VAT Documentation
Installing and Configuration VAT
Installation of the external GSL and GD libraries
In order to install VAT two external libraries must be installed first. The libBIOS library depends on GSL, whereas VAT makes use of the GD library. Please follow the instructions provided by each package. The GSL library can be installed on most systems using the following commands (for details, please refer to the specific instructions at the GNU Scientific Library website):
$ cd /path/to/gsl-1.14/ $ ./configure --prefix=`pwd` $ make $ make install
Similarly, the GD library can be installed on most systems with the following commands:
$ cd /path/to/gd-2.0.35/ $ ./configure --prefix=`pwd` --with-jpeg=/path/to/jpegLib/ $ make $ make install
After they are installed, the first step to install VAT is the installation and configuration of libBIOS.
Installation and Configuration of libBIOS
Depending on where the three libraries (GSL, libBIOS, and GD) are installed, the following variables need to be set:
export CPPFLAGS="-I/path/to/gsl-1.14/include -I/path/to/libbios/include -I/path/to/gd-2.0.35/include" export LDFLAGS="-L/path/to/gsl-1.14/lib -L/path/to/libbios/lib -L/path/to/gd-2.0.35/lib" export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:path/to/gsl-1.14/lib:/path/to/libbios/lib:/path/to/gd-2.0.35/lib
libBIOS can be installed on most systems with the following commands:
$ cd /path/to/libbios-x.x.x/ $ ./configure --prefix=`pwd` $ make $ make install
Installation and Configuration of VAT
A few simple steps are required to install VAT:
$ cd /path/to/vat-x.x.x/ $ ./configure --prefix=`pwd` $ make $ make install
VAT contains a configuration file that resides in one's home directory as .vatrc
and in the web root as vat.conf
, which contains a set of variables that are used by a number of different programs. The name/value pairs are space or tab-delimited. Empty lines are lines starting with '//' are ignored.
// ============================================================================= // REQUIRED // ============================================================================= // Tabix directory (includes both tabix and bgzip) TABIX_DIR /path/to/tabixdir // Directory where VAT executables are VAT_EXEC_DIR /path/to/vat_exe // ============================================================================= // OPTIONAL (required only for CGIs) // ============================================================================= // Path to processed data sets WEB_DATA_DIR /path/to/data/sets // URL to preprocessed files WEB_DATA_URL https://webserver/data/sets // Path to the web data directory where the preprocessed files are stored WEB_DATA_REFERENCE_DIR /path/to/data/reference WEB_DATA_WORKING_DIR /path/to/data/working WEB_DATA_RAW_DIR /path/to/data/raw // ============================================================================= // AWS/S3 Configuration values // ============================================================================= // Option for turning on or off Amazon Simple Storage Support (S3) support. // Use true to activate S3, false to deactivate. Note that if S3 support is // active, you will need to enter your AWS account infomation for the VAT web // components in web/lib/aws/config.inc.php AWS_USE_S3 false // S3 access key ID AWS_ACCESS_KEY_ID access_key_id // S3 secret access key AWS_SECRET_ACCESS_KEY secret_key // S3 hostname AWS_S3_HOSTNAME s3.amazonaws.com // The name of the S3 bucket for processed data sets. If S3 support is enabled, // this bucket is used instead of WEB_DATA_DIR AWS_S3_DATA_BUCKET data-bucket // The name of the S3 bucket for raw VCF input files. If S3 support is enabled, // this bucket is used instead of WEB_DATA_RAW_DIR AWS_S3_RAW_BUCKET raw-bucket // ============================================================================= // Set only if setting up as master node in master/worker configuration // ============================================================================= // Set to true if we are using the master/worker cluster configuration, false // if we are running single-node only CLUSTER false // IP address of master node. Used by worker to access the master's API MASTER_ADDRESS xxx.xx.xxx.xx // ---------------------------------------------------------------------------- // Used by master only: // ---------------------------------------------------------------------------- // MySQL configuration MASTER_MYSQL_HOST localhost MASTER_MYSQL_USER user MASTER_MYSQL_PASS pass MASTER_MYSQL_DB dbname
This file has to be configured properly by filling in the required information.
Running make install will copy the configuration file to your home directory as .vatrc
and is used when manually running VAT programs on the command line. Subsequently, the environment variable VAT_CONFIG_FILE
should be set. It is recommended that your shell start-up script sets this variable:
VAT_CONFIG_FILE=/pathTo/vat/.vatrc
A VAT configuration file also exists in the web root as vat.conf
and is expected and loaded by the VAT web application.
VAT Web Application Setup
This step is optional, but is very useful for visualizing the results of processed data sets.
Configuring PHP
Due to the large file sizes uploaded to VAT, PHP must be configured to allow larger upload sizes. In your php.ini file, set upload_max_filesize
and post_max_size
to at least 100M:
upload_max_filesize = 100M post_max_size = 100M
It is also recommended to turn off output buffering so that flush()
works properly:
output_buffering = Off
VAT Setup and Configuration
In the web directory under the VAT source tree, the VAT configuration file should have been copied into this directory during make. If it is not present, copy the VAT configuration file default.vatrc
from the root of the source tree into the web directory and rename it vat.conf
.
Copy the contents of the web directory to your Apache web root directory. This is usually /var/www/html
or /var/www
. Make the /data directory that contains directory tree used by the VAT I/O layer readable and writable:
$ sudo chmod -R 777 data
You will need to download the GENCODE annotation files used by VAT. The get_annotation_sets.sh script in the /scripts
directory under the VAT source tree may be used to download all the necessary annotation files using wget:
$ cd /web/root/data/reference $ sudo /path/to/vat-x.x.x/scripts/get_annotation_sets.sh
Edit the VAT configuration file in the web root according to your installation. If you wish to set up an Amazon S3-backed installation, create two web-accessible buckets, one for storing raw VCF files and one for storing processed data sets. In your VAT configuration file, enable S3-backed storage by setting the AWS_USE_S3
directive to true and setting your AWS credentials and bucket names:
AWS_USE_S3 true AWS_ACCESS_KEY_ID access_key_id AWS_SECRET_ACCESS_KEY secret_key AWS_S3_DATA_BUCKET data-bucket AWS_S3_RAW_BUCKET raw-bucket
The WEB_DATA_URL
directive must be set to the URL where the processed data sets are stored. If S3-backed storage is enabled, it should be set to the S3 URL of your data bucket:
WEB_DATA_URL http://s3.amazonaws.com/data-bucket
If you are setting up VAT to store all files locally, set WEB_DATA_URL
to the URL to the directory where processed data sets are stored, which is by default data/sets
:
WEB_DATA_URL http://webserver/data/sets
Regardless of whether S3-backed storage is enabled, the WEB_DATA_WORKING_DIR
directive must be set to the working directory that the I/O layer uses to give each VAT process a unique copy of files requested on demand. Also, the WEB_DATA_REFERENCE_DIR
directive must be set to the directory containing the reference GENCODE annotation files. By default the directories are data/working and data/reference respectively:
WEB_DATA_WORKING_DIR /web/root/data/working WEB_DATA_REFERENCE_DIR /web/root/data/reference
If S3-backed storage is disabled, instead of using two S3 buckets, raw VCF files and processed data sets are stored in local directories. The directives WEB_DATA_RAW_DIR
and WEB_DATA_DIR
must be set to point to the directives used to store raw VCF files and processed data sets, which are by default data/raw
and data/sets
respectively:
WEB_DATA_RAW_DIR /web/root/data/raw WEB_DATA_DIR /web/root/data/sets
Data formats
VCF
The Variant Call Format (VCF) is a tab-delimited text file format to represent a number of different genetic variants including single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and structural variants (SVs). This format was developed as part of the 1000 Genomes Project. A detailed summary of this file format can be found here. The annotation information is captured as part of the INFO field using the VA (Variant Annotation) tag. The string with the variant information has the following format:
AlleleNumber:GeneName:GeneId:Strand:Type:FractionOfTranscriptsAffected:{List of transcripts}
All annotated variant use the above format to capture information about the gene. The format describing the list of affected transcripts depends on the variant class (SNP, indel, or SV) and the variant type as shown in the table below:
Variant | Type1 | Transcript name | Transcirpt ID | Transcript length | Relative position of variant2 | Relative position of amino acid | Amino acid substitution | Transcript overlap |
---|---|---|---|---|---|---|---|---|
SNP | synonymous | Yes | Yes | Yes | Yes | Yes | Yes | No |
nonsynonymous | Yes | Yes | Yes | Yes | Yes | Yes | No | |
prematureStop | Yes | Yes | Yes | Yes | Yes | Yes | No | |
removedStop | Yes | Yes | Yes | Yes | Yes | Yes | No | |
spliceOverlap | Yes | Yes | Yes | Yes | Yes | Yes | No | |
Indel | insertionFS | Yes | Yes | Yes | Yes | Yes | Yes | No |
insertionNFS | Yes | Yes | Yes | Yes | Yes | Yes | No | |
deletionFS | Yes | Yes | Yes | Yes | Yes | Yes | No | |
deletionNFS | Yes | Yes | Yes | Yes | Yes | Yes | No | |
startOverlap | Yes | Yes | Yes | No | No | No | No | |
endOverlap | Yes | Yes | Yes | No | No | No | No | |
spliceOverlap | Yes | Yes | Yes | No | No | No | No | |
SV | svOverlap | Yes | Yes | Yes | No | No | No | Yes |
Notes:
|
The allele number refers to the numbering of the alleles. By definition, the reference allele has zero as the allele number, whereas the alternate alleles are numbered starting at one (some variants have more than one alternate alleles). The type refers to the type of variant. For SNPs, the types can take on the following values (generated by snpMapper): synonymous, nonsynonymous, prematureStop, removedStop, and spliceOverlap. For indels (generated by indelMapper), the types can take on the following values: spliceOverlap, startOverlap, endOverlap, insertionFS, insertionNFS, deletionFS, deletionNFS, where FS denotes 'frameshift' and NFS indicates 'non-frameshift'. The term spliceOverlap (for both SNPs and indels) refers to a genetic variant that overlaps with a splice site (either two nucleotides downstream of an exon or two nucleotides upstream of an exon).
Example 1
A SNP is introducing a premature stop codon. This variant affects one out of five transcripts for this gene.
chr1 23112837 . A T . PASS AA=A;AC=7;AN=118;DP=168;SF=2;VA=1:EPHB2:ENSG00000133216:+:prematureStop:1/5:EPHB2-001:ENST00000400191:3165_3055_1019_K->*
Example 2
A SNP leads to a non-synonymous substitution. This variant affects two out of four transcripts for this gene.
chr1 1110357 . G A . PASS AA=G;AC=3;AN=118;DP=203;SF=2;VA=1:TTLL10:ENSG00000162571:+:nonsynonymous:2/4:TTLL10-001:ENST00000379288:1212_1187_396_R->H:TTLL10-202:ENST00000400931:1212_1187_396_R->H
Example 3
A SNP causing a non-synonymous substitution in one transcript and a splice overlap in another transcript of the same gene.
chr9 35819390 rs2381409 C T . PASS AA=N;AC=157;AN=240;DP=49;SF=0,1;VA=1:TMEM8B:ENSG00000137103:+:nonsynonymous:1/7:TMEM8B-202:ENST00000360192:2109_166_56_P->S,1:TMEM8B:ENSG00000137103:+:spliceOverlap:1/7:TMEM8B-001:ENST00000450762:2106
Example 4
An indel with two alternate alleles. Each alternate allele leads to a non-frameshift deletion.
chr7 140118541 . TACAACAACA T,TACA . PASS HP=1;VA=1:AC006344.1:ENSG00000236914:+:deletionNFS:1/1:AC006344.1-201:ENST00000434223:66_23_8_LQQQ->L,2:AC006344.1:ENSG00000236914:+:deletionNFS:1/1:AC006344.1-201:ENST00000434223:66_23_8_LQQ->L
Notice that multiple annotation entries are comma-separated. Multiple annotation entries arise when a variant causes different types of effects on different transcripts (Example 3) or if there are multiple alternate alleles (Example 4).
VAT also enables the grouping of samples. For examples, samples can be assigned to different sub-populations or they can be designated as cases or controls. This is done by modifying the header line using vcfModifyHeader. Specifically, the sample is prefixed by group identifier using the ':' character as a delimiter.
Interval
The Interval format consists of eight tab-delimited columns and is used to represent genomic intervals such as genes. This format is closely associated with the intervalFind module, which is part of libBIOS. This module efficiently finds intervals that overlap with a query interval. The underlying algorithm is based on containment sublists: Alekseyenko, A.V., Lee, C.J. "Nested Containment List (NCList): A new algorithm for accelerating interval query of genome alignment and interval databases" Bioinformatics 2007;23:1386-1393 [1]
- Name of the interval
- Chromosome
- Strand
- Interval start (with respect to the "+")
- Interval end (with respect to the "+")
- Number of sub-intervals
- Sub-interval starts (with respect to the "+", comma-delimited)
- Sub-interval end (with respect to the "+", comma-delimited)
Note: For the purpose of VAT, the name field in the Interval file must contain four pieces of information delimited by the '|' symbol (geneId|transcriptId|geneName|transcriptName). Using the gencode2interval program ensures proper formatting.
Example file:
ENSG00000008513|ENST00000319914|ST3GAL1|ST3GAL1-201 chr8 - 134472009 134488267 6 134472009,134474117,134475656,134477020,134478136,134487961 134472180,134474237,134475702,134477200,134478333,134488267 ENSG00000008513|ENST00000395320|ST3GAL1|ST3GAL1-202 chr8 - 134472009 134488267 6 134472009,134474117,134475656,134477020,134478136,134487961 134472180,134474237,134475702,134477200,134478333,134488267 ENSG00000008513|ENST00000399640|ST3GAL1|ST3GAL1-203 chr8 - 134472009 134488267 6 134472009,134474117,134475656,134477020,134478136,134487961 134472180,134474237,134475702,134477200,134478333,134488267 ENSG00000008516|ENST00000325800|MMP25|MMP25-201 chr16 + 3097544 3105947 4 3097544,3100009,3100254,3105830 3097548,3100145,3100546,3105947 ENSG00000008516|ENST00000336577|MMP25|MMP25-202 chr16 + 3096918 3109096 10 3096918,3097415,3100009,3100254,3107033,3107310,3107531,3108181,3108412,3108827 3097017,3097548,3100145,3100547,3107210,3107395,3107614,3108334,3108670,3109096
List of programs
VAT Core Modules
snpMapper
snpMapper is a program to annotate a set of SNPs in VCF format. The program determines the effect of a SNP on the coding potential (synonymous, nonsynonymous, prematureStop, removedStop, spliceOverlap) of each transcript of a gene.
Usage
snpMapper <annotation.interval> <annotation.fa>
Inputs | Takes a VCF input from STDIN |
---|---|
Outputs | Outputs annotated SNPs in VCF format. The annotation information is captured as part of the INFO field. For details refer to the VCF format specification. |
Required arguments |
|
Optional Arguments | None |
indelMapper
indelMapper is a program to annotate a set of indels in VCF format. The program determines the effect of an indel on the coding potential (frameshift insertion, non-frameshift insertion, frameshift deletion, non-frameshift deletion, spliceOverlap, startOverlap, endOverlap) of each transcript of a gene.
Usage
indelMapper <annotation.interval> <annotation.fa>
Inputs | Takes a VCF input from STDIN |
---|---|
Outputs | Outputs annotated indels in VCF format. The annotation information is captured as part of the INFO field. For details refer to the VCF format specification. |
Required arguments |
|
Optional Arguments | None. |
svMapper
svMapper is a program to annotate a set of SVs in VCF format. The program determines if a SV overlaps with different transcript isoforms of a gene.
Usage
svMapper <annotation.interval>
Inputs | Takes a VCF input from STDIN |
---|---|
Outputs | Outputs annotated SVs in VCF format. The annotation information is captured as part of the INFO field. For details refer to the VCF format specification. |
Required arguments |
|
Optional Arguments | None. |
genericMapper
genericMapper is a program to annotate a number of different variants in VCF format. The program checks whether a variant overlaps with entries in the specified annotation set (it does not determine the effect on the coding potential).
Usage
genericMapper <annotation.interval> <nameFeature>
Inputs | Takes a VCF input from STDIN |
---|---|
Outputs | Outputs the annotated variants in VCF format. The annotation information is captured as part of the INFO field. |
Required arguments |
|
Optional arguments | None. |
vcfSummary
vcfSummary is a program to aggregate annotated variants across genes and samples.
Usage
vcfSummary <file.vcf.gz> <annotation.interval>
Inputs | None |
---|---|
Outputs | Generates two output files. The first file, named file.geneSummary.txt , contains the number of variants categorized by type for each gene. A second file, named file.sampleSummary.txt , summarizes number of variants categorized by type for each sample. |
Required arguments |
|
Optional arguments | None. |
vcfImages
vcf2images is a program to generate an image for each gene to visualize effect of the annotated variants.
Usage
vcf2images <file.vcf.gz> <annotation.interval> <outputDir>
Inputs | None. |
---|---|
Outputs | Generates an image in PNG format for each gene that has at least one annotated variant. |
Required arguments |
|
Optional Arguments | None. |
vcfSubsetByGene
vcfSubsetByGene is a program to subset a VCF file with annotated variants by gene.
Usage
vcfSubsetByGene <file.vcf.gz> <annotation.interval> <outputDir>
Inputs | None. |
---|---|
Outputs | Generates a VCF file for each gene that has at least one annotated variant. |
Required arguments |
|
Optional Arguments | None. |
vcfModifyHeader
vcfModifyHeader is a program to modify the header line (part of the meta-lines) in a VCF file. Specifically, it assigns each sample to a group or population (these assignments are used by other programs including vcfSummary).
vcfModifyHeader <oldHeader.vcf> <groups.txt>
Inputs | None. |
---|---|
Outputs | Generates a VCF header file. |
Required arguments |
|
Optional arguments | None. |
Auxiliary programs
gencode2interval
gencode2interval converts a GENCODE annotation file (in GTF format) to the Interval format.
Usage
gencode2interval
Inputs | Takes a GENCODE annotation file in GTF format from STDIN |
---|---|
Outputs | Outputs the GENCODE annotation file in Interval format to STDOUT |
Required arguments | None. |
Optional arguments | None. |
Note: Remove all header lines in the annotation file before running gencode2interval. Also filter out coding transcripts that do not have an annotated start or stop as follows: grep -v '^#' gencode.v19.annotation.gtf | awk '/\t(HAVANA|ENSEMBL)\t(CDS|start_codon|stop_codon)\t/ {print}' | grep -v mRNA_end_NF | grep -v mRNA_start_NF > gencode.v19.annotation.filtered.gtf |
interval2sequences
Module to retrieve genomic/exonic sequences for an annotation set in Interval format.
Usage
interval2sequences <file.2bit> <file.annotation> <exonic|genomic>
Inputs | None. |
---|---|
Outputs | Reports the extracted sequences in FASTA format |
Required arguments |
|
Optional arguments | None. |
Note: You will want to cd into a directory where you have write permission since interval2sequences may create temporary files |
External programs
bgzip/tabix
Tabix is generic tool that indexes position-sorted files in tab-delimited formats to facilitate fast retrieval. This tool was developed by Heng Li. For more information consult the tabix documentation page.
VCF tools
VCF tools consists of a suite of very useful modules to manipulate VCF files. For more information consult the documentation page.
Example workflow
This workflow shows how the 1000 Genomes Project, Phase I, chr22, SNP calls data set was processed.
Prerequisites
Download the GENCODE annotation set (version 3c, hg19):
$ wget ftp://ftp.sanger.ac.uk/pub/gencode/release_3c/gencode.v3c.annotation.GRCh37.gtf.gz
Download the human genome (hg19) in 2bit format. This is used by interval2sequences to extract the genomic sequences for the entries specified in the annotation set:
$ wget http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.2bit
Download the SNP files in VCF format and a third file that assigns each sample to a population:
$ wget ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/20100804/ALL.2of4intersection.20100804.genotypes.vcf.gz $ wget ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/20100804/ALL.2of4intersection.20100804.genotypes.vcf.gz.tbi $ wget ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/20100804/20100804.ALL.panel
Extract variants on chromosome 22:
$ tabix -h ALL.2of4intersection.20100804.genotypes.vcf.gz 22 | bgzip -c > ALL.2of4intersection.20100804.chr22.genotypes.vcf.gz
Preprocessing of the annotation file
Decompress the annotation file:
$ gunzip gencode.v3c.annotation.GRCh37.gtf.gz
Extract the coding sequence (CDS) elements ignoring mRNA_start_NF
and mRNA_end_NF
:
grep -v '^#' gencode.v3c.annotation.GRCh37.gtf | awk '/\t(HAVANA|ENSEMBL)\t(CDS|start_codon|stop_codon)\t/ {print}' | grep -v mRNA_end_NF | grep -v mRNA_start_NF > gencode.v3c.annotation.GRCh37.filtered.gtf
Convert the GENCODE GTF file into Interval format:
$ gencode2interval < gencode.v3c.annotation.GRCh37.filtered.gtf > gencode.v3c.annotation.GRCh37.filtered.interval
Retrieve the genomic sequences for the transcripts specified in the annotation file.
$ interval2sequences hg19.2bit gencode.v3c.annotation.GRCh37.filtered.interval exonic > gencode.v3c.annotation.GRCh37.filtered.fa
Annotation of the SNPs
Annotate the variants using snpMapper
$ zcat ALL.2of4intersection.20100804.chr22.genotypes.vcf.gz | snpMapper gencode.v3c.annotation.GRCh37.cds.gtpc.ttpc.interval gencode.v3c.annotation.GRCh37.cds.gtpc.ttpc.fa > ALL.2of4intersection.20100804.chr22.genotypes.annotated.vcf
Modification the VCF header line
Modify the VCF header line to assign individual samples to populations (groups). This is done by using the following syntax: group:sample
(i.e. CEU:NA0705
).
First get the old meta-data lines:
$ grep "#" ALL.2of4intersection.20100804.chr22.genotypes.annotated.vcf > ALL.2of4intersection.20100804.chr22.genotypes.annotated.oldHeader.vcf
Store the annotated variants in a separate file:
$ grep "#" -v ALL.2of4intersection.20100804.chr22.genotypes.annotated.vcf > ALL.2of4intersection.20100804.chr22.genotypes.annotated.variants.vcf
Create the new meta-data lines:
$ vcfModifyHeader ALL.2of4intersection.20100804.chr22.genotypes.annotated.oldHeader.vcf 20100804.ALL.panel > ALL.2of4intersection.20100804.chr22.genotypes.annotated.newHeader.vcf
Merge the new meta-data lines with the annotated variants and create a new file called ALL.2of4intersection.20100804.chr22.vcf
:
$ cat ALL.2of4intersection.20100804.chr22.genotypes.annotated.newHeader.vcf ALL.2of4intersection.20100804.chr22.genotypes.annotated.variants.vcf > ALL.2of4intersection.20100804.chr22.vcf
Compress the newly created VCF file with the annotated variants:
$ bgzip ALL.2of4intersection.20100804.chr22.vcf
Index the newly created VCF file with the annotated variants:
$ tabix -p vcf ALL.2of4intersection.20100804.chr22.vcf.gz
Generation of summaries and images
Generate gene and sample summaries for the annotated variants
$ vcfSummary ALL.2of4intersection.20100804.chr22.vcf.gz gencode.v3c.annotation.GRCh37.cds.gtpc.ttpc.interval
Resulting files should be: ALL.2of4intersection.20100804.chr22.geneSummary.txt
and ALL.2of4intersection.20100804.chr22.sampleSummary.txt
Make a new directory to store the images and VCF files for each gene.
$ mkdir ALL.2of4intersection.20100804.chr22
Generate an image for each gene with at least one annotated variant.
$ vcf2images ALL.2of4intersection.20100804.chr22.vcf.gz gencode.v3c.annotation.GRCh37.cds.gtpc.ttpc.interval ./ALL.2of4intersection.20100804.chr22
Subset the VCF file with the annotated variants by gene.
$ vcfSubsetByGene ALL.2of4intersection.20100804.chr22.vcf.gz gencode.v3c.annotation.GRCh37.cds.gtpc.ttpc.interval ./ALL.2of4intersection.20100804.chr22
Setting up the web server
Make a gzipped tarball containing all of the relevant files:
- Directory with the images and the VCF files for each gene (ALL.2of4intersection.20100804.chr22)
- File with the gene summary (ALL.2of4intersection.20100804.chr22.geneSummary.txt)
- File with the sample summary (ALL.2of4intersection.20100804.chr22.sampleSummary.txt)
- Compressed VCF file with the annotated variants (ALL.2of4intersection.20100804.chr22.vcf.gz)
- Index file of the annotated variants (ALL.2of4intersection.20100804.chr22.vcf.gz.tbi)
$ tar -pczvf ALL.2of4intersection.20100804.chr22.tar.gz \ ALL.2of4intersection.20100804.chr22 \ ALL.2of4intersection.20100804.chr22.geneSummary.txt \ ALL.2of4intersection.20100804.chr22.sampleSummary.txt \ ALL.2of4intersection.20100804.chr22.vcf.gz \ ALL.2of4intersection.20100804.chr22.vcf.gz.tbi
Open the upload page of your VAT installation in your web browser and click on the ÒProcessed data setÓ tab for the upload form for uploading processed data sets. Choose your .tar.gz archive using the file input box and click Submit. Once the file has been processed, click View Results.