Resources: Classes - wallacelab/lab-wiki GitHub Wiki

Table of Contents

General

This is the page The list of courses helpful for bioinformatics work in this lab.
For people conducting research on the microbiome, I strongly recommend MIBO8700, which detailly explains the history, development, and method under the hood of microbiome analysis.

Applied genome analysis is also another useful class, which cover most analysis bioinformatics student will encounter

Special Topics in Microbiology - MIBO 8700

Taxonomic Note: A Place for DNA-DNA Reassociation and 16S rRNA Sequence Analysis in the Present Species Definition in Bacteriology by E. STACKEBRANDT and B. M. GOEBEL.

  • A paper on early day microbiome classification

Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample by E. STACKEBRANDT and B. M. GOEBEL.

  • The one of earliest paper on 16S RNA sequencing
  • Take Home message: Look at the mutation over time to determine the lineage. 16s is a core ribosome, every cell needs 16s genes. Both stable and variable, not encoding for protein but ribosome

Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis by Jethro S. Johnson et.al.

  • This paper compared the accuracy of 16S RNA between different primer regions.

BINF8940: Applied Genome Analyis

  • Conceptual and practical aspects of applying bioinformatics approaches to analyze genomic data. Topics covered will include genome sequence assembly, annotation, variant calling, regulatory genomics, and transcriptomic.

PBGG8871: Genome Analysis and Comparative Genomics

  • The concepts behind genetic mapping, genome analyses and comparative genomics in plants that help students understand the relationships between genomes at the structural and functional level.

PBGG8872: QTL mapping

  • The principles and procedures underlying the establishment of marker-based linkage maps and their application in the establishment of marker-trait associations.

PBGG8874: Genomic Selection

Concepts, implementation, and application of predicting organism phenotypes from genome-wide marker sets. This course covers genomic selection (GS), an application of genome-wide prediction in order to accelerate breeding and reduce phenotyping costs. Course also covers both theory and practice, and requires a good understanding of mixed linear models and genome-wide marker sets.

PBGG8875: Genome-wide Association in Plants

Dr. Wallace's GWAS class. Covers the stats behind GWAS (linear regression) and how to design and carry out GWAS well.

Binformatics II

BINF8600: Introduction to Grant Writing

  • Introduction to the principles of successful grant writing. Students are expected to develop a grant proposal in NIH or NSF format.