Bioinformatics Training Workshop @ PAG2020

‐ Functional Annotations of Animal Genomes Workshop

Notice:

For participants do not meet the prerequisites, the workshop will start at 2:00PM January 8, 2020; while for advanced participants who have basic knowledge of and experience with UNIX command line and R programming language are expected to start at 8:00 AM January 9, 2020. To prepare yourself for the workshop, you can teach yourself some basic Unix and R via the resources provided by the appendix.

	Day 1: Jan 8, 2020 (2:00 PM - 5:30 PM)
2:00-2:20	registration and welcome
2:20-3:20	Introduction to UNIX command line (Lecture and hands-on session) Intro to the UNIX operating system (ssh, terminal, file system) Handle paths and files (ls, cp, cd, mkdir, rm, find, touch, mv, ln) View content of files (less, more, head, tail, vi, cat) Search content of files (grep, wildcards) Get help (man) File permission (chmod) Process and job Resource management (df, du, quota, ...) Other goodies (gzip/unzip, tar, zcat, cut, paste, join, file, diff, history)
3:20-3:30	break
3:30-5:30	Introduction to R (Lecture and hands-on session) R/RStudio installation and setup Data structure and manipulation (vector, list, array/matrix, data frame/table) Data input and output Get help Flow control (if/else, for, while, repeat, break, next) Function Intro to Object oriented programming in R (S3/S4 classes, reference class). R package management Different modes of running R scripts (interactive and batch)
	Day 2: Jan 9, 2020 (8:00 AM -6:30 PM)
8:00-8:15	registration and welcome
8:15 -9:15	Advanced Unix command line (Lecture and hands-on session) Regular expression, sed, awk, xargs pipe, redirection, shell scripting Large data management: download, copy, backup(scp, ftp, ascp, rsync) Software installation and management (module, configuration file, ...) HPC job management systems (one or 2 out of SLURM, SGE, PBS, LSF, ...)
9:15-9:25	break
9:25-10:55	Exploratory data analysis and Data visualization in R (Lecture and hands-on session) Descriptive statistics (frequency, correlation, statistic tests, PCA, MDS, hierarchical clustering) R graphics (base, ggplot2): all types of plots, and heatmap
10:55-11:05	break
11:05-12:00	Introduction to some very useful R/BioConductor packages (mainly lecture and some hands-on session) Readr, data.table tidyverse, dplyr,reshape2, tidyr, stringr, lubridate ggvis, plotly, htmlwidgets, googleVis, threejs lme4/nlme, survival, caret shiny, rmarkdown, solidify For more useful packages, see https://awesome-r.com/
12:00PM-1:00	lunch
1:00-2:00	Introduction to NGS technologies, common types of genomics data, and handling tools (Lecture) Illumina and other sequencing technologies fastq, fasta, BAM, SAM, bed, gtf, gff, bigwig, ... read QC: FASTQC, MultiQC Short read aligners, SAMtools, picardtools, bedtools- Visualization: IGV, UCSC genome browser
2:00-2:10	break
2:10-3:20	RNA-seq data analysis (I) (Lecture) (REF) Experimental design, RNA-seq data characteristics Read QC (FASTQC, MultiQC) Optional preprocessing: trimming (Trimmomatic/Trim Galore), error correction (Rcorrector) Alignment (STAR, HISAT, GMAP/GSNAP, RSEM) or semi-alignment (Kallisto, Salmon) Post ‚Äìalignment QC (QoRT) Optional post-alignment process: multi-mapper assignment (MMR) Count summary (featureCounts) Exploratory analysis (PCA, hierarchical clustering) Differential expression analysis (statistic model selection): DESeq2/edgeR, Voom Gene ontology and pathway analysis Network analysis
3:20-3:30	break
3:30-5:30	RNA-seq data analysis (II) (hands-on session) Exercises with toy data for QC and mapping, and real life count table for DEG, discussion
5:30-6:30	ChIP-seq data analysis (I) (Lecture) (REF) Experimental design, data characteristics Read QC (FASTQC, MultiQC) Optional preprocessing: trimming (Trimmomatic/Trim Galore), error correction (Rcorrector) Alignment (bwa-mem, bowtie/bowtie2) Post-alignment QC (picard tools, deeptools, ChIPQC, SPP) Peak Calling (MASC2, MUSIC/BCP) Peak annotation (ChIPSeeker, GREAT)
	Day 3: Jan 10, 2020 (8:00 AM -12:00 PM)
8:00-10:00	ChIP-seq data analysis (II) (Hands-on session) Exercises, discussion
10:00-10:10	break
10:10-11:00	ATAC-seq data analysis (Lecture, providing scripts for analysis) Experimental design, data characteristics Read QC (FASTQC, MultiQC) Optional preprocessing: trimming (Trimmomatic/Trim Galore), error correction (Rcorrector) Alignment (bwa-mem, bowtie/bowtie2) Post-alignment QC (picard tools, deeptools, ATACseqQC) (REF) Peak Calling (MASC2) Peak annotation (ChIPSeeker, GREAT)
11:00-12:00	NGS data and metadata management (Lecture and demo) [Instructor: Peter Harrison @ EBI] FAANG data and metadata submission Querying and downloading legacy NGS data from ENA SRA databases

APPENDIX: Resources for preparing yourself to meet the prerequisites

Resources for learning basics of UNIX (you can pick one of them you like most)
- UNIX Tutorial for Beginners: [http://www.ee.surrey.ac.uk/Teaching/Unix/](http://www.ee.surrey.ac.uk/Te aching/Unix/)
- Learning UNIX through exercises: [https://www.doc.ic.ac.uk/~wjk/UnixIntro/](https://www.doc.ic.ac.uk/~wjk/ UnixIntro/)
- Learn Shell Programming - Free Interactive Shell Programming Tutorial: [https://www.learnshell.org/](https://www.learnshell.org/)
- Free Linux shell access is available here: [https://bellard.org/jslinux/](https://bellard.org/jslinux/) or [https://linuxzoo.net/](https://linuxzoo.net/)
- Resources for learning R basics (you can pick one you like most)
- Lear R, in R: [https://swirlstats.com/](https://swirlstats.com/)
- Quick R: [https://www.statmethods.net/r- tutorial/index.html](https://www.statmethods.net/r-tutorial/index.html)
- Introduction to R (DataCamp free course, providing interactive programming): [https://www.datacamp.com/courses/free-introduction-to- r](https://www.datacamp.com/courses/free-introduction-to-r)
- Free RStudion cloud for practice: [https://rstudio.cloud/](https://rstudio.cloud/)
Install R and RStudio Please follow this link to install R and RStudio before workshop: [https://www.datacamp.com/community/tutorials/installing-R-windows-mac- ubuntu](https://www.datacamp.com/community/tutorials/installing-R- windows-mac-ubuntu)

This Bioinformatics Training Workshop was financially supported by USDA NIFA grant 2020-67015-30982, as well as the Swine, Horse, Poultry and Bovine NRSP8 Genome Coordinators.