jordan2lee Goto Github PK

batcheffectspackage

The MBatch R package and Docker image are designed to help assess and correct for batch effects.

battenberg

Battenberg R package for subclonal copynumber estimation

bmeg-dash

bmeg-site

covid19_datadictionary

dash-bootstrap-components

Bootstrap components for Plotly Dash

demo-git-conflict

Demo a git conflict.

demultiplexing-jordan2lee

demultiplexing-jordan2lee created by GitHub Classroom

gdan-tmp-webdash

ggr-cwl

CWL tools and workflows for GGR

grip

Graph Integration Platform

hop-covid-models

jadbiopythonclient

This client provides major JADBio functionality to python users using API calls. Requests are HTTP GET and POST only.

lab-website

logregression-workshop

In biomedical research we often wish to classify data into two or more groups (eg. healthy and diseased) based on a variety of measurement variables, but how do you determine if the model you’ve selected is good? In this BioData Club workshop instructor Crista Moreno will discuss the mathematics of logistic regression for binary classification modeling, and how to prevent the harms of overfitting with cross validation in R. Attendees will gain knowledge through hands-on exercises about the following concepts and data science skills. Logistic regression (logit function, probability, binary classification) Overfitting (adding parameters and high dimensional spaces) Cross validation Cross validation Error R (R markdown, R packages magrittr, dplyr, ggplot2, tidyr, corrplot, caret, rgl) Anyone with interest in building a classification model for biomedical data is encouraged to attend! Prior experience with R, Rstudio, and a basic knowledge of classification modeling (also mathematical functions) will be helpful, but is not a requirement.

motif-mark

Python script to visualize motifs on sequences

sifter

ETL Platform for building JSON schema based data and property graphs