over the past few years , the throughput of the next generation sequencing ( ngs ) technologies have been exponentially increased to a massive scale , greatly changing the face of genomic research and making post - sequencing data analysis tremendously difficult . this technology improvement calls for powerful and handy bioinformatics tools that can process with high performance the ngs data , such as genomic variants , as well as satisfy analysis features to facilitate research . many genomic variants annotation online tools published ( 14 ) or not published like seattleseq annotation ( http://snp.gs.washington.edu/seattleseqannotation134/ ) and offline tools ( 58 ) are available , but variowatch is unique in its ability to annotate comprehensively and efficiently millions of variants online , immediately delivering the results in real time , plus visualizes up to 1000 annotated variants . based on genowatch ( 9 ) , serving since 2006 and published in the 2008 web server issue , variowatch was developed with the aim to offer the research community extremely efficient online annotation service of human genomic variants in the ngs era . regarding speed , the superseded genowatch relied on web robots to retrieve data from many public domain websites , such as ncbi ( 1012 ) , uniprot ( 13 ) , kegg ( 14 ) and go ( 15 ) , to annotate bulks of variants . it always provided the up - to - date annotations , and this strategy was sufficient before ngs prevailed . due to slow responses from the source websites , genowatch failed to cope with massive online annotation . to solve the problem , we changed our approach by replacing the idea of always providing the most up - to - date information from the internet with the idea of providing information from frequently updated local databases . by constructing local databases , we increased the annotating speed to at least 10  000-times faster and kept data integrity better by completely avoiding source information retrieval through internet connection and the instability of external web sites . now that the system is re - structured , re - programmed and fine - tuned , millions of variants can be analyzed and downloaded in minutes , if not seconds , in csv format with megaquery , and up to 1000 variants can be easily visualized and browsed . in addition , we provided filters in megaquery to help users narrow down candidate variants and expedite their research . on top of speed increase , variowatch also offers more comprehensive analysis . in contrast to genowatch annotating only known snps , variowatch analyzes both known snps and novel variants . by incorporating features similar to fans ( 16 ) , variowatch investigates a novel variant with its genomic context , analyzes the functional effect if it is located in a protein coding region or in a gt - ag splice site , presents information of genes nearby , checks affection to ese and ess hexamers pattern [ from rescue - ese ( 17 ) and fas - ess ( 18 ) ] if the variant is in an exon , and predicts risk of the variant based on the above - mentioned information . if the variant is reported in dbsnp or 1000 genomes project ( 19 ) , related details will be listed as well . creating an annotation database for variowatch not only improves the system performance , but also enables variowatch to serve more than one reference version at the same time . variowatch currently provides annotations of two popular human genome reference versions ( ncbi build 36.3 , ncbi build 37.2 ) , including gene annotation , pre - computed variation risks , known variants from dbsnp , 1000 genomes project ( released on october 2011 ) , omim ( 20 ) and other minor variant databases ( see supplementary data ) . users can easily query and visualize up to 1000 regions by chromosome positions , markers , gene symbols , a batch file input , etc . for instance , they can use a physical position , a single marker ( e.g. snp ) , plus downstream and upstream spans , to define a chromosome region like in genowatch . variowatch also supports sequence upload , finding all variants on the uploaded sequence by blat ( 21 ) and then annotating them automatically . by incorporating human variation data sets , such as omim it first translates the input disease name into a group of relevant genes then shows all annotations of these genes as well as variants within . ( a ) an example to retrieve and visualize genomic annotations on gene apoe plus 5000 bases upstream and downstream . ( b ) megaquery download is capable of taking a massive amount of variants as input , labeling them with genomic annotations , filtering out unwanted records and returning with purified annotation results . ( a ) an example to retrieve and visualize genomic annotations on gene apoe plus 5000 bases upstream and downstream . ( b ) megaquery download is capable of taking a massive amount of variants as input , labeling them with genomic annotations , filtering out unwanted records and returning with purified annotation results . furthermore , variowatch has a special unit called megaquery ( figure 1b ) dedicated to annotating millions of variants generated by ngs . megaquery currently supports batch queries for both single nucleotide substitution and in / del variants . result files , e.g. snp.txt or indel.txt from illumina casava variant detection outcome or vcf format , can also be directly uploaded through megaquery to process . often , instead of examining all the variants identified by ngs , researchers only want to examine those which satisfy their research needs . before , upon receiving variant annotation data , they either looked for further help from an it specialist or turned to a computer - based spreadsheet , doing tedious work to achieve this goal . to address this issue , megaquery provides four handy filters to help researchers listing variants with functional impacts , with predicted risk above a certain threshold , in specific gene region or variants not reported in either dbsnp or 1000 genome project . the results page is comprised of genome view , gene view , transcript view and variation view . genome view and gene view genome view ( figure 2a ) displays an overview of input markers plus their nearby genes . if a marker is a variant with risky functional impact , it is coloured according to the risk level . clicking on a marker leads to gene view ( figure 2b ) , showing structured genes and their corresponding annotations , including gene functions , tissue - specificity , diseases and so on . instead of showing only snp annotations like in genowatch , variowatch also lists disease - associated mutations and reveals the relation between query variants and these known mutations in this view . transcript view ( figure 2c ) presents transcript structure , the functional impacts of the same variant on different transcript isoforms and the distribution of known variants within . the top area tabulates detailed variant information including its location , allele change , gene i d and gene symbol if the variant sits in a gene , cdna change if the variant causes transcript change , protein and codon change if the variant falls in a translated region , estimated risk level , snp information if the variant is a snp , related disease and literature reference . the middle area graphs a risk - level decision tree and a highlighted path to show how the risk level of the variant is decided . users can click on the path steps to obtain detailed reasons and references to data sources . what s more , at the upper right corner of the area are links for users to download the variant - containing sequence and design primers for that variant . finally , at the bottom area , information of population diversity extracted from 1000 genomes project and hapmap ( 22 ) is clearly presented . ( a ) genome view provides a bird's - eye - view of the query result on the genome scale . it shows the distribution of the query items on the whole genome , and colours each item according to the risk level analyzed based on the annotation results . ( b ) gene view displays each query item in the context of genes and mutations known to cause diseases . in addition to providing a diagram representation of gene structures , including introns and exons , it also annotates each gene within the view - port with known functions , tissue specificity , ontology , pathway involved and disease caused . since one variant may have different effects on different transcript isoforms , this view provides a precise genomic context in which the query item is analyzed . transcript view also depicts known snps within the specified transcript along with disease - relevant mutations . ( d ) variation view shows the annotation details of a query item , the decision tree of risk evaluation , and the relevant allele frequencies in different human races . ( a ) genome view provides a bird's - eye - view of the query result on the genome scale . it shows the distribution of the query items on the whole genome , and colours each item according to the risk level analyzed based on the annotation results . ( b ) gene view displays each query item in the context of genes and mutations known to cause diseases . in addition to providing a diagram representation of gene structures , including introns and exons , it also annotates each gene within the view - port with known functions , tissue specificity , ontology , pathway involved and disease caused . since one variant may have different effects on different transcript isoforms , this view provides a precise genomic context in which the query item is analyzed . transcript view also depicts known snps within the specified transcript along with disease - relevant mutations . ( d ) variation view shows the annotation details of a query item , the decision tree of risk evaluation , and the relevant allele frequencies in different human races . the results downloaded through megaquery are a zip file containing three reports : snv / indel variation annotation , 1000 genome allele frequency and gene annotation ( figure 3 ) . the three csv - formatted reports have the same contents as a results page minus the visualization part and reference literature . users can visualize any individual variant by clicking the url provided in the last column of the snv / indel variant annotation report . also , users can further manipulate these files with any application that supports csv file format . figure 3.megaquery download responds a query with one zip file containing three different reports : snv / indel variation annotation , 1000 genome allele frequency and gene annotation . snv variation annotation provides a text - based annotation and risk analysis result of each query item in csv format , while the other two auxiliary reports provide relevant allele frequencies and the information of containing genes . megaquery download responds a query with one zip file containing three different reports : snv / indel variation annotation , 1000 genome allele frequency and gene annotation . snv variation annotation provides a text - based annotation and risk analysis result of each query item in csv format , while the other two auxiliary reports provide relevant allele frequencies and the information of containing genes . variowatch is written in java programming language with struts framework and jdbc technology . to further improve user experience , this makes it easier for users to define a genomic region in query page and to browse the classified result page . for variowatch database construction , we built a script that mirrors all needed source data files from public domain ftp sites . once each data source is verified to be consistent with their reference version , a pipe - line system will be involved to process these data into databases . in addition , a simple computer cluster system is built for hosting sift non - synonymous variants prediction tool ( 23 ) . combining these pre - computed and stored results , each variant generated from all possible substitution bases in coding regions and gt - ag splice sites variowatch provides an easy way for researchers to directly and quickly annotate a large number of human genomic variants online without having to run an offline annotating application or needing help from an it specialist . the input interface is intuitive and the returning outcome is displayed in a carefully designed results page . its reliability , availability and serviceability are much better than genowatch because of database localization . variowatch should be able to help researchers facilitate their work substantially in variant annotation and prioritization in the ngs era . supplementary data are available at nar online : supplementary table 1 and supplementary references [ 2426 ] . academia sinica life sciences [ 40 - 05-gmm ] ; national science council , taiwan , r.o.c . [ nsc100 - 2319-b-001 - 001 ] ; national center for genomic medicine . funding for open access charge :
variowatch ( http://genepipe.ncgm.sinica.edu.tw/variowatch/ ) has been vastly improved since its former publication genowatch in the 2008 web server issue . 
 it is now at least 10  000-times faster in annotating a variant . 
 drastic speed increase , through complete re - design of its working mechanism , makes variowatch capable of annotating millions of human genomic variants generated from next generation sequencing in minutes , if not seconds . 
 while using megaquery of variowatch to quickly annotate variants , users can apply various filters to retrieve a subgroup of variants according to the risk levels , interested regions , etc . 
 that satisfy users requirements . 
 in addition to performance leap , many new features have also been added , such as annotation on novel variants , functional analyses on splice sites and in / dels , detailed variant information in tabulated form , plus a risk level decision tree regarding the analyzed variant . 
 up to 1000 target variants can be visualized with our carefully designed genome view , gene view , transcript view and variation view . 
 two commonly used reference versions , ncbi build 36.3 and ncbi build 37.2 , are supported . 
 variowatch is unique in its ability to annotate comprehensively and efficiently millions of variants online , immediately delivering the results in real time , plus visualizes up to 1000 annotated variants .