Skip to content

Latest commit

 

History

History
146 lines (109 loc) · 6.57 KB

Schedule for Bioinformatics Training Workshop at PAG 2020.md

File metadata and controls

146 lines (109 loc) · 6.57 KB

Schedule for Bioinformatics Training Workshop @ PAG2020

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.

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) (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728800/)

  • 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 –alignment 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): https://www.ncbi.nlm.nih.gov/pubmed/22955991

  • 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): https://www.ncbi.nlm.nih.gov/pubmed/29490630
  • 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)

Resources for learning R basics (you can pick one you like most)

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