From 50846f9691cf17f2dd89261cca54cf590bac67ed Mon Sep 17 00:00:00 2001 From: Don Armstrong Date: Wed, 21 Mar 2018 15:09:01 -0700 Subject: [PATCH] comment out statistics and genomics --- don_armstrong_resume.org | 34 +++++++++++++++++----------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/don_armstrong_resume.org b/don_armstrong_resume.org index 18ac5ab..c5f59fc 100644 --- a/don_armstrong_resume.org +++ b/don_armstrong_resume.org @@ -87,23 +87,23 @@ + GNU/Linux (Debian, Ubuntu, Red Hat) + Windows (5.0-10) + MacOS (10-10.13) -** Statistics - + Statistical modeling in very large datasets - + Addressing confounders and batch effects -** Genomics and Epigenomics -+ NGS and array-based Genomics and Epigenomics of complex human - diseases using RNA-seq, targeted DNA sequencing, RRBS, Illumina - bead arrays, and Affymetrix microarrays from sample collection to - publication. -+ Reproducible, scalable bioinformatics analysis using make, - nextflow, and cwl based workflows on cloud- and cluster-based - systems on terabyte-scale datasets -+ Alignment, annotation, and variant calling using existing and custom - software, including GATK, bwa, STAR, and kallisto. -+ Correcting for and experimental design to overcome multiple - testing, confounders, and batch effects using Bayesian and - frequentist methods approaches -+ Using evolutionary genomics to identify causal human variants +# ** Statistics +# + Statistical modeling in very large datasets +# + Addressing confounders and batch effects +# ** Genomics and Epigenomics +# + NGS and array-based Genomics and Epigenomics of complex human +# diseases using RNA-seq, targeted DNA sequencing, RRBS, Illumina +# bead arrays, and Affymetrix microarrays from sample collection to +# publication. +# + Reproducible, scalable bioinformatics analysis using make, +# nextflow, and cwl based workflows on cloud- and cluster-based +# systems on terabyte-scale datasets +# + Alignment, annotation, and variant calling using existing and custom +# software, including GATK, bwa, STAR, and kallisto. +# + Correcting for and experimental design to overcome multiple +# testing, confounders, and batch effects using Bayesian and +# frequentist methods approaches +# + Using evolutionary genomics to identify causal human variants ** Big Data + Parallel and Cloud Computing (slurm, torque, AWS, OpenStack, Azure) + Inter-process communication: MPI, OpenMP -- 2.39.5