Name: Vang Le
Type: User
Company: Aalborg University
Bio: Hacking Python, R, Javascript, C, C++, D, Java, Scala, SQL (MySQL, Postgres, SQLite), Docker, Singularity. Stopped writing new code in Perl. Eyeing Go, Julia.
Location: Aalborg, Denmark
Vang Le's Projects
Data Engineering class
A collection of Aalborg University LaTeX-templates
Assembly Based ReAligner
Algorithm for secondary de novo genome assembly guided by closely related references
This is a collection of modules that I've released over the years. Most of them stand alone, or have just one or two dependencies in here, so you don't have to download this whole repo. You may find some ddoc here:http://arsdnet.net/ddoc/ or you can always ask me for help.
Pipeline components for real-time phylodynamic analysis
Web app for visualizing pathogen evolution
:sunglasses: Curated list of awesome lists
A curated list of awesome Bioinformatics libraries and software.
A curated list of awesome C frameworks, libraries, resources and other shiny things. Inspired by all the other awesome-... projects out there.
Awesome configuration for Hammerspoon.
A minimal Ubuntu base image modified for Docker-friendliness
Best-practice pipelines for fully automated high throughput sequencing analysis
general purpose library for evaluating the likelihood of sequence evolution on trees
BEDOPS: high-performance genomic feature operations
A powerful toolset for genome arithmetic.
Random collection of bioinformatics thingies
A catalog of interesting bioinformatics software, mostly those available on Github that I work with
BWK awk modified for biological data
Conda recipes for the bioconda channel.
Travis test and delete soon
Life and code
Bioinformatics library in D. (utils for working with SAM, BAM, SFF formats)
Bioinformatics for the Scala programming language
Collection of handy scripts for bioinformatic work
Chanjo provides a better way to handle sequence coverage data in clinical sequencing.
My cheatsheets
a tool for CNV discovery and genotyping from depth-of-coverage by mapped reads
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1