nowadays , next - generation sequencing ( ngs ) technologies allow the generation of sequence data on an unprecedented scale . the versatility of ngs - based techniques together with the remarkable reduction in per - base sequencing cost , have encouraged researchers to produce a growing number of dna resequencing studies . the 1000 genomes project leads this trend and represents a notable effort to understand the human variation at a genome - wide scale ( 1 ) . the goal is to report a comprehensive catalogue of dna variants corresponding to a number of human populations , expanding the concept of reference human genome from the current haploid and mosaic sequence to a frequency - based model built from population - specific variants . along the same lines , the detection of novel dna variants is also an objective for the international cancer genome consortium [ icgc ( http://www.icgc.org ) ] . this project is currently resequencing more than 50 types of cancer providing new collections of tumour - associated genomic mutations with the aim of relating them to the oncogenic processes , tumour evolution and clinical prognosis ( 2 ) . the new catalogues of single nucleotide polymorphism ( snps ) and mutations generated by resequencing studies are usually stored in genome position files . basically , genome position files ( gpfs ) consist of tab - delimited text files containing information regarding the base reported by the ngs experiment , defined by chromosome name and genomic coordinates . several standard formats have been recently proposed to organize the information contained in gpfs , such as the variant call format ( .vcf ) adopted by the 1000 genomes project ( http://www.1000genomes.org/wiki/analysis/variant%20call%20format/vcf-variant-call-format-version-40 ) , and the .pileup format ( 3 ) . in such a situation , gpfs analysis becomes a critical task for a deeper understanding of the genome and its relation to human diseases . however , given that gpfs usually include large lists of genomic positions , their handling is cumbersome . this situation calls for efficient , practical and intuitive tools to explore , analyse , visualize and annotate dna variants . to this end , some authors have recently introduced novel , free and useful applications to deal with standard gpfs . for instance , the annotate variation ( annovar ) toolbox ( 4 ) is a collection of perl scripts to functionally annotate dna variants detected at gene ( or region ) level . among other things , the software can handle several gpfs standard formats and provides tools to estimate the biological impact of dna variants ( i.e. retrieve non - synonymous mutations ) from pre - computed sorting intolerant from tolerant ( sift ) scores ( 5 ) . nevertheless , annovar does not implement a genome browser able to explore variants along with the reference genome and its command - line nature could be too difficult for biomedical researchers without computing skills . eagleview ( 6 ) , tablet ( 7 ) , savant ( 8) , igv ( 9 ) , artemis ( 10 ) and magicviewer ( 11 ) offer friendly guis together with powerful genomic browsers for visualization of genetic variation and its associated annotation . nonetheless , common tasks in biomedical studies such as variant pairwise comparisons ( i.e. case versus control ) or variant comparisons across n gpfs are not supported by these applications . in addition , they do not provide specific support to generate inputs for third - party programs with the goal of predicting the biological impact of dna variants . in this context , here we introduce pilelinegui , a novel desktop application specifically intended for effectively handling and browsing gpfs generated in dna - seq experiments . pilelinegui is open software , multi - platform and designed to be intuitively used by biomedical researchers . the application includes all the core functionalities implemented in the pileline command - line toolbox ( 12 ) and a new interactive genome browser to explore dna variants . pilelinegui implements a number of operations for filtering , searching , annotating and analysing dna variants , with specific support for generating out - files that can be subsequently used by third - party software such as sift ( 5 ) , polyphen2 ( 13 ) and firestar ( 14 ) specialized in prediction of biological impact of dna variants . pilelinegui supports pair - wise comparisons versus the reference and is able to generate four different types of specific variants lists : ( i ) variants in case , but not in control , ( ii ) variants in control , but not in the case , ( iii ) common variants in both case and control and ( iv ) discrepant variants in both case and control . it also allows comparisons across n gpfs at genomic coordinate or whole - gene level . this functionality may be of particular interest to detect a common mutation ( or snp ) across several individuals sharing a particular phenotype . pilelinegui supports variant cell format ( vcf ) , samtools pileup , gff and bed standard files , together with the fasta format used by the genome browser for reference genome visualization . the software reads and visualizes inputs in .pileup and .vcf for single - nucleotide files ( each line contains information for a single genome position ) , as well as .bed and .gff for intervals files ( each line defines a continuous interval in the genome , i.e. a gene ) . moreover , input gp files can be also bgzf - compressed in order to alleviate the disk requirements while keeping the possibility to manage them efficiently . the built - in genome browser works with the standard samtools indexed fasta files ( .fai ) and currently supports all previous gp files for tracks , including their compressed form . pilelinegui allows the user to load and browse gp files via a user - friendly interface that can be used to instantly search for a given range within a sequence . standard gp files may be easily explored and analysed using this tool . in this example , the output of the nsmc functionality is shown . note that the second row corresponds to a variant consistently detected in cases , but not in controls . standard gp files may be easily explored and analysed using this tool . in this example , the output of the nsmc functionality is shown . note that the second row corresponds to a variant consistently detected in cases , but not in controls . two single - nucleotide gp files ( a and b ) can be joined together in order to match the information associated to the same genomic position in both a and b. moreover , the join function allows the user to include unmatched lines of a ( left outer join ) or b ( right outer join ) . if the user is only interested in specific intervals of a given gp file ( e.g. genes , dbsnp , custom targets , etc . ) , a single - nucleotide gp file can be filtered using the intervals specified in an intervals gp file . inverse filters , for example , to filter - out all entries , which are known snps in dbsnp . similarly to the filter function , the user can annotate each position in any gp file using an intervals file . pilelinegui includes two additional modules to find somatic mutations . working with samtools pileup files , the two samples somatic mutations calling ( 2smc ) function compares two samples ( a and b ) of an individual ( e.g. healthy against tumour sample ) . each sample is defined by ( i ) a variants - only file and ( ii ) a complete sequencing file ( including non - variant positions ) . the 2smc operation generates 4 gp files as output , including ( i ) variants found in a , which were sequenced as non - variants in b , ( ii ) variants found in b , which were sequenced as non - variants in a , ( iii ) variants found in a and b and ( iv ) variants found in a and b , but with a discrepant genotype . for example , if a represents a tumour sample and b a healthy one from the same individual , variants found only in a are candidates for being considered as somatic mutations ( not present in the germ line ) . in addition , the n samples somatic mutation calling ( nsmc ) function allows the user to assess the reproducibility of several 2smc experiments . for example , if we have several samples , we could first extract the non germ - line mutations with 2smc and then use nsmc to check , in which samples each mutation is found . further , if we have two groups of samples ( e.g. the tumour samples plus a control group ) , nsmc provides a fisher s exact test over each mutation in order to arrive at the significance of the reproducibility . furthermore , nsmc can also compare samples at the single - nucleotide level or using genomic intervals ( e.g. gene or exon level ) . in this sense , it is sometimes more interesting to see whether tumour samples contain mutations in several genes of interest , regardless of their exact positions . finally , a pileup file containing a list of candidate somatic mutations can be exported to several mutation consequence assessment packages like sift , polyphen and firestar . pilelinegui incorporates a powerful genome browser for gp files including multiple track support , fully interactive zoom and image export facilities . the browser loads a genome via a standard samtools fasta index ( .fai ) and allows the user to add several gp files as individual tracks . single - nucleotide gp files ( .pileup and .vcf ) are rendered in the genome by displaying the value of a custom column at the corresponding genome position . moreover , pileup files can be dynamically filtered by depth , snp quality and consensus quality . if the zoom level is low ( showing a very large range of bases ) , the browser plots a configurable histogram to see the distribution of occurrences in the gp file . if there are overlapping segments , they are plotted at different heights in the track . figure 2.pilelinegui browser interface has been designed to be customizable and includes multiple track support . in this example , the first track ( in blue ) represents the sequencing depth along a genomic region in chromosome 10 . since data correspond to a full - exome experiment , depth peaks match to exon positions depicted in the second track ( green ) . the third track ( black ) pilelinegui browser interface has been designed to be customizable and includes multiple track support . in this example , the first track ( in blue ) represents the sequencing depth along a genomic region in chromosome 10 . since data correspond to a full - exome experiment , depth peaks match to exon positions depicted in the second track ( green ) . the third track ( black ) shows four ensembl genes located in this particular genomic region . pilelinegui is implemented using the java programming language on top of the pileline tools ( 14 ) , which can be seen as the command - line version of this software . the graphical user interface of pilelinegui was developed using the aibench application framework ( 15 ) . the compatibility with samtools bgzf compressed files was included in pileline by using the java ports provided by the samtools project ( http://picard.sourceforge.net/ , http://samtools.sourceforge.net/tabix.shtml ) . in addition , pilelinegui implements a new genome browser as a separate plugin to facilitate its later inclusion and reuse in other projects . moreover , this component was carefully designed in order to add full support to other types of tracks ( e.g. a bam track including aligned reads is also planned ) . gpfs analyses are critical for a deeper understanding of the genome and its relation to human diseases . however , given that gpfs usually include large lists of genomic positions , they are often difficult to handle systematically by researchers . this situation calls for efficient , practical and intuitive tools to explore , analyse , visualize and annotate dna variants . here , we present pilelinegui , a desktop application to efficiently handle , browse and analyse genome position files focusing on somatic mutation finding . by also including a new interactive genome browser , this tool is useful for wet - lab users demanding fast and easy - to - use local applications able to analyze huge amounts of data coming from next - generation sequencing studies . further work aims at ( i ) extending the somatic mutation calling functions ( 2smc and nsmc ) to handle vcf files , since the samtools pileup format is now deprecated and ( ii ) include more standard file formats to the genome browser , such as bam . pilelinegui is licensed under the terms of lgplv3 ( gnu lesser general public license , version 3 ) and it is available at : http://sing.ei.uvigo.es/pileline/pilelinegui.html . spanish ministry of science and innovation , the plan e from the spanish government and the european union from the erdf ( tin2009 - 14057-c03 - 02 ) ; university of vigo ( to m.r .- j . , pre - doctoral fellowship ) . funding for open access charge : spanish ministry of science and innovation , the plan e from the spanish government and the european union from the erdf ( tin2009 - 14057-c03 - 02 ) .
next - generation sequencing ( ngs ) technologies are making sequence data available on an unprecedented scale . in this context 
 , new catalogs of single nucleotide polymorphism and mutations generated by resequencing studies are usually stored in genome position files ( e.g. variant call format , samtools pileup , bed , gff ) comprising of large lists of genomic positions , which are difficult to handle by researchers . here , we present pilelinegui , a novel desktop application primarily designed for manipulating , browsing and analysing genome position files ( gpf ) , with specific support to somatic mutation finding studies . 
 the developed tool also integrates a new genome browser module specially designed for inspecting gpfs . 
 pilelinegui is free , multiplatform and designed to be intuitively used by biomedical researchers . 
 pilelinegui is available at : http://sing.ei.uvigo.es/pileline/pilelinegui.html .