gaospecial/hrm-ml

Supplementary materials for enabling reproducible study

HRM-ML Paper

This repository provides the supplementary materials for the following study:

Precise prediction of dual-species synthetic community structure with high-resolution melting curve and machine learning authored by Chun-Hui Gao, Jiaqi He, Bin Cao, Huan He, Rui Zhang, Cong Lan, Yichao Wu, and Peng Cai. In submission.

Read the contents

• Online Book: https://hrm-ml.bio-spring.top

• PDF document: https://hrm-ml.bio-spring.top/HRM-ML-Paper.pdf

Compile by yourself

Requirements

This project depends on several Python modules and R packages.

• Python
  • scikit-learn
  • numpy
  • pandas

Using conda.

conda create -n hrm-ml
conda activate hrm-ml
conda install scikit-learn numpy pandas

• R
  • tidyverse
  • tidymodels
  • mcmodel: in GitHub.

Using pak to install.

install.packages("pak")
pak::pak("tidyverse")
pak::pak("tidymodels")
pak::pak("gaospecial/mcmodel")

Compile

Using RStudio.

git clone https://github.com/gaospecial/hrm-ml
cd hrm-ml

Open *.Rproj file with RStudio, and press <SHIFT> + <CMD> + B to compile the book.