Informatics Pipeline Research Articles

A statistical method for single sample analysis of HumanMethylation450 array data: genome-wide methylation analysis of patients with imprinting disorders.

BackgroundThe Illumina Infinium HumanMethylation450 BeadChip is an array-based technology for analysing DNA methylation at approximately 475,000 differentially methylated cytosines across the human genome. Hitherto, the array has been used for case-control studies, where sample numbers can be sufficient to yield statistically robust data on a genome-wide basis. We recently reported an informatic pipeline capable of yielding statistically and biologically significant results using only five cases, which expanded the use of this technology to rare disease studies. However, the clinical application of these technologies requires the ability to perform robust analysis of individual patients.ResultsHere we report a novel informatic approach for methylation array analysis of single samples, using the Crawford-Howell t-test. We tested our approach on patients with ultra-rare imprinting disorders with aberrant DNA methylation at multiple locations across the genome, which was previously detected by targeted testing. However, array analysis outperformed targeted assays in three ways: it detected loci not normally analysed by targeted testing, detected methylation changes too subtle to detect by the targeted testing and reported broad and consistent methylation changes across genetic loci not captured by point testing.ConclusionsThis method has potential clinical utility for human disorders where DNA methylation change may be a biomarker of disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0081-5) contains supplementary material, which is available to authorized users.

Development and Validation of a Scalable Next-Generation Sequencing System for Assessing Relevant Somatic Variants in Solid Tumors

Next-generation sequencing (NGS) has enabled genome-wide personalized oncology efforts at centers and companies with the specialty expertise and infrastructure required to identify and prioritize actionable variants. Such approaches are not scalable, preventing widespread adoption. Likewise, most targeted NGS approaches fail to assess key relevant genomic alteration classes. To address these challenges, we predefined the catalog of relevant solid tumor somatic genome variants (gain-of-function or loss-of-function mutations, high-level copy number alterations, and gene fusions) through comprehensive bioinformatics analysis of >700,000 samples. To detect these variants, we developed the Oncomine Comprehensive Panel (OCP), an integrative NGS-based assay [compatible with <20 ng of DNA/RNA from formalin-fixed paraffin-embedded (FFPE) tissues], coupled with an informatics pipeline to specifically identify relevant predefined variants and created a knowledge base of related potential treatments, current practice guidelines, and open clinical trials. We validated OCP using molecular standards and more than 300 FFPE tumor samples, achieving >95% accuracy for KRAS, epidermal growth factor receptor, and BRAF mutation detection as well as for ALK and TMPRSS2:ERG gene fusions. Associating positive variants with potential targeted treatments demonstrated that 6% to 42% of profiled samples (depending on cancer type) harbored alterations beyond routine molecular testing that were associated with approved or guideline-referenced therapies. As a translational research tool, OCP identified adaptive CTNNB1 amplifications/mutations in treated prostate cancers. Through predefining somatic variants in solid tumors and compiling associated potential treatment strategies, OCP represents a simplified, broadly applicable targeted NGS system with the potential to advance precision oncology efforts.

FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections.

High-throughput sequence (HTS) analysis of combinatorial selection populations accelerates lead discovery and optimization and offers dynamic insight into selection processes. An underlying principle is that selection enriches high-fitness sequences as a fraction of the population, whereas low-fitness sequences are depleted. HTS analysis readily provides the requisite numerical information by tracking the evolutionary trajectory of individual sequences in response to selection pressures. Unlike genomic data, for which a number of software solutions exist, user-friendly tools are not readily available for the combinatorial selections field, leading many users to create custom software. FASTAptamer was designed to address the sequence-level analysis needs of the field. The open source FASTAptamer toolkit counts, normalizes and ranks read counts in a FASTQ file, compares populations for sequence distribution, generates clusters of sequence families, calculates fold-enrichment of sequences throughout the course of a selection and searches for degenerate sequence motifs. While originally designed for aptamer selections, FASTAptamer can be applied to any selection strategy that can utilize next-generation DNA sequencing, such as ribozyme or deoxyribozyme selections, in vivo mutagenesis and various surface display technologies (peptide, antibody fragment, mRNA, etc.). FASTAptamer software, sample data and a user's guide are available for download at http://burkelab.missouri.edu/fastaptamer.html.

Multi-Scale Imaging and Informatics Pipeline for In Situ Pluripotent Stem Cell Analysis

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

Neuroinformatics of the Allen Mouse Brain Connectivity Atlas

The Allen Mouse Brain Connectivity Atlas is a mesoscale whole brain axonal projection atlas of the C57Bl/6J mouse brain. Anatomical trajectories throughout the brain were mapped into a common 3D space using a standardized platform to generate a comprehensive and quantitative database of inter-areal and cell-type-specific projections. This connectivity atlas has several desirable features, including brain-wide coverage, validated and versatile experimental techniques, a single standardized data format, a quantifiable and integrated neuroinformatics resource, and an open-access public online database (http://connectivity.brain-map.org/). Meaningful informatics data quantification and comparison is key to effective use and interpretation of connectome data. This relies on successful definition of a high fidelity atlas template and framework, mapping precision of raw data sets into the 3D reference framework, accurate signal detection and quantitative connection strength algorithms, and effective presentation in an integrated online application. Here we describe key informatics pipeline steps in the creation of the Allen Mouse Brain Connectivity Atlas and include basic application use cases.

Neighborhood Death Rate: A Big-Data Based Health Informatics Pipeline Helps Identify Factors Impacting Clinical Outcomes and Cost Effectiveness in Acute Myeloid Leukemia Patients

BackgroundAcute Myeloid Leukemia (AML) affects 18,860 adults in the US and is expected to account for 10,460 deaths of all mortalities due to leukemia. Several models have been constructed comparing different treatment strategies with their economic burden. We sought to investigate the early deaths in AML using a unique model utilizing the predictability of sum total of patient’s neighborhood characteristics at the level of 5% and its applicability to assess the correlation between the overall outcomes and length of stay.MethodsThe patient data was queried from METEOR (Methodist Environment for Translational Enhancement and Outcomes Research), a clinical data warehouse and analytics environment that integrates existing business data warehouse with internal and external research databases and national registries to support clinical research and outcomes studies for improving patient care cost-effectively. METEOR data warehouse contains records dating back to January 1, 2006, with over 1 million unique patients and over 4 million unique patient encounters. In order to evaluate the correlation between integral/continuous variables (e.g. length of stay a.k.a. LoS) and binary clinical outcomes (e.g. survival/expired), we developed a statistical pipeline based on the concept of “Neighborhood Death Rate (NDR)”. For a specific patient X, the mean length of stay across all his/her encounters serves as the model input; and a series of neighborhood patient population are defined as all patients with mean length of stay within ±5%, ±15% or ±25% range of the number for X; the death rates within the neighborhood population then serve as a output. Thus for each individual patient, a series of NDRs are defined, and the correlation coefficients between mean LoS and 5%, 15% and 25% NDR are available. These correlations are then individually corrected for baseline demographic factors sex and race; number of encounters; and the first order statistics (mean, median, sum, minimum and maximum) for total cost and cost without bone marrow transplant corresponding to each encounter. Such statistics corrections help identify the driving force underlying the “LoS-NDR” correlations.ResultsOur database has records for 12943 encounters from 1141 patients, 838 of which are currently alive survival 73%) . The groups of survived and expired patients show significant difference on the mean LoS (p-value 2.04-E22 from Wilcoxon rank sum test). Figure 1A plots the distributions of survived (green) and expired (red) patient population separately. X-axis shows the log2 value of mean LoS; for each patient X, we calculate the number of patient with both 1) the same outcome as X and 2) a mean length of stay within ±15% range of X; and this number is then normalized using the total size of patients with the same outcome as X. [Display omitted] [Display omitted] The two outcome groups were then merged together to calculate the ±15% NDR for mean LoS (Figure 1B, X-axis show the log2 value of mean LoS, red nodes indicates expired patients). The Spearman’s Rho correlation between mean LoS and its ±15% NDR is 0.8390; meanwhile between mean LoS of 2 and 3 days, the NDR makes a significant jump from below 0.1 to above 0.3, which may represent a critical predictor for patient outcomes.During the statistical corrections, the Spearman correlations changed less than 0.01 when corrected by Sex, Race and #of encounters, indicating limited impact from these baseline factors. However, the correlation reduced to 0.6906 when corrected by mean total cost, and to 0.7301 when corrected by mean total cost without bone marrow transplant. Table 1 show the results for individual statistics corrections for Spearman correlations of “mean LoS-±15% NDR” and “median LoS-±15% NDR”. [Display omitted] ConclusionsPublished models for longevity and cost effectiveness often do not apply to the induction treatment as this a time-lapse hospital data for the duration is not usually available. Our unique analysis of Neighborhood death rates revealed that total cost is the main read-out that underlies the high correlation between length of stay and neighborhood death rates in patients with AML. We further hypothesis that medication cost (infection, critical care) and intensive care infrastructure are the main driving forces underlying the high correlation between LoS and NDR; and this model may help us obtain novel strategies to improve the cost effectiveness for AML patient care. DisclosuresNo relevant conflicts of interest to declare.

Dissecting noncoding and pathogen RNA-protein interactomes.

RNA–protein interactions are central to biological regulation. Cross-linking immunoprecipitation (CLIP)-seq is a powerful tool for genome-wide interrogation of RNA–protein interactomes, but current CLIP methods are limited by challenging biochemical steps and fail to detect many classes of noncoding and nonhuman RNAs. Here we present FAST-iCLIP, an integrated pipeline with improved CLIP biochemistry and an automated informatic pipeline for comprehensive analysis across protein coding, noncoding, repetitive, retroviral, and nonhuman transcriptomes. FAST-iCLIP of Poly-C binding protein 2 (PCBP2) showed that PCBP2-bound CU-rich motifs in different topologies to recognize mRNAs and noncoding RNAs with distinct biological functions. FAST-iCLIP of PCBP2 in hepatitis C virus-infected cells enabled a joint analysis of the PCBP2 interactome with host and viral RNAs and their interplay. These results show that FAST-iCLIP can be used to rapidly discover and decipher mechanisms of RNA–protein recognition across the diversity of human and pathogen RNAs.

A High-Resolution Spatiotemporal Atlas of Gene Expression of the Developing Mouse Brain

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for ∼2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (http://developingmouse.brain-map.org).

Analytical validation of whole exome and whole genome sequencing for clinical applications.

BackgroundWhole exome and genome sequencing (WES/WGS) is now routinely offered as a clinical test by a growing number of laboratories. As part of the test design process each laboratory must determine the performance characteristics of the platform, test and informatics pipeline. This report documents one such characterization of WES/WGS.MethodsWhole exome and whole genome sequencing was performed on multiple technical replicates of five reference samples using the Illumina HiSeq 2000/2500. The sequencing data was processed with a GATK-based genome analysis pipeline to evaluate: intra-run, inter-run, inter-mode, inter-machine and inter-library consistency, concordance with orthogonal technologies (microarray, Sanger) and sensitivity and accuracy relative to known variant sets.ResultsConcordance to high-density microarrays consistently exceeds 97% (and typically exceeds 99%) and concordance between sequencing replicates also exceeds 97%, with no observable differences between different flow cells, runs, machines or modes. Sensitivity relative to high-density microarray variants exceeds 95%. In a detailed study of a 129 kb region, sensitivity was lower with some validated single-base insertions and deletions “not called”. Different variants are "not called" in each replicate: of all variants identified in WES data from the NA12878 reference sample 74% of indels and 89% of SNVs were called in all seven replicates, in NA12878 WGS 52% of indels and 88% of SNVs were called in all six replicates. Key sources of non-uniformity are variance in depth of coverage, artifactual variants resulting from repetitive regions and larger structural variants.

Bioimage Informatics in the context of Drosophila research

Modern biological research relies heavily on microscopic imaging. The advanced genetic toolkit of Drosophila makes it possible to label molecular and cellular components with unprecedented level of specificity necessitating the application of the most sophisticated imaging technologies. Imaging in Drosophila spans all scales from single molecules to the entire populations of adult organisms, from electron microscopy to live imaging of developmental processes. As the imaging approaches become more complex and ambitious, there is an increasing need for quantitative, computer-mediated image processing and analysis to make sense of the imagery. Bioimage Informatics is an emerging research field that covers all aspects of biological image analysis from data handling, through processing, to quantitative measurements, analysis and data presentation. Some of the most advanced, large scale projects, combining cutting edge imaging with complex bioimage informatics pipelines, are realized in the Drosophila research community. In this review, we discuss the current research in biological image analysis specifically relevant to the type of systems level image datasets that are uniquely available for the Drosophila model system. We focus on how state-of-the-art computer vision algorithms are impacting the ability of Drosophila researchers to analyze biological systems in space and time. We pay particular attention to how these algorithmic advances from computer science are made usable to practicing biologists through open source platforms and how biologists can themselves participate in their further development.

Genome-wide DNA methylation analysis of patients with imprinting disorders identifies differentially methylated regions associated with novel candidate imprinted genes

BackgroundGenomic imprinting is allelic restriction of gene expression potential depending on parent of origin, maintained by epigenetic mechanisms including parent of origin-specific DNA methylation. Among approximately 70 known imprinted genes...

NGSANE: a lightweight production informatics framework for high-throughput data analysis

Summary: The initial steps in the analysis of next-generation sequencing data can be automated by way of software ‘pipelines’. However, individual components depreciate rapidly because of the evolving technology and analysis methods, often rendering entire versions of production informatics pipelines obsolete. Constructing pipelines from Linux bash commands enables the use of hot swappable modular components as opposed to the more rigid program call wrapping by higher level languages, as implemented in comparable published pipelining systems.Here we present Next Generation Sequencing ANalysis for Enterprises (NGSANE), a Linux-based, high-performance-computing-enabled framework that minimizes overhead for set up and processing of new projects, yet maintains full flexibility of custom scripting when processing raw sequence data.Availability and implementation: Ngsane is implemented in bash and publicly available under BSD (3-Clause) licence via GitHub at https://github.com/BauerLab/ngsane.Contact: Denis.Bauer@csiro.auSupplementary information: Supplementary data are available at Bioinformatics online.

Production and analytic bioinformatics for next-generation DNA sequencing.

The bioinformatics requirements within the clinical environment are very specific, and analytic techniques need to be fit for purpose, robust, and predictable. At the same time, the bewildering amount of information produced during these analyses needs to be carefully managed, used and interpreted correctly. The challenge for clinical laboratories now is to implement production analytical processes that are capable of handling different experimental approaches on current equipment, as well as to incorporate ways for these systems to evolve to take account of developments likely to make impacts in the near future. This is complicated by the many options available at each of the critical processing steps and a clear method needs to be developed to assemble appropriate pipelines. Here, I discuss the issues relevant to the development of an informatics pipeline that meets these criteria that should allow individual laboratories to assess their proposed strategies.

Targeted-capture massively-parallel sequencing enables robust detection of clinically informative mutations from formalin-fixed tumours

Massively parallel sequencing offers the ability to interrogate a tumour biopsy for multiple mutational changes. For clinical samples, methodologies must enable maximal extraction of available sequence information from formalin-fixed and paraffin-embedded (FFPE) material. We assessed the use of targeted capture for mutation detection in FFPE DNA. The capture probes targeted the coding region of all known kinase genes and selected oncogenes and tumour suppressor genes. Seven melanoma cell lines and matching FFPE xenograft DNAs were sequenced. An informatics pipeline was developed to identify variants and contaminating mouse reads. Concordance of 100% was observed between unfixed and formalin-fixed for reported COSMIC variants including BRAF V600E. mutations in genes not conventionally screened including ERBB4, ATM, STK11 and CDKN2A were readily detected. All regions were adequately covered with independent reads regardless of GC content. This study indicates that hybridisation capture is a robust approach for massively parallel sequencing of FFPE samples.

Chloroplast genome analysis of Australian eucalypts – Eucalyptus, Corymbia, Angophora, Allosyncarpia and Stockwellia (Myrtaceae)

We present a phylogenetic analysis and comparison of structural features of chloroplast genomes for 39 species of the eucalypt group (genera Eucalyptus, Corymbia, Angophora, and outgroups Allosyncarpia and Stockwellia). We use 41 complete chloroplast genome sequences, adding 39 finished-quality chloroplast genomes to two previously published genomes. Maximum parsimony and Bayesian analyses, based on >7000 variable nucleotide positions, produced one fully resolved phylogenetic tree (35 supported nodes, 27 with 100% bootstrap support). Eucalyptus and its sister lineage Angophora+Corymbia show a deep divergence. Within Eucalyptus, three lineages are resolved: the ‘eudesmid’, ‘symphyomyrt’ and ‘monocalypt’ groups. Corymbia is paraphyletic with respect to Angophora. Gene content and order do not vary among eucalypt chloroplasts; length mutations, especially frame shifts, are uncommon in protein-coding genes. Some non-synonymous mutations are highly incongruent with the overall phylogenetic signal, notably in rbcL, and may be adaptive. Application of custom informatics pipelines (GYDLE Inc.) enabled direct chloroplast genome assembly, resolving each genome to finished-quality with no need for PCR gap-filling or contig order resolution. Analysis of whole chloroplast genomes resolved major eucalypt clades and revealed variable regions of the genome that will be useful in lower-level genetic studies (including phylogeography and geneflow).

An informatic pipeline for managing high-throughput screening experiments and analyzing data from stereochemically diverse libraries

Integration of flexible data-analysis tools with cheminformatics methods is a prerequisite for successful identification and validation of "hits" in high-throughput screening (HTS) campaigns. We have designed, developed, and implemented a suite of robust yet flexible cheminformatics tools to support HTS activities at the Broad Institute, three of which are described herein. The "hit-calling" tool allows a researcher to set a hit threshold that can be varied during downstream analysis. The results from the hit-calling exercise are reported to a database for record keeping and further data analysis. The "cherry-picking" tool enables creation of an optimized list of hits for confirmatory and follow-up assays from an HTS hit list. This tool allows filtering by computed chemical property and by substructure. In addition, similarity searches can be performed on hits of interest and sets of related compounds can be selected. The third tool, an "S/SAR viewer," has been designed specifically for the Broad Institute's diversity-oriented synthesis (DOS) collection. The compounds in this collection are rich in chiral centers and the full complement of all possible stereoisomers of a given compound are present in the collection. The S/SAR viewer allows rapid identification of both structure/activity relationships and stereo-structure/activity relationships present in HTS data from the DOS collection. Together, these tools enable the prioritization and analysis of hits from diverse compound collections, and enable informed decisions for follow-up biology and chemistry efforts.

Finding the true $1000 Genome

Finding the true $1000 Genome

Specialty Grand Challenge – Genetic Disorders

SPECIALTY GRAND CHALLENGE article Front. Pediatr., 20 November 2013Sec. Genetics of Common and Rare Diseases Volume 1 - 2013 | https://doi.org/10.3389/fped.2013.00036

Abstract 4414: Distinct taxonomic, metagenomic and metabolomic profiles from a comprehensive gut flora analysis in healthy and colon adenoma African Americans

Abstract Background: Gut flora has long been suspected to play a role in colorectal cancer (CRC) pathogenesis. Elegant experiments have substantiated such claims with the use of single pathogenic bacteria in germ free colon cancer mouse models. Here we run a comprehensive taxonomic, metagenomic and metabolomics analysis of stool samples from healthy and colon adenoma African American (AA) patients to define further this role. Patients &amp; Methods: DNA extracts from stool samples of 6 healthy and 6 colon adenoma patients were used for the taxonomic and metagenomic analysis. The sequencing was done using a 454 pyrosequencer and the generated data was processed using informatics pipeline for phylogenetic bacterial affiliation and for bacterial functions assignment. For the metabolomics analysis, 10 fecal water extracts from healthy individuals and 10 from colon adenoma patients were analysed for their metabolites’ contents using NMR spectrometry. Results: The analysis of 16S-rDNA sequences revealed the existence of 22 groups of bacteria. A phylogenetic clustering revealed colon adenoma cases clustering together. Most predominant groups in both sets of samples were Clostridia and Bacteroides. No Lactobacilli or Bifidobacteria (good bacteria) were detected. The synergistetes_Dynergistia group -involved in gastrointestinal infections and Firmicutes phylum: Firmicutes group - involved in energy resorption and obesity were 20 and 10 folds more prevalent in adenoma patients, respectively. Bacteria TM7 group that contain active agents in IBD was 5 folds more represented in the control compared to the adenoma group. The metagenomic experiment have led to the generation of about 100,000 reads per sample, 80% of which were successfully annotated. Among the annotated functions, many were differentially present in the colon adenoma compared to healthy individuals. The metabolomics analysis led to a strong clustering of the adenoma samples metabolomes further consolidating the role of bacteria and their metabolites in colon cancer pathology. Conclusion: Our taxonomic, metagenomic and metabolomics analysis have led the presence of clear differential profiles in colon adenoma patients vs. healthy persons. Lack of detection of “good bacteria” (Lactobacilli and Bifidobacteria) in this study defines already a first level of intervention in this high risk CRC population. A comprehensive analysis of all the results is underway to bridge the Taxo, Meta and metabolomics data. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4414. doi:1538-7445.AM2012-4414

Comparison of Three Targeted Enrichment Strategies on the SOLiD Sequencing Platform

Despite the ever-increasing throughput and steadily decreasing cost of next generation sequencing (NGS), whole genome sequencing of humans is still not a viable option for the majority of genetics laboratories. This is particularly true in the case of complex disease studies, where large sample sets are often required to achieve adequate statistical power. To fully leverage the potential of NGS technology on large sample sets, several methods have been developed to selectively enrich for regions of interest. Enrichment reduces both monetary and computational costs compared to whole genome sequencing, while allowing researchers to take advantage of NGS throughput. Several targeted enrichment approaches are currently available, including molecular inversion probe ligation sequencing (MIPS), oligonucleotide hybridization based approaches, and PCR-based strategies. To assess how these methods performed when used in conjunction with the ABI SOLID3+, we investigated three enrichment techniques: Nimblegen oligonucleotide hybridization array-based capture; Agilent SureSelect oligonucleotide hybridization solution-based capture; and Raindance Technologies' multiplexed PCR-based approach. Target regions were selected from exons and evolutionarily conserved areas throughout the human genome. Probe and primer pair design was carried out for all three methods using their respective informatics pipelines. In all, approximately 0.8 Mb of target space was identical for all 3 methods. SOLiD sequencing results were analyzed for several metrics, including consistency of coverage depth across samples, on-target versus off-target efficiency, allelic bias, and genotype concordance with array-based genotyping data. Agilent SureSelect exhibited superior on-target efficiency and correlation of read depths across samples. Nimblegen performance was similar at read depths at 20× and below. Both Raindance and Nimblegen SeqCap exhibited tighter distributions of read depth around the mean, but both suffered from lower on-target efficiency in our experiments. Raindance demonstrated the highest versatility in assay design.