Reproducible Phylogenomics Dave Lunt, Amir Szitenberg, Max John, Mark Blaxter software: http://hulluni-bioinformatics.github.io/ReproPhylo dave.lunt@gmail.com ReproPhylo reproducible phylogenomics environment evohull.org @davelunt davelunt.net +davelunt

1. Does not scale Whats wrong with phylogenomics now? 0. Rarely reproducible 2. Is not experimental

Many reproducibility challenges are solved problems Solved problems in computer science, and other disciplines, do not always reach biology well, almost

Lack of reproducibility is sociological problem not a new problem unlikely to be solved by outlining best practice a problem for most areas of science and non-science an extensive problem human nature costs and benefits

Reproducibility makes your life much easier ‘future you’ will reproduce your work reproducibility gives you new experimental powers we should highlight to users that benefits to the user- carrot not stick benefit

Frictionless Reproducibility Environments happens in background, user doesn’t have to remember/care to behave reproducibly we should aim for “good science whether you like it or not” c/f computer backups ease

ReproPhylo reproducible phylogenomics environment v1.0 http://hulluni-bioinformatics.github.io/ReproPhylo

ReproPhylo Software: http://hulluni-bioinformatics.github.io/ReproPhylo v1.0 Editable User Manual: http://goo.gl/aZeRXf Open phylogenomics environment Uses standards Frictionless reproducibility Platform independent

ReproPhylo Software: http://hulluni-bioinformatics.github.io/ReproPhylo Editable User Manual: http://goo.gl/aZeRXf IPython notebook Pickle text reports

Sequences, alignments & metadata pickle, git, explicit code, Docker html report, ms figures, tables, Methods, IPython notebook usability reproducibility

.zip files for Dryad and FigShare Docker containers pickled project git figures for manuscript tables for supp info Methods text detailed html report explicit python scripts IPython notebooks usability re-usability reproducibility likely to be used

code output Exploratory Data Analysis

Exploratory Data Analysis check this? high GC exploratory data analysis suggests experimental reuse with variation = reproducibility

ReproPhylo reproducible phylogenomics environment v1.0 Challenge is to make reproducibility the norm Target audience is not bioinformaticians successful human interaction is essential component of reuse and reproducibility usability

ReproPhylo ReproPhylo is environment & approach reproducibility leads to other advantages….. promote experimental, exploratory & hypothesis-testing phylogenomics speed inherently experimental new ways of working? collaborative working

Reproducible Phylogenomics Dave Lunt, Amir Szitenberg, Max John, Mark Blaxter software: http://hulluni-bioinformatics.github.io/ReproPhylo dave.lunt@gmail.com ReproPhylo reproducible phylogenomics environment evohull.org @davelunt davelunt.net +davelunt