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33 repositories
- Consensus pathway analysis module developed by the University of Nevada at Reno
- In this module, you will learn how to use a Nextflow pipeline to assemble and annotate a novel transcriptome using RNA-seq data
- RNAseq workflow run using BASH, Nextflow, and Snakemake on AWS and GCP, developed as part of the NIH NIGMS Sandbox
- In this module, you will harness novel machine learning techniques to investigate how proteins behave. A special focus will be given to data preprocessing, model training, and evaluation techniques to uncover complex biological relationships
- This repository offers an introductory Python module for bioinformatics, emphasizing practical coding techniques for biological scientists. It covers Python basics, data handling with NumPy and Pandas, and cloud computing on Azure.
- In this module, you will learn how sequencing data is generated and go through a detailed guide on assembling, assessing, and annotating a bacterial genome. You will then automate the workflow and perform a large-scale comparative genomic analysis.
- This repository provides a comprehensive module on structural biology and drug discovery, covering protein structure, docking, and drug design. It runs on Google Cloud Platform using Jupyter notebooks and includes tools like PyMOL and AutoDock.
- The MeRIP-seq data analysis tutorial is structured into four submodules, designed to comprehensively guide users through the complete workflow for RNA methylation analysis
Intro-to-Pangenomics
PublicThis repository provides a comprehensive module on graphical pangenomics, guiding users through building, indexing, mapping, and visualizing pangenome graphs. The module runs on Google Cloud Platform using Jupyter notebooks and includes tools like PGGB, vg, BLAST, and Bandage.- Secondary analysis of Proteomics data in R, developed by the University of Arkansas for Medical Sciences for the NIH NIGMS Sandbox project.
- Multi-omics module that includes RNAseq, Epigenetics, and integrated multi-omics analyses developed as part of the NIGMS Sandbox project
- In this module, you will learn how to download raw sequence data, calculate differentially methylated regions, and run a canonical methyl-seq pipeline in Nextflow
- Introduction to bioinformatics command line tools on the cloud, developed by Dartmouth College
- In this module, you will take a deeper look at RNA-sequencing using single-cell approaches and miRNA sequencing, and investigate their impacts on gene regulation
- R-based module that uses machine learning in biomarker discovery
- Python-based machine learning and data science module from SFSU developed for the NIGMS Sandbox project
- ATAC-seq and scATAC-seq module developed by the University of Nebraska Medical Center
- In this module, you will learn how to use a Docker container to analyze amplicon sequencing metagenomics data with common tools such as qiime2 and PICRUSt2
- Machine Learning module for cloud-based analyses developed as part of the NIGMS Sandbox Project
- In this module, you will learn to solve protein structure from crystallography data. This course will cover detailed aspects of protein structures, from primary to quaternary levels, and explores physiochemical principles using common bioinformatics tools
- This repository provides a comprehensive tutorial for phylogenetic analysis, covering data collection, sequence alignment, tree construction, and interpretation. It runs on AWS SageMaker using Jupyter notebooks and includes tools like MAFFT, Nextclade, and IQ-TREE.
- This repository provides a cloud-based learning module for microbial analysis of 16S rRNA sequencing data. It covers principles, data preprocessing, taxonomic classification, and diversity analysis using R and AWS SageMaker.
NIGMS-Sandbox-Repository-Template
Public template- This repository offers an introductory data science module using R and cloud computing on Google Cloud Platform (GCP). Key topics include R programming, Tidyverse (dplyr, tidyr, ggplot2), statistical methods (ANOVA, Linear Regression), and RNAseq analysis (Salmon, DESeq2).
- This repository offers a tutorial for assembling RADseq data and performing basic population genetic and phylogenetic analyses. It runs on Google Cloud Platform using Jupyter notebooks and covers RADseq data processing, population structure analysis, and phylogenetic tree inference and plotting.
NIGMS-Sandbox
PublicCollection of cloud-based biomedical data science learning modules funded by the National Institute of General Medical Sciences at the NIHChromatin-Occupancy
PublicIn this module, you will learn how to perform the bioinformatics analysis of differential chromatin occupancy using data generated by three well-known high-throughput sequencing assaying, including differences between them and integration of chromatin accessibility and differential gene expression- This repository provides a practical, data-centric AI/ML module for biomedical researchers. It covers R programming, data preparation, model building, and AI/ML applications using AWS SageMaker and Jupyter notebooks.
Workshop-Tutorials
Public