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

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

build the ISCB2017 R package

roxygen2::roxygenise()

read the vignettes

# 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.