GWAS related websites

• PLINK

Some useful SNP annotation databases:

• SeattleSeq Annotation
• GEN2PHEN Knowledge Centre
• Duke SequenceVariantAnalyzer, or SVA
• SNP Function Portal from University of Michigan
• PolyPhen (=Polymorphism Phenotyping): prediction of functional effect of human nsSNPs
• SIFT from J.Craig Venter Institute

Related web-tools

• Integrative Genomics Viewer (IGV)

Gene-based test

• VEGAS, or Versatile Gene-based Association Study

Convert PLINK file for Haploview

Suppose you have test.bim, test.bed, and test.fam for PLINK.
1) generate ped/map files
plink --noweb --bfile test --recode --alleleACGT --prune --out gene
This will generate a ped file, gene.ped, coded by letters (instead of numbers) and a map file, gene.map, including marker information.
The "--prune" option removes individuals with missing phenotype. If you don't use "--prune", you may need to update the ped file accordingly because in PLINK ped file, -9 is used for missing while in Haploview/Linkage ped file, 0 is used for missing. Here are some suggestion command lines in R:
----------------------------------------------------------------------------
ped = read.table("gene.ped")
ped[,6]==-9 -> x
ped[x, 6]=0
write.table(ped, file="gene.ped2", row.names=F, col.names=F, quote=F)
----------------------------------------------------------------------------
2) convert map file to contain only marker and position
cut -f 2,4 gene.map > gene.map2
The generated gene.ped and gene.map2 can be input into Haploview as "Linkage format".

Shell command to convert PLINK output

PLINK results are sepecrated by multiple spaces for nice print-out: a variable number of spaces actually, which is not convenient for programming.
1) convert to tab separated file: first remove spaces in the beginning of every line, then replace other spaces to tab
sed -r 's/^\s+//g' plink.assoc | sed -r 's/\s+/\t/g' > plink.tab
2) extract certain columns: cut uses tab as delimiter for default
sed -r 's/^\s+//g' plink.assoc | sed -r 's/\s+/\t/g' | cut -f 2 > SNPlist
If the file is separated by space, like fam file, use this:
cut -d " " -f 2

Resources for miRNA target prediction

Target prediction

1. TargetScan (http://www.targetscan.org/): data can be directly downloaded
2. miRanda (http://www.microrna.org/microrna/home.do)
3. RNAhybrid (http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/): no data downloadable, but software is available; there is also a webservice which can be accessed through Perl or Java.
4. PicTar (http://pictar.mdc-berlin.de/): online search or downloaded here:
5. DIANA-MicroT (http://diana.cslab.ece.ntua.gr/microT/): data can be directly downloaded

Experimental database

1. TarBase (http://diana.cslab.ece.ntua.gr/tarbase/): from the same DIANA lab

miRNA vs. disease

1. miR2Disease Base (http://www.mir2disease.org/): data available

Comprehensive tools

1. GOmir (http://www.bioacademy.gr/bioinformatics/projects/GOmir/): stand-alone Java tool

Next-generation sequencing seminar

Seminar Information:
--------------------------------
Tuesday, July 13, 2010
Vanderbilt University
Light Hall
2215 Garland Ave
Nashville, TN 37232
Room 512
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Seminar Schedule
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1:00 Registration
1:30 Introduction