Dave Tang

learning_vcf_file. Learning the Variant Call Format

learning_bam_file. Learning the Sequence Alignment/Map format

learning_docker. Learning about Docker.

machine_learning. Machine learning in R

defining_genomic_regions. Define regions in the genome

sars_cov_2. Bioinformatics analysis of SARS-CoV-2

research_parasite. How research parasites can download your data!

romim. R package for querying the OMIM database

learning_random_forest. Notes and code for learning Random Forests

reproducible_bioinformatics. Workshop material for BioC Asia 2019

learning_bash. My Bash notes

rnaseq. RNA-seq analyses.

cv. My curriculum vitae

learning_python. My repository for learning Python

human_phenotype_ontology. Resources for working with the Human Phenotype Ontology

getting_started_with_c. Learning how to code in C

bioinformatics_tips. R

learning_singularity. Learning about Singularity (the container platform and not the technological singularity)

learning_r. R notes

scRNA-seq_notes. A list of scRNA-seq analysis tools

getting_started_with_latex. Getting started with LaTeX

importbio. R

muse. Updated posts from my blog

daily_tips. One tip each day

Cancer_notes. A continually expanding collection of cancer genomics notes and data

oneliners. Useful bash one-liners for bioinformatics.

getting_started_with_git. Learning Git

cookiemonster. Cookiecutter templates

learning_awk. Finally learning AWK instead of being annoyed at its syntax

blogs. Links to data science, bioinformatics, statistics, and machine learning resources

learning_vim. Vim notes

vcf2prot. Accelerate the generation of personalized proteomes from a Variant calling format (VCF) file and a reference proteome using graphical processing units (GPUs).

scrnaseq. Single cell RNA sequencing

tang_sd_2015. Perl

immune_repertoire. B-cell and T-cell Adaptive Immune Receptor Repertoire analysis

learning_shiny. Learning about Shiny