ISCB2017 - Workshop for Proteomics Data Analysis and Bioinformatics (p2364)

This R package contains data and vignette files for a Pigeon Pea (Cajanus cajan) project from a Indo-Swiss Collaboration in Biotechnology (ISCB) training course on proteome informatics given from January 21th to January 25th 2017 at the National Research Centre on Plant Biotechnology (NRCPB) in New Delhi-110012 by JG, WEW, and CP.

Overview of the week

Day 1 (Common Day)

• Morning Session: Responsible SE -> Ingrid & Urs
• Afternoon Session: Responsible PrXIT -> Jonas

Day 2 (Protein Identifications)

Module Number | Theoretical Part | Hands-on Module | Duration | Main responsible Person ------------ |------------ | ------------- | ------------- | ------------- 1 | Outline for this week | break | 0.5 h | jg 2 | The FGCZ in Zurich | browse FGCZ page | 0.5 h | jg 3 | Mass spectrometry (and protein analytics) | browse around for milestones in MS, form groups, introduce yourself and your task | 1 h | jg 4 | Getting ready for hands-on sessions | Install MQ, do git co, commits, get R packages | 1 h | CP 5 | PSM identification with protViz | get fasta, R (seqinR), R (digest), theoretical considerations about search space, different DBs, uniqueness of peptides. | 2.5h | CP 6 | Protein identification VALIDATION with target-decoy strategy | FDR | 2h | WEW 7 | Start your own MQ | run it on your PC | 1h | jg 8 | Conclusion of day 1 | Q & A | 1h | all

Day 3 (Protein Quantification)

Module Number | Theoretical Part | Hands-on Module | Duration | Main responsible Person ------------ |------------ | ------------- | ------------- | ------------- 1 | Repetition of Day 1 | Q & A | 0.5 h | all 2 | About Plots | coffee break | 0.5 h | JG 3 | Protein, Peptide, Mass-spec view and LFQ | hands-on LFQ | 3h | JG/CP 4 | Experimental design in quant experiments | Looking at annotation of samples in Bfabric | 1h | jg 5 | Two group analysis for Yeast, grown on different nutrient sources | Analysing 2 groups in R-quantable | 2h | WEW 6 & 7 | Principle of ORA and Webtools for model organisms | Webgestalt, StringDB, YeastCyc w YEAST results | 2h | cpNjg 8 | Conclusion of day 2 | Q & A | 1h | jg

Day 4 -> Republican Day

Day 5 -> Look at Pigeon Pea and Wrap up of the whole course -> identify room for improvements ;)

Module Number | Theoretical Part | Hands-on Module | Duration | Main responsible Person ------------ |------------ | ------------- | ------------- | ------------- 1 | Repetition of Day 3 | Q & A | 0.5 h | all 2 | fun with | R, CRAN & Bioconductor | 1.5 h | CP/WEW 3 | blast | | 0.3 h | CP 4 | Look at the Pigeon Pea project | Make use of what we learnt in the pigeon pea project | 3h | all 5 | Wrap up of the course | Course Evaluation | 1h | all

additionally if we have too much time ;)

• Quantitative proteomics strategies (an overview) | break | 1h | jg | Combo-course day4 (NSK) (show 12)
• Label-free quantification | MQ: txt-tables | 1h | jg | Combo-course day4 (partI) (show 13)
• YeastData: RNASeq vs PrX: Number crunch | Shiny-app | jg | 1h

Organisational issues:

Student should bring:

• own laptop (Windows or Mac/Linux w Virtual Box and Windows instance)
• equiped with: Editor (vi, nano, ..), R., RStudio, git
• some free space (20gigs at least)

Bfabric Project

http://fgcz-bfabric.uzh.ch/bfabric/userlab/show-project.html?projectId=2364

Publications to study (upfront)

• Review (Aebersold n Mann) -> https://www.ncbi.nlm.nih.gov/pubmed/27629641
• MQ -> https://www.ncbi.nlm.nih.gov/pubmed/24942700
• LFQ -> https://www.ncbi.nlm.nih.gov/pubmed/23391308
• MSQC1 -> https://www.ncbi.nlm.nih.gov/pubmed/27130639
• Top3 Protein quantification -> https://www.ncbi.nlm.nih.gov/pubmed/20576481

Howtos

install the ISCB2017 R package

{r} install.packages('devtools') library(devtools) install_git('https://github.com/fgcz/ISCB2017', build_vignettes = TRUE, quiet = FALSE)

build the ISCB2017 R package

{r} roxygen2::roxygenise()

read the vignettes

```{r}

get an overview

library(ISCB)

vignette(package="ISCB2017") vignette('peakplot') vignette('fdr') vignette('lfq') ```

Notes by CP

References for R

• An Introduction to R
• Visualizing data, William S. Cleveland, Murray Hill, New Jersey: AT&T Bell Laboratories 1993
• Lattice, Multivariate Data Visualization with R, Deepayan Sarkar , 2008
• Uses and misuses of the fudge factor in quantitative discovery proteomics.