Funseq
From GersteinInfo
|  (→A. Required Tools) |  (→A. Required Tools) | ||
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| 3) [http://vat.gersteinlab.org/index.php VAT] - A good installation guide for VAT can be found [http://ngsda.blogspot.com/2011/06/vat.html here]. <br> | 3) [http://vat.gersteinlab.org/index.php VAT] - A good installation guide for VAT can be found [http://ngsda.blogspot.com/2011/06/vat.html here]. <br> | ||
| 4) [http://bioinfo.lifl.fr/TFM/TFMpvalue/ TFMpvalue-sc2pv]<br> | 4) [http://bioinfo.lifl.fr/TFM/TFMpvalue/ TFMpvalue-sc2pv]<br> | ||
| - | 5) [http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/ bigWigAverageOverBed] | + | 5) [http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/ bigWigAverageOverBed]<br> | 
| 6) [http://www.r-project.org R] - Only needed for differential gene expression analysis | 6) [http://www.r-project.org R] - Only needed for differential gene expression analysis | ||
| <br> | <br> | ||
Revision as of 20:45, 17 October 2013
| Contents | 
Installation
A. Required Tools
The following tools are REQUIRED for FunSeq: 
1) Bedtools 
3) Tabix 
3) VAT - A good installation guide for VAT can be found here. 
4) TFMpvalue-sc2pv
5) bigWigAverageOverBed
6) R - Only needed for differential gene expression analysis
B. PERL Requirement
1) Please make sure you have Perl 5 and up. Latest PERL can be downloaded here. 
2) Install package Parallel::ForkManager (this package is used for parallel running). The PERL library can be found here.
C. FunSeq tool installation
FunSeq is a PERL- and Linux/UNIX-based tool. At the command-line prompt, enter the following: 
$ cd FUNSEQ/ $ perl Makefile.PL $ make $ make test $ make install
D. Required Data Files
Please download all the following data files from ' http://funseq.gersteinlab.org/data/ ' and put them in a new folder ' $path/funseq-0.1/data/ ': 
	1.	1kg.phase1.snp.bed.gz   (bed format) 
			Contents : all 1KG phaseI SNVs in bed format. 
			Columns : chromosome , SNVs start position (0-based), SNVs end position, MAF (minor allele frequency) 
			Purpose : to filter out common variants against 1KG SNVs. 
	2.	ENCODE.annotation.gz   (bed format) 
			Contents : compiled annotation files from ENCODE, Gencode v7 and others, includes DHS, TF peak, Pseudogene, ncRNA, enhancers 
			Columns : chromosome , annotation start position (0-based), annotation end position, annotation name. 
			Purpose :  to find SNVs in annotated regions.  
	3.	ENCODE.tf.bound.union.bed  (bed format) 
			Contents : transcription factor (TF) motifs in ENCODE TF peaks.  
			Columns : chromosome, start position (0-based), end position, motif name, , strand, TF name 
			Purpose : used for motif breaking analysis 
	4.	gencode7.cds.bed  (bed format) 
			Contents : extracted CDS information from Gencode7. 
			Columns :  chromosome, start position, end position  
			Purpose : to find SNVs in CDS region 
	5.	gencode.v7.promoter.bed  (bed format) 
			Contents : compiled promoter regions, -2.5kb from transcription start site (TSS) 
			Columns : chromosome, start, end, gene, whether the gene is a hub in protein-protein interaction network (PPI) or regulatory network (REG). 
			Purpose : to associate promoter SNVs with genes 
	6.	gencode.v7.annotation.GRCh37.cds.gtpc.ttpc.interval 
			Purpose : For variant annotation tool (VAT); Gencode v7. 
	7.	gencode.v7.annotation.GRCh37.cds.gtpc.ttpc.fa 
			Purpose : For Variant Annotation Tool (VAT); Gencode v7. 
	8.	DRM_transcript_pairs_modify 
			Contents : distal regulatory module with gene information. 
			Purpose : to associate enhancer SNVs with genes 
	9.	Pouya.motif 
			Contents : PWMs 
			Purpose : used for motif breaking calculation 
	10.	PPI.hubs.txt 
			Purpose : defined hub genes in protein-protein interaction network 
	11.	REG.hubs.txt 
			Purpose : defined hub genes in regulatory network 
	12.	GENE.strong_selection.txt 
			Purpose : genes under strong negative selection (fraction of rare SNVs among non-synonymous variants). 
	13.	human_ancestor_GRCh37_e59/* 
			Contents : this directory contains human ancestral allele in hg19, Ch37.  
			Purpose : for motif breaking calculation in personal or germ-line genome. 
			* Note :  for somatic analysis, these files are not needed. 
	14.	sensitive.nc.bed 
			Contents : coordinates of sensitive/ultra-sensitive regions. 
			Purpose : to find SNVs in sensitive/ultra-sensitive regions. 
Running FunSeq
Usage
Usage : ./funseq -f file -maf maf -m <1/2> -inf <bed/vcf> -outf <bed/vcf>
       Options :
               	-f              user input SNVs file
               	-maf            Minor Allele Frequency (MAF) threshold to filter 1KG phaseI SNVs (value 0 ~ 1)
               	-m              1 - somatic Genome; 2 - germline or personal Genome
               	-inf            input format - BED or VCF
               	-outf           output format - BED or VCF
Default : -maf 0 -m 1 -outf vcf
Input
FunSEQ takes BED or VCF files as input 
1. BED format 
In addition to the three required BED fields, please prepare your file as follows (5 required fields, tab-delimited): 
chrom	chromStart	chromEnd	Reference.allele	Alterative.allele	... 
* chrom - The name of the chromosome (e.g. chr3, chrY).
* chromStart - The starting position of the feature in the chromosome. The first base in a chromosome is numbered 0. * chromEnd - The ending position of the feature in the chromosome. The chromEnd base is not included in the display of the feature. For example, the first 100 bases of a chromosome are defined as chromStart=0, chromEnd=100, and span the bases numbered 0-99. * Reference.allele - The reference allele of SNVs * Alternative.allele - The alternative allele of SNVs.
2. VCF format (http://www.1000genomes.org/node/101) 
The header line names the 8 fixed, mandatory columns. These columns are as follows (tab-delimited): 
- CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO 
 
Output
You can download a sample of the output VCF here. 
FunSEQ can produce either BED format or VCF format files. 
An example of the VCF annotation of a coding variant: 
chr1 36205042 . C A . . OTHER=MAF(1kg-phase1)=0;CDS=Yes;VA=1:CLSPN:ENSG00000092853.8:-:prematureStop:4/5:CLSPN-001: \ ENST00000251195.5:3996_3232_1078_E->*:CLSPN-005:ENST00000318121.3:4017_3232_1078_E->*:CLSPN-003:ENST00000373220.3:3825_3040_1014_E->*:CLSPN-004:ENST00000520551.1: \ 3858_3073_1025_E->*;HUB=PPI;GNEG=Yes;GENE=CLSPN;CDSS=4
- OTHER field contains other original information other than the 5 required ones (chrom, chromStart, chromEnd, reference, alternative). When input file is less than 3,000 lines, OTHER also contains the MAF (minor allele frequency) of SNVs in 1KG Phase1 data.
An example of the VCF annotation of a non-coding variant: 
chr5 85913480 . T C . . OTHER=MAF(1kg-phase1)=0;CDS=NO;HUB=REG;NCENC=TFP(ETS1),TFP(ELF1),TFP(GATA2),TFP(POU2F2), \ TFP(TBP),TFP(SRF),TFP(ELK4),TPM(TAF1),TFP(STAT3),TFP(GATA3),TFP(SIX5),TFP(YY1),TPM(TBP),TFP(CHD2),TFP(MYC),TFP(IRF1),DHS(MCV-2),TFP(TAF1),TFP(GATA1), \ TFP(ZEB1),TFP(SETDB1),TFP(ZNF143),TFP(NFKB1),TFP(MAX),TFP(GABPA),Enhancer(chromHmm),TFP(STAT1); \ MOTIFBR=85913478#85913493#+#TATA_known1_8mer#TAF1,85913478#85913493#+#TATA_known1_8mer#TBP;GENE=COX7C(promoter);NCDS=4
-  NCENC (Non-coding ENCODE annotation) field.  
 
TFP -transcription factor binding peak.  
TFM - transcription factor motifs in peak regions. 
DHS - DNase1 hypersensitive sites, with number of cell lines (MCV- , total 125 cell lines) information (R.E. Thurman et al., The accessible chromatin landscape of the human genome. Nature 489,75, Sep 2012). 
ncRNA - non-coding RNA 
Pseudogene 
Enhancer - chromHmm (genome segmentation), drm (distal regulatory module) 
-  MOTIFBR field. 
 
This field is a hash-delimited tag, defined as follows: 
motif start # motif end # motif strand # motif name # transcription factor name 
An example: " 85913478#85913493#+#TATA_known1_8mer#TAF1 " 
-  NCRECUR field. 
 
Please be aware of large TF peak and chromHMM regions. Because of the low resolution issues, recurrent information may not indicate functional importance.
