From GersteinInfo

Revision as of 23:18, 5 January 2014 by Public (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Variants Prioritization

A. Required Tools

The following tools are REQUIRED:

sed, awk, grep
bedtools (version bedtools-2.17.0)
tabix (version tabix-0.2.6 and up)
VAT (snpMapper Module) - A good installation guide for VAT can be found here.

If you are only interested in non-coding variants, you don't need to install VAT. But remember to use '-nc' option in Funseq

Retrieve GERP scores. Note that GERP data file is ~7G. If you are not interested in GERP scores, the GERP file and bigWigAverageOverBed are not needed.

R

Only needed for differential gene expression analysis.

Perl package Parallel::ForkManager

Required for parallel running.
Please make sure you have Perl 5 and up.

B. Tool installation

This is a PERL- and Linux/UNIX-based tool. At the command-line prompt, type the following. The purpose is to write the path of funSVPT.pm to your environment.

$ tar xvf funSVPT.v.0.1.tar
$ cd funsvpt-0.1/
$ cd funSVPT/
$ perl Makefile.PL
$ make 
$ make test
$ make install

If you don’t have the permission to modify the environment, open the ‘.bashrc’ file and put the following lines to the end of the file. Then ‘source .bashrc’.

PERL5LIB=${PERL5LIB}: $path_of_the_tool/funsvpt-0.1/funSVPT/lib
export PERL5LIB

C. Pre-built Data Context

All of the data can be downloaded under ‘Downloads’ in the web server. If you would like to use the data, please download them and put them under ‘funsvpt-0.1/data’.

D. Tool Usage

To display the usage of tool, type ‘./run.sh’.

* Usage : ./run.sh -f file -maf MAF -m <1/2> -inf <bed/vcf> -outf <bed/vcf> -nc -o path -g file -exp file 
          -cls file -exf   <rpkm/raw> -p int -cancer cancer_type -s score -uw
       Options :
               	-f		[Required] User Input SNVs File
               	-inf	 	[Required] Input format - BED or VCF
               	-maf 		[Optional] Minor Allele Frequency Threshold to filter 1KG SNVs,default = 0 
               	-m		[Optional] 1 - Somatic Genome (default); 2 - Germline or Personal Genome
               	-outf	 	[Optional] Output format - BED or VCF,default is VCF
               	-nc		[Optional] Only do non-coding analysis, no need of VAT (variant annotation tool)
               	-o		[Optional] Output path, default is the directory 'out'
               	-g		[Optional] gene list, only output variants associated with selected genes. 	
               	-exp		[Optional] gene expression matrix
               	-cls		[Optional] class file for samples in gene expression matrix
               	-exf		[Optional] gene expression format - rpkm / raw
               	-p		[Optional] Number of genomes to parallel, default = 5
               	-cancer		[Optional] cancer type from recurrence database, default is all of the cancer type
               	-uw		[Optional] Use unweighted scoring scheme, defalut is weighted
               	-s		[Optional] Score threshold to call non-coding candidates, default = 1.5 
               			for weighted scoring & default = 5 for unweighted scoring
       
       Multiple Genomes with Recurrent Output	
               	Option 1: Separate multiple files by ','
               	Example: ./run.sh -f file1,file2,file3,... -maf MAF -m <1/2> -inf <bed/vcf> -outf <bed/vcf> ...
               	Option 2: Use the 6th column of BED file to specify samples
               	Example: ./run.sh -f file -maf MAF -m <1/2> -inf bed -outf <bed/vcf> ...
               	
               	NOTE: Please make sure you have sufficient memory, at least 3G.

E. Input file format

User input file (-f): could be either BED format or VCF format.

BED format. In addition to the three required BED fields, please prepare your file as follows (5 required fields, tab delimited; 
the 6th column is reserved for sample names, do not put other information there): 
chromosome, start position, end position, reference allele, and alternative allele.
       Chromosome - name of the chromosome (e.g. chr3, chrX)
       Start position - start position of variants. (0-based)
       End position - ending position of variants. (end exclusive)
               e.g., chr1   0     100  spanning bases numbered 0-99
       Reference allele - reference allele of variants
       Alternative allele - alternative allele of variants
       
VCF forma. The header line names the 8 fixed, mandatory columns. These columns are as follows (tab-delimited):  
#CHROM POS ID REF ALT  QUAL FILTER INFO
       
Recurrent analysis input format
       Option 1: separate files for each genome (BED or VCF). Use “-f file1, file2, file3” separated by comma.
       Option 2: put all variants in one file (only for BED format, use the 6th column labeling sample names). Use “-f file”.

Gene list format (-g): If you are interested in particular set of genes, you can put your genes in one file (one gene per row) and use “-g file” to instruct the program to only analyze variants in or linked to those genes. Please use gene symbols.

Gene expression format (-exp): Users can also upload gene expression data for the program to detect differentially expressed genes between cancer and benign samples and highlight variants linked to these genes. The gene expression data should be prepared as a matrix with first column stores gene names (use gene symbols) and first row as sample names. Other fields are gene expression data either in rpkm or raw read counts. Tab delimited.

e.g.,

Gene Sample1 Sample2 Sample3 Sample4 … A1BG 1 5 40 0 … A1CF 20 9 0 23 … … … … … … …

Sample class format (-cls): In addition to the expression data, users need to upload annotations of samples as “cancer” or “benign” (only two classes “cancer” or “benign”). The number of samples in this file should equal to that in expression data. And sample names should match.

e.g.,

Sample1 benign Sample2 cancer Sample3 cancer Sample4 benign … …

Output

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:
TF name # motif name # motif start # motif end # motif strand # mutation position # alternative allele frequency in PFM # reference allele frequency in PFM
An example: " TAF1#TATA_known1_8mer#85913478#85913493#+#3#0.02#0.4 "

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.

Building data context

Usage

Usage : ./funseq -f file -maf maf -m <1/2> -inf <bed/vcf> -outf <bed/vcf> -nc
       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
                -nc              [Optional] Only do non-coding analysis.

       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
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

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:
TF name # motif name # motif start # motif end # motif strand # mutation position # alternative allele frequency in PFM # reference allele frequency in PFM
An example: " TAF1#TATA_known1_8mer#85913478#85913493#+#3#0.02#0.4 "

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.

FunSVPT

From GersteinInfo

Contents

Variants Prioritization

A. Required Tools

B. Tool installation

C. Pre-built Data Context

D. Tool Usage

E. Input file format

Output

Building data context

Usage

Input

Output

Views

Personal tools

GersteinLab Public Wiki

Search

Toolbox