frequentist methods approaches
# + Using evolutionary genomics to identify causal human variants
** Statistics
-+ Statistical modeling (regression, inference, Bayesian and
- frequentist approaches in very large (> 1TB) datasets)
++ Statistical modeling (regression, inference, prediction, and
+ learning in very large (> 1TB) datasets)
+ Addressing confounders and batch effects
# + Reproducible research
** Big Data
+ Parallel and Cloud Computing (slurm, torque, AWS, OpenStack, Azure)
-+ Inter-process communication: MPI, OpenMP, Hadoop
++ Inter-process communication: MPI, OpenMP
+ Filestorage: Gluster, CEFS, GPFS, Lustre
+ Linux system administration
** Mentoring and Leadership
+ Former chair of Debian's Technical Committee
+ Head developer behind https://bugs.debian.org
** Software Development
-+ Languages: perl, R, C, C++, python, groovy, assembly, sh, make
++ Languages: perl, R, C, C++, python, groovy, sh, make
+ Collaborative Development: git, travis, continuous integration,
automated testing
-+ Databases: Postgresql (PL/SQL), SQLite, Mysql
++ Web, Mobile: Shiny, jQuery, JavaScript
++ Databases: Postgresql (PL/SQL), SQLite, Mysql, NoSQL
+ Office Software: Gnumeric, Libreoffice, \LaTeX, Word, Excel,
Powerpoint
** Communication