next - generation dna sequencing ( ngs ) has revolutionized genetics by enabling researchers to routinely sequence genomes , either in their entirety or specific subsets [ 1 - 3 ] .
for example , exome resequencing , in which researchers enrich for all annotated and putative exons and then sequence the genomic targets , has been widely adopted .
exome sequencing has become a popular approach owing to the availability of commercial exome enrichment assays , the generally lower cost than whole - genome sequencing and the focus on coding regions and associated variants that have a direct impact on coding sequence and thus gene function . as a result , a large number of studies are using human exome resequencing to study the genetic diversity of human populations .
furthermore , exome resequencing is frequently used in the study of human diseases , including mendelian disorders and cancer .
given the accessibility of the technology , many groups are working towards potential clinical diagnostic applications in personalized medicine .
analysis has become one of the primary challenges for ngs users , as a direct result of the sheer volume of sequencing data currently being generated .
exome sequence analysis can be generally summarized as a two step process with alignment of the data to a human genome reference followed by subsequent genetic variant calling from the post - alignment data , or , more simply , the identification of specific sequence alterations that are polymorphisms , rare variants or mutations .
exome - targeted resequencing analysis is particularly useful for the discovery of single nucleotide variants ( snvs ) and insertion or deletions ( indels ) .
although a variety of robust and now widely adopted sequence alignment tools are available , the challenge of variant calling from aligned data remains .
although alignment algorithms can be used to accurately determine the location of any sequence , it is more problematic to determine whether a variation that is identified in an aligned sequence is a true genetic variation .
numerous academic and commercial groups have developed a variety of bioinformatic tools or cloud - based solutions to facilitate variant calling .
for example , samtools   and the genome analysis tool kit ( gatk )   provide snv and indel calling and are widely used .
however , experienced bioinformaticians and information technology specialists are required to implement these and other popular tools , limiting accessibility of variant calling for the research community and in clinical diagnostic laboratories . in addition , the accuracy of variant calling bioinformatic tools is highly variable .
improving the speed , accuracy and user - friendliness of sophisticated variant calling pipelines is an important step towards personalized medicine . seeking to address this challenge , fuli yu and colleagues from the baylor genome center recently published in bmc bioinformatics a variant - calling software package , the atlas2 suite , that can analyze aligned data generated from a variety of ngs platforms , including life sciences ' solid , roche 's 454 and illumina 's genome analyzer and hiseq systems .
i focus on application of the atlas2 suite and its optimization for exome sequence analysis .
atlas2 relies on the standard binary sequence alignment / mapping format ( bam ) sequence format , which is a widely adopted and generally supported format among ngs users .
for example , this format is used for cancer exome data from the national institutes of health 's repertoire of sequencing production studies such as the cancer genome atlas .
variant calls are produced using the variant call format ( vcf ) , which has been adopted by the 1000 genomes project .
atlas2 runs on many different computing platforms , from the standard desktop computer to highly scaled implementation with multimode computational clusters .
the group also implemented atlas2 on the genboree workbench , a genomic web resource that enables the user to view ngs data and carry out analysis .
web - driven analysis tools are increasingly popular , as seen with galaxy   and dnanexus . given that most clinical diagnostic centers do not have a dedicated bioinformatics staff , the desktop computer and web implementation aspects have particular appeal for a diagnostic laboratory setting .
challis et al .   used a trained logistic regression model to assess the quality of each potential variant as a true variant rather than a sequencing , mapping , or alignment error .
critical factors that they assessed include the following : ratio of the variant base to the reference sequence , the overall sequencing depth , the quality scores of the base calls , and the position in the read and strand direction based on whether it is the forward or reverse sequence .
these factors are well known to be important in determining the accuracy of variant calls and , not surprisingly , were the most significant in the authors ' statistical analysis .
ultimately , these variables were an important component of the statistical model driving the atlas2 variant calling algorithm .
one of the challenges faced by any ngs variant caller is the introduction of false positive and false negative snvs and indel calls .
all variant callers and their related publications typically report the overall sensitivity , specificity and false discovery rates of variants called from a control genome .
atlas2 was compared with two other popular variant callers , gatk and samtools , using sequence data from the 1000 genomes project .
for single nucleotide polymorphisms ( snps ) , the group discovered that atlas2 had a generally high concordance with reported snp discovery .
overall , atlas2 showed a significantly lower number of indels by nearly an order of magnitude than either gatk or samtools , potentially because of higher false positive rates in gatk and samtools .
for the analysis of illumina sequencer data , atlas2 indel calls were comparable to those of dindel , an indel caller considered to be state - of - the - art , with a greater than 85% concordance rate .
the authors   also demonstrated that atlas2 could be run on a desktop computer and that the analysis of a 28 gb whole - exome bam file takes only 2 hours .
interestingly , they used a single core processor , whereas many current desktop computers have significantly more processors , suggesting that even faster processing times could be achieved on newer and more powerful desktop computers .
the implementation of atlas2 on a computational cluster enabled rapid processing and they cite a performance of running 92 exomes from 64 processors in 4 hours . in my own experience , gatk requires a significant number of compute nodes to process exome sequence in days , rather than hours .
the speed of analysis is a major strength of the atlas2 suite and makes such analyses accessible to research groups analyzing exome data , even those who do not have routine access to large multiprocessor computational clusters .
have introduced a highly flexible and rapid snv , snp and indel calling program suite .
most importantly , the flexibility of atlas2 to run on standard desktop computers and workstations provides an opportunity for many laboratories to use the software .
also , in comparison studies with gatk , samtools and dindel , atlas2 demonstrated comparable variant calling accuracy , showing that accuracy is not compromised by faster processing times .
given that this software is generally available and is open source , this represents a solution that could be readily adopted by many groups regardless of their size or resources .
bam : binary sequence alignment / mapping format ; gatk : genome analysis tool kit ; ngs : next - generation sequencing ; snp : single nucleotide polymorphism ; snv : single nucleotide variant ; vcf : variant call format .
this work was supported by the following grants from the nih : 2p01hg000205 and rc2 hg005570 - 01 . in addition , hpj received support from the doris duke clinical foundation and the howard hughes medical foundation .
the funding bodies had no role in writing of the manuscript or the decision to submit the manuscript .
 exome sequencing analysis is a cost - effective approach for identifying variants in coding regions . 
 however , recognizing the relevant single nucleotide variants , small insertions and deletions remains a challenge for many researchers and diagnostic laboratories typically do not have access to the bioinformatic analysis pipelines necessary for clinical application . 
 the atlas2 suite , recently released by baylor genome center , is designed to be widely accessible , runs on desktop computers but is scalable to computational clusters , and performs comparably with other popular variant callers . 
 atlas2 may be an accessible alternative for data processing when a rapid solution for variant calling is required.see research article http://www.biomedcentral.com/1471-2105/13/8 . 
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Challenges of variant calling from exome sequencing
Developing and testing a variant calling algorithm
Abbreviations
Competing interests
Acknowledgements