaRchive: enabling reproducibility of Bioconductor package versions
/Nitesh Turaga/

Nitesh is part of the Galaxy team at Johns Hopkins. Issue with Bioconductor is
that it's quite difficult to get an older version of tools -- you can only
really get the latest. [[https://bioarchive.galaxyproject.org][bioarchive]] provides a nice browsable website and packages
of old version of tools. Can use standard install.packages and point to
bioarchive. For Galaxy, this now makes all versions available for full
reproducibility. Future goals are to get bioconductor involved in the process
and integrate with biocLite.

** Developing an Arvados BWA-GATK pipeline
/Pjotr Prins/

Pjotr working at a HiSeq X-10 facility. 18k genomes per year and 50 genomes per
day. Existing pipeline takes 3 days on the cluster. Bottleneck is the shared
filesystem. Decided to try using Arvados based on conversations at BOSC last
year. Took a week to port Perl script over to Arvados. Runs in 2 days with 1 run
and flat performance with 8 samples on AWS. Nice ability to share pipelines in
Arvados.

** Out of the box cloud solution for Next-Generation Sequencing analysis
/Freerk van Dijk/

Put together a VM for NGS analysis using Molgenis. Can download image, upload
data to the VM and then run. Used OpenStack framework for running. Used
[[https://hpcugent.github.io/easybuild/][easyBuild]] to install the software. Define the inputs with a CSV file. Generates
jobs through Molgenis. Nice setup, creates a Reproducible, Scalble and Portable system.
