Name: Hugo Gabriel Eyherabide
Type: User
Bio: I'm a dad with a PhD in physics, interested in electrical engineering, complex systems, bioinformatics, statistics, software, communication, cooking and sports.
Location: Finland
Blog: eyherabidehg.com
Hugo Gabriel Eyherabide's Projects
Blazing fast and lightweight autocomplete widget without dependencies. Only 1KB gzipped. Demo:
This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.
This is the official development repository for BCFtools. To compile, the develop branch of htslib is needed: git clone --branch=develop git://github.com/samtools/htslib.git htslib
Quick and easy product tours with Twitter Bootstrap Popovers
The Docker CLI
Command-line tools performance for data analysis
The Python programming language
Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments
R's data.table package extends data.frame:
dbSNP
The book Distributed systems: for fun and profit
Documentation for the ANNOVAR software
Notes, tips and issues that may be useful for docker development
Burst firing is a neural code in an insect auditory system
Bursts generate a non-reducible spike pattern code
When and why noise correlations are important in neural decoding
Disambiguating the role of noise correlations when decoding neural populations together
Neural Stochastic Codes, Encoding and Decoding
Collection of comments on floating-point arithmetic (e.g. rounding in GCC) for future reference to myself that may also be useful for others.
Notes while learning f# that might be of interest in the future
Comparison of genetic maps provided with different genetic phasing and imputation tools
Script to convert GTC/BPM files to VCF
Using jq for parsing NCBI dbsnp json files
:closed_lock_with_key: Access the system credential store from R
A DSL for data-driven computational pipelines
Notes about rounding probabilities
A comprehensive update to the PLINK association analysis toolset. Beta testing of the first new version (1.90), focused on speed and memory efficiency improvements, is finishing up. Development is now focused on building out support for multiallelic, phased, and dosage data in PLINK 2.0.