Pinned Repositories
courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
WholeGenomesPractical
Whole genomes practical for the SSCM Genetic Epidemiology Short Course
ads1-notebooks
Copies of notebooks used in the practical sessions for Algorithms for DNA Sequencing
Algorithms-for-DNA-sequencing
Codes from Coursera's course Algorithms for DNA sequencing, part of genomic data science specialization offered by Johns Hopkins University
Algorithms-for-DNA-Sequencing-1
Coursera MOOC Algorithms for DNA Sequencing by Ben Langmead, PhD, Jacob Pritt
BDA_R_demos
Bayesian Data Analysis demos for R
BioConductor
coursera-ads
Solutions to Algorithms for DNA Sequencing
CourseraLectures
Lecture Materials for Coursera Courses by Roger Peng
COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
msbs2013's Repositories
msbs2013/COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
msbs2013/BDA_R_demos
Bayesian Data Analysis demos for R
msbs2013/fmj
msbs2013/homework-0
msbs2013/interactive-tutorials
Interactive Tutorials
msbs2013/rethinking
Statistical Rethinking course and book package
msbs2013/distribution-zoo
App to view distribution properties and access dynamic code in R, Python, Matlab, Mathematica and Stan
msbs2013/Rcode-Stats-Bubbles
Here is the material for a workshop series about biostatistics in R. Topics will include data management, a lot of (generalized) linear (mixed) models, bayesian and frequentist principles, simulations, multi-model inference... or whatever you ask me for
msbs2013/figures
R code for figures on Statistics with R slides
msbs2013/pyexcel
Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files
msbs2013/labs
Rmd source files for the HarvardX series PH525x
msbs2013/dlbook_exercises
Exercises for the Deep Learning textbook at www.deeplearningbook.org
msbs2013/StatMedPolicyHealth
DataAnalysis for Medicine and Public Health and Policy
msbs2013/courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
msbs2013/WholeGenomesPractical
Whole genomes practical for the SSCM Genetic Epidemiology Short Course
msbs2013/Tutorial
msbs2013/mychembl
Resources used to create the myChEMBL virtual machine
msbs2013/kruschke-doing_bayesian_data_analysis
John K. Kruschke's Doing Bayesian Data Analysis: A Tutorial with R and BUGS
msbs2013/Algorithms-for-DNA-sequencing
Codes from Coursera's course Algorithms for DNA sequencing, part of genomic data science specialization offered by Johns Hopkins University
msbs2013/BioConductor
msbs2013/genbioconductor
Materials for Genomics Data Science: Introduction to Bioconductor
msbs2013/Python
Python script and Documents
msbs2013/Algorithms-for-DNA-Sequencing-1
Coursera MOOC Algorithms for DNA Sequencing by Ben Langmead, PhD, Jacob Pritt
msbs2013/mr-code
Code for implementing Mendelian randomization investigations
msbs2013/ads1-notebooks
Copies of notebooks used in the practical sessions for Algorithms for DNA Sequencing
msbs2013/genstats
Statistics course for JHU Genomic Data Science Sequence
msbs2013/genstats_site
Site for Genomic Data Science Class
msbs2013/coursera-ads
Solutions to Algorithms for DNA Sequencing
msbs2013/R-Coursera
R Programming by Roger D. Peng, PhD, Jeff Leek, PhD, Brian Caffo, PhD on Coursera.org
msbs2013/Statistical-Inference-Coursera
Course Instructor(s) The primary instructor of this class is Brian Caffo Brian is a professor at Johns Hopkins Biostatistics and co-directs the SMART working group This class is co-taught by Roger Peng and Jeff Leek. In addition, Sean Kross and Nick Carchedi have been helping greatly.