Clinical Sequencing Technical Guide

Table of Contents

Letter from the Editor
Index of Experts
Q1: How does sample prep for clinical sequencing differ from sample prep for sequencing in a research setting? Especially when designing targeted panels or exome capture, can you use off-the-shelf kits, or do you design your own?
Q2: How do you do analysis and interpretation for clinical sequencing? Can you describe how you use the different variant databases, or whether you are also developing your own internal database?
Q3: How do you deal with variants of unknown significance and variants that are unrelated to the patient's condition?
Q4: Can you describe your informed consent protocol?
Q5: How do you decide what information to include in the physician's report, and who is responsible for making the decisions on what information to include?
Q6: What happens to the data that does not get included in the physician's report — do you store that, and, if so, for how long and can the physician access it?
List of Resources

Letter from the Editor

Next-generation sequencing technology has made major gains in the last several years, and as the technology continues to improve and become cheaper, researchers are increasingly looking to transition it from purely a research tool and into the clinic.

A number of laboratories and companies have already launched diagnostic tests based on next-gen sequencing, and many more are in the works including targeted sequencing-based tests to diagnose specific genetic disorders such as hereditary blindness or intellectual disability, oncology assays to identify therapeutic targets, and even whole-exome and whole-genome sequencing tests to elucidate undiagnosed diseases.

Yet, moving the technology into the clinic poses a host of technical challenges. Currently, there are no technical standards for sequencing in a clinical setting. Additionally, there are no tests that have yet been approved by the US Food and Drug Administration.

While groups such as the American College of Medical Genetics and Genomics and the College of American Pathologists are working on guidelines for clinical sequencing, test developers have largely been navigating the technical and regulatory issues on their own.

Then there is the issue of what to do with the massive amounts of data that can be produced by next-gen sequencing approaches — whether, how, and for how long to store patients' genomic data. With comprehensive sequencing, such as whole-genome or whole-exome, there is always the prospect of finding unanticipated results, such as pathogenic variants unrelated to the patient's condition.

In this guide, we've asked a variety of experts to share how they've answered issues around sample preparation, interpretation, data analysis and storage, unanticipated findings, informed consent, and return of results in their respective clinical sequencing pipelines.

— Monica Heger

Index of Experts

Genome Technology would like to thank the following contributors for taking the time to respond to the questions in this tech guide.

Saskia Biskup
Center for Genomics and Transcriptomics (CeGaT)

Andrew Bredmeyer
Genomics and Pathology Services (GPS)
Washington University School of Medicine

David Dimmock
Medical College of Wisconsin

Stan Nelson
Departments of Human Genetics, Pathology and Laboratory Medicine, and Psychiatry
UCLA, David Geffen School of Medicine

Joris Veltman
Genomic Disorders Nijmegen
Radboud University Nijmegen Medical Centre

Q1: How does sample prep for clinical sequencing differ from sample prep for sequencing in a research setting? Especially when designing targeted panels or exome capture, can you use off-the-shelf kits, or do you design your own?

For specific gene panels (Diagnostic Panels) we do not use off-the-shelf kits, but have designed our own CeGaT kits. Our own designed kits deliver a significantly better coverage per base for the genes of interest. We spend a lot of money and time in designing and optimizing our kits. This is an iterative process of designing, sequencing, re-designing (optimizing by including additional baits in regions of low coverage and balancing of baits), sequencing, and so on.

We only use off-the-shelf kits when enriching for the whole exome. So far we have gained the best experience in combining Agilent SureSelect together with SOLiD sequencing.

— Saskia Biskup

Our 27 cancer gene set test begins with a pathologist's examination of the tumor specimen to identify an area of high neoplastic cellularity for DNA extraction (for solid tumors). Sample preparation steps are performed according to validated clinical protocols by certified personnel, and careful documentation is maintained per College of American Pathology requirements for CLIA licensure. Since our assay is performed as a laboratory-developed test, we use custom-designed fluid-phase capture probes for our targeted oncology test, and [we] went through multiple iterations of probe design to optimize performance. We also target greater than 1,000x coverage to maintain a high sensitivity and high positive predictive value, even for those variants present in only a fraction of the cells assayed.

— Andrew Bredmeyer

Both can be used. Clinically, we have a lot more checks in place to reduce the risk of sample switch. To recheck final results, we also typically sequence deeper. For specific gene panels, there is a lot of "rebalancing" to ensure under-sequenced regions are better covered.

— David Dimmock

UCLA uses off-the-shelf kits for sample preparation, so sample preparation for clinical sequencing is not different from sample preparation for research sequencing. However, for clinical sequencing in our CLIA lab, we strictly follow our validated workflow, which requires passing strict quality filters as well as sequencing to a higher depth than we do for research samples.

— Stan Nelson

We used off-the-shelf exome kits and protocols for our clinical sequencing, no different from the research setting. For exome enrichment, we currently use the Agilent SureSelect v4 exome assay. Before making the move to clinical exome sequencing, we embedded an exome-sequencing protocol in our research laboratory, which is also quality accredited and audited.

Our exome sequencing protocol only differs minimally from the provided protocol (e.g. new QC steps as additional Agilent bioanalyzer runs), and we have implemented additional QC steps to avoid sample swaps in our clinical exome sequencing protocol by genotyping 12 coding SNPs from the stock DNA prior to exome sequencing and comparing this to the exome sequencing genotypes afterwards.

— Joris Veltman

Q2: How do you do analysis and interpretation for clinical sequencing? Can you describe how you use the different variant databases, or whether you are also developing your own internal database?

Firstly, we make sure that every base is covered sufficiently often so that variants can be called. This sometimes requires sequencing by Sanger to overcome gaps or underrepresented regions. Secondly, we annotate variants using different databases (Ensembl, RefSeq, dbSNP, EVS, HapMap, et cetera. and our own database). Thirdly, we filter for non-synonymous, splice sites, stop-gain and stop loss mutations and then filter using minor allele frequencies depending on the disease and inheritance pattern and prioritize according to alignment score (BLOSUM Matrices) and conservation of the position in different species. PolyPhen, MutationTaster, and NetSplice help to judge potential effects on protein structure.

— Saskia Biskup

GPS has built a software tool for clinical sequencing order management called the Clinical Genomics Workstation. We use the CGW to process sequencing orders, perform bioinformatic analysis, annotate identified variants, visualize variant and reference data, and draft and sign out clinical reports. Bioinformatic analyses, including alignment and variant calling, have been optimized to maximize analytical and diagnostic sensitivity and specificity. This analysis pipeline is controlled through the CGW and is locked down to ensure each assay GPS runs has the sensitivity and specificity we report in our documentation. We are currently validating an expanded clinical oncology gene set test with 50 genes and detection of SNV, indels, translocations, and copy number variants. Annotation relies both on available databases such as COSMIC, dbSNP, and HGMD, and on our own clinical-grade curated knowledgebase.

— Andrew Bredmeyer

For known genes, we will start with the known locus or public database, for example HGMD. However, an estimated 20 percent of published mutations are actually errors. We also use public resources such as the exome variant server to identify frequent population variants.

We maintain internal databases of mutations we have identified until we can publish them, in addition to data on local population frequencies of common variants and annotations of erroneous published mutations. We use publically available and self-developed tools to evaluate the potential that a specific variant disrupts gene functioning.

— David Dimmock

Analysis is performed using our in-house developed, clinically validated bioinformatics workflow. (More details: http://pathology.ucla.edu/workfiles/Lab%20Medicine/CES-Workflow.pdf)

— Stan Nelson

Our bioinformaticians have made a user-friendly clinical sequencing software package with graphical interface that allows us to automatically filter for genomic variation based on extensive annotation related to the affected nucleotide position, the gene involved, and the corresponding protein.

For each disease for which we offer clinical exome sequencing, we have established disease gene packages, and we first filter for variation in these genes. For example, for a patient with blindness, only variants that lie within known blindness genes are selected for interpretation.

In addition, we use three variant database resources:

1. Variants are annotated with information from dbSNP. Whether the variant is known in dbSNP and what the overall frequency of the variant is.

2. Variants are annotated with information from our in-house database, containing information from roughly 1,200 exomes. Whether the variant is in the database, at what frequency, in which type of disease it was found, as well as a reliability score.
3. Variants are annotated with information from HGMD and an in-house database of pathogenic mutations.

The current diagnostic filters exclude variants occurring at frequencies above 1 percent in dbSNP or our in-house database, albeit we keep all variants reported in HGMD or our in-house pathogenic mutation database. In addition, further filtering allows us to exclude non-coding and synonymous variants, as well as nonsynonymous variants that are not well conserved in evolution.

For patients with sporadic forms of intellectual disability, we use a family-based approach to identify causative de novo mutations. In these cases, the exomes of both the patient as well as the unaffected parents are sequenced and potential de novo mutations are selected that are in the coding region and are predicted to affect the protein, using basically the same selection criteria. Next to the gene package, it is then also possible to select potential de novo mutations that are outside of the gene package. The additional information also allows us to select for recessive and X-linked variants that may explain the intellectual disability.

— Joris Veltman

Q3: How do you deal with variants of unknown significance and variants that are unrelated to the patient's condition?

We do not report benign variants, but report variants of unknown significance if we think that they might be pathogenic. We suggest segregation analysis in these cases and usually test the parents after informed consent.

— Saskia Biskup

Our approach is to highlight those variants with definitively established importance for treatment decisions based on evidence from the medical literature, while also reporting findings with less evidence-based support, but potential relevance. Given the selection of genes in our test, we are unlikely to find variants that draw us too far afield from oncology. However, findings that may indicate a familial cancer predisposition syndrome are occasionally made, and we recommend constitutional DNA testing and genetic counseling in such cases. Variants of unknown significance are reported if the variant has been described previously in cancer patients.

Overall, to assist clinicians with interpreting the significance of the result, variants are reported in a classification scheme from Level 1 to Level 8. Level 1 variants are clinically actionable for the patient's cancer, Level 2 variants are clinically prognostic for the patient's cancer, Level 3 variants are clinically actionable in a cancer other than the patient's cancer, Level 4 variants have biological evidence suggesting an alteration of function of the normal protein, Level 5 variants have been previously identified in other patients having the same cancer but with no known clinical relevance, Level 6 variants have been previously identified in other patients having some other cancer or other disease but with no known clinical relevance, Level 7 variants are novel and have not been previously documented as a polymorphism, Level 8 variants have been previously documented as a known polymorphism.

We plan to transition to the simplified scheme similar to those recommended by several professional societies: pathogenic, likely pathogenic, variant of uncertain significance, likely benign, and benign.

— Andrew Bredmeyer

For the first question: In known genes, we follow ACMG guidelines for the interpretation of variants in genes. Describing new genes is much more involved and typically involves research testing separate from the clinical lab. (For details on the second question, see: http://genomemedicine.com/content/4/6/54/abstract).

— David Dimmock

In general, variants that are unrelated to the primary clinical concern(s) are not reported. Variants of unknown clinical significance, which are the vast majority of all variants detected, are generally not reported, especially if they are unrelated to the primary clinical concern(s).

— Stan Nelson

Possible pathogenic variants of unknown significance (UV3) are reported to the patient or their legal representatives when detected in a gene relevant for the patient’s condition.

The use of predefined filters for disease gene packages greatly reduces the chance to identify variants that are unrelated to the patient’s condition. Still, if these variants are encountered (incidental findings) they are reported only when classified as pathogenic (UV4) AND after consultation with an independent expert committee. This committee consists of a laboratory specialist clinical geneticist, a clinical geneticist, a molecular geneticist, a social worker, a lawyer, and an ethicist. If needed, a medical specialist with more knowledge of the disease involved will be consulted. Together, they will decide whether or not to disclose the unsolicited finding to the referring doctor. He or she will inform the patient.

— Joris Veltman

Q4: Can you describe your informed consent protocol?

In Germany, the Gene Diagnostic Law applies, which requires genetic counselling before testing. CeGaT follows this law. Firstly, we give all necessary background information related to the test to the referring clinician and to the patient. This includes the methods, possible outcomes of the test and how this might affect the individual and other family members. We also clarify the below issues:

(i) The patient asking for the test must determine who will receive the medical report.
ii) Incidental findings are discussed with the patient and to what extent they are reported. We distinguish between incidental findings with therapeutic consequences and those that do not have immediate consequences (i.e. late-onset disease where no therapy is available).
(iii) Storage of blood, DNA, data and medical reports. The material can be destroyed after completing the test or can be stored for 10 years or up to 30 years.
(iv) Scientific usage of data in anonymized form.
(v) The patient has the right to cease the testing at any point of time.

Testing is forbidden in children if there are no therapeutic consequences. In asymptomatic individuals, a special qualification is necessary to being allowed to counsel and test.

— Saskia Biskup

For our 27 cancer gene set, we currently do not administer a consent to perform testing in the context of the patient's recurrent cancer because the findings are limited to the disease itself. However, we are in the process of preparing consents to perform clinical genomic testing as we expand our test offerings to include larger targeted gene sets (for both oncology and inherited disorders) and whole exome/genome sequencing. This consent includes options for the patient to receive or not receive familial relationship and secondary (incidental) findings, to opt out of future research use of data and specimens gathered as part of the test, and to opt in to future clinical study/trial recruitment based on data derived from the test being administered.

— Andrew Bredmeyer

We recommend genetic counseling pre- and post-test by a geneticist or genetics counselor, and we require signed consent form with test request.

— Stan Nelson

All patients or their legal representatives have to sign informed consent for exome sequencing. People are informed on the small risk of unsolicited findings, but they have to agree that they will be informed in case the expert committee decides that this finding might be relevant for the counselee. It is (for now) NOT an option to opt out for these unsolicited findings. Furthermore, the informed consent includes information about data storage, and the fact that data might be shared anonymously with other researchers.

— Joris Veltman

Q5: How do you decide what information to include in the physician's report, and who is responsible for making the decisions on what information to include?

We have a standard report that comprises the exact description of the variant (according to the reference database), a judgment on the relevance of the variant, the method applied, an overview of the literature related to the finding and a summary containing all relevant medical information. Depending on the consent protocol, incidental findings are included in the report or not. So, in the end the patient is responsible for making the decision if a test is performed and what information is included in the report. The report is sent to the referring clinician and not to the patient directly.

— Saskia Biskup

Variants identified in tumor DNA are automatically categorized by the CGW based on their clinical relevance as reported in the literature (see answer to question #3 above). In addition, a summary section of the report contains a brief synopsis of the available clinical evidence for each reported variant. Decisions on what information to include are made by the clinical genomicist signing out the report; in our laboratory, these individuals are either pathologists with subspecialty board certification in molecular genetic pathology from the American Board of Pathology or molecular geneticists board certified by the American Board of Medical Genetics.

— Andrew Bredmeyer

The patient or parents are responsible for deciding what they want returned. We return cause of clinical presentation in question and proven pathogenic mutations.

— David Dimmock

The interpretation and reporting decisions are made at the UCLA Genomics Data Board meeting, where board certified pathologists, molecular geneticists, molecular cytogeneticists, clinical geneticists, genetic counselors, and informatics specialists review each case. However, the final responsibility rests with the laboratory director.

— Stan Nelson

The reports are written by qualified laboratory specialist clinical geneticists. Decision making is not very much different from "regular" diagnostics tests: Variants are reported when considered relevant for the condition of the counselee.

— Joris Veltman

Q6: What happens to the data that does not get included in the physician's report — do you store that, and if so for how long and can the physician access it?

The individual seeking the testing decides if and (if so) how long the data and the material are stored. We offer to re-evaluate the data at a later time point if wished.

— Saskia Biskup

Synonymous and non-coding variants that have not been reported previously and known polymorphisms without clinical significance do not appear on the report, but are available to the treating physician upon request. These data are stored indefinitely. With the appropriate institutional review board approval, we will make these data available for research.

— Andrew Bredmeyer

We are required by law to keep data for not less than two years. A physician could request a re-analysis.

— David Dimmock

All of the variant data is stored in a secure database. We intend to store the data indefinitely at this point. The physician can request the full variant file, but we do not attempt to interpret all of the 20,000 protein coding sequence variants per genome. Thus, this information can be returned without clinical interpretation. The physician can also submit an order for re-analysis in the cases where no clinically significant variants are found in the initial analysis. With the ongoing discovery of new disease-associated variants, this may allow for the identification of the causal variant(s) in some patients at a later date without the need for re-sequencing.

— Stan Nelson

All data is stored for a minimum period of two years. Variant files on which the report is based are stored for a minimum of 10 years.

— Joris Veltman

List of resources

Publications

Biesecker LG. (2012). Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: lessons from the ClinSeq project. Genet Med. 14(4):393-8.

Coonrod EM, Durtschi JD, Margraf RL, Voelkerding KV. (2012). Developing genome and exome sequencing for candidate gene identification in inherited disorders. Arch Pathol Lab Med. 2012 Jul 7. [Epub ahead of print]

Coonrod EM, Margraf RL, Voelkerding KV. (2011). Translating exome sequencing from research to clinical diagnostics. Clin Chem Lab Med. 50(7):1161-8.

Cronin M, Ross JS. (2011). Comprehensive next-generation cancer genome sequencing in the era of targeted therapy and personalized oncology. Biomark Med. 5(3):293-305.

Dimmock D. (2012). A personal perspective on returning secondary results of clinical genome sequencing. Genome Med. 4(6):54.

Ellis MJ, Ding L, Shen D, Luo J, Suman VJ, Wallis JW, Van Tine BA, Hoog J, Goiffon RJ, Goldstein TC, Ng S, Lin L, Crowder R, Snider J, Ballman K, Weber J, Chen K, Koboldt DC, Kandoth C, Schierding WS, McMichael JF, Miller CA, Lu C, Harris CC, McLellan MD, Wendl MC, DeSchryver K, Allred DC, Esserman L, Unzeitig G, Margenthaler J, Babiera GV, Marcom PK, Guenther JM, Leitch M, Hunt K, Olson J, Tao Y, Maher CA, Fulton LL, Fulton RS, Harrison M, Oberkfell B, Du F, Demeter R, Vickery TL, Elhammali A, Piwnica-Worms H, McDonald S, Watson M, Dooling DJ, Ota D, Chang LW, Bose R, Ley TJ, Piwnica-Worms D, Stuart JM, Wilson RK, Mardis ER. (2012). Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature. 486(7403):353-60.

Evers AW, Rovers MM, Kremer JA, Veltman JA, Schalken JA, Bloem BR, van Gool AJ. (2012). An integrated framework of personalized medicine: from individual genomes to participatory health care. Croat Med J. 53(4):301-3.

Goh V, Helbling D, Biank V, Jarzembowski J, Dimmock D. (2012). Next-generation sequencing facilitates the diagnosis in a child with twinkle mutations causing cholestatic liver failure. J Pediatr Gastroenterol Nutr. 54(2):291-4.

Green ED, Guyer MS; National Human Genome Research Institute. (2011). Charting a course for genomic medicine from base pairs to bedside. Nature. 470(7333):204-13.

Green RC, Berg JS, Berry GT, Biesecker LG, Dimmock DP, Evans JP, Grody WW, Hegde MR, Kalia S, Korf BR, Krantz I, McGuire AL, Miller DT, Murray MF, Nussbaum RL, Plon SE, Rehm HL, Jacob HJ. (2012). Exploring concordance and discordance for return of incidental findings from clinical sequencing. Genet Med. (4):405-10.

Harismendy O, Schwab RB, Bao L, Olson J, Rozenzhak S, Kotsopoulos SK, Pond S, Crain B, Chee MS, Messer K, Link DR, Frazer KA. (2011). Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing. Genome Biol. 12(12):R124.

Hoppman-Chaney N, Peterson LM, Klee EW, Middha S, Courteau LK, Ferber MJ. (2010). Evaluation of oligonucleotide sequence capture arrays and comparison of next-generation sequencing platforms for use in molecular diagnostics. Clin Chem. 56(8):1297-306.

Jones MA, Bhide S, Chin E, Ng BG, Rhodenizer D, Zhang VW, Sun JJ, Tanner A, Freeze HH, Hegde MR. (2011). Targeted polymerase chain reaction-based enrichment and next generation sequencing for diagnostic testing of congenital disorders of glycosylation. Genet Med. 13(11):921-32.

Kaphingst K, Facio F, Cheng MR, Brooks S, Eidem H, Linn A, Biesecker B, Biesecker L. (2012). Effects of informed consent for individual genome sequencing on relevant knowledge. Clin Genet. 2012 Jun 13. doi: 10.1111/j.1399-0004.2012.01909.x. [Epub ahead of print]

Lipson D, Capelletti M, Yelensky R, Otto G, Parker A, Jarosz M, Curran JA, Balasubramanian S, Bloom T, Brennan KW, Donahue A, Downing SR, Frampton GM, Garcia L, Juhn F, Mitchell KC, White E, White J, Zwirko Z, Peretz T, Nechushtan H, Soussan-Gutman L, Kim J, Sasaki H, Kim HR, Park SI, Ercan D, Sheehan CE, Ross JS, Cronin MT, Jänne PA, Stephens PJ. (2012). Identification of new ALK and RET gene fusions from colorectal and lung cancer biopsies. Nat Med. 18(3):382-4.

Lo YM. (2012). Non-invasive prenatal diagnosis by massively parallel sequencing of maternal plasma DNA. Open Biol. 2(6):120086.

Mardis ER. (2012). Applying next-generation sequencing to pancreatic cancer treatment. Nat Rev Gastroenterol Hepatol. 9(8):477-86.

McDonald SA, Mardis ER, Ota D, Watson MA, Pfeifer JD, Green JM. (2012). Comprehensive genomic studies: emerging regulatory, strategic, and quality assurance challenges for biorepositories. Am J Clin Pathol. 138(1):31-41.

Meldrum C, Doyle MA, Tothill RW. (2011). Next-generation sequencing for cancer diagnostics: a practical perspective. Clin Biochem Rev. 32(4):177-95.

Norton ME, Brar H, Weiss J, Karimi A, Laurent LC, Caughey AB, Rodriguez MH, Williams J 3rd, Mitchell ME, Adair CD, Lee H, Jacobsson B, Tomlinson MW, Oepkes D, Hollemon D, Sparks AB, Oliphant A, Song K. (2012). Non-Invasive Chromosomal Evaluation (NICE) Study: results of a multicenter prospective cohort study for detection of fetal trisomy 21 and trisomy 18. Am J Obstet Gynecol. 207(2):137.e1-8.

Palomaki GE, Deciu C, Kloza EM, Lambert-Messerlian GM, Haddow JE, Neveux LM, Ehrich M, van den Boom D, Bombard AT, Grody WW, Nelson SF, Canick JA. (2012). DNA sequencing of maternal plasma reliably identifies trisomy 18 and trisomy 13 as well as Down syndrome: an international collaborative study. Genet Med. 14(3):296-305.

Pritchard CC, Smith C, Salipante SJ, Lee MK, Thornton AM, Nord AS, Gulden C, Kupfer SS, Swisher EM, Bennett RL, Novetsky AP, Jarvik GP, Olopade OI, Goodfellow PJ, King MC, Tait JF, Walsh T. (2012). ColoSeq provides comprehensive lynch and polyposis syndrome mutational analysis using massively parallel sequencing. J Mol Diagn. 14(4):357-66.

Roychowdhury S, Iyer MK, Robinson DR, Lonigro RJ, Wu YM, Cao X, Kalyana-Sundaram S, Sam L, Balbin OA, Quist MJ, Barrette T, Everett J, Siddiqui J, Kunju LP, Navone N, Araujo JC, Troncoso P, Logothetis CJ, Innis JW, Smith DC, Lao CD, Kim SY, Roberts JS, Gruber SB, Pienta KJ, Talpaz M, Chinnaiyan AM. (2011). Personalized oncology through integrative high-throughput sequencing: a pilot study. Sci Transl Med. 3(111):111ra121.

Schrijver I, Aziz N, Farkas DH, Furtado M, Gonzalez AF, Greiner TC, Grody WW, Hambuch T, Kalman L, Kant JA, Klein RD, Leonard DG, Lubin IM, Mao R, Nagan N, Pratt VM, Sobel ME, Voelkerding KV, Gibson JS. (2012). Opportunities and Challenges Associated with Clinical Diagnostic Genome Sequencing: A Report of the Association for Molecular Pathology. J Mol Diagn. 2012 Aug 20. [Epub ahead of print]

Sehnert AJ, Rhees B, Comstock D, de Feo E, Heilek G, Burke J, Rava RP. (2011). Optimal detection of fetal chromosomal abnormalities by massively parallel DNA sequencing of cell-free fetal DNA from maternal blood. Clin Chem. 57(7):1042-9.

Shearer AE, DeLuca AP, Hildebrand MS, Taylor KR, Gurrola J, Scherer S, Scheetz TE, Smith RJH. (2010). Comprehensive genetic testing for hereditary hearing loss using massively parallel sequencing. Proc Natl Acad Sci U S A. 107(49): 21104–21109.

Tran B, Brown AM, Bedard PL, Winquist E, Goss GD, Hotte SJ, Welch SA, Hirte HW, Zhang T, Stein LD, Ferretti V, Watt S, Jiao W, Ng K, Ghai S, Shaw P, Petrocelli T, Hudson TJ, Neel BG, Onetto N, Siu LL, McPherson JD, Kamel-Reid S, Dancey JE. (2012). Feasibility of real time next generation sequencing of cancer genes linked to drug response: Results from a clinical trial. Int J Cancer. 2012 Sep 5. doi: 10.1002/ijc.27817. [Epub ahead of print]

Valencia CA, Rhodenizer D, Bhide S, Chin E, Littlejohn MR, Keong LM, Rutkowski A, Bonnemann C, Hegde M. (2012). Assessment of target enrichment platforms using massively parallel sequencing for the mutation detection for congenital muscular dystrophy. J Mol Diagn. 14(3):233-46.

Vasta V, Merritt Ii JL, Saneto RP, Hahn SH. (2012). Next-generation sequencing for mitochondrial diseases: A wide diagnostic spectrum. Pediatr Int. Apr 12. doi: 10.1111/j.1442-200X.2012.03644.x. [Epub ahead of print]

Wolf SM, Crock BN, Van Ness B, Lawrenz F, Kahn JP, Beskow LM, Cho MK, Christman MF, Green RC, Hall R, Illes J, Keane M, Knoppers BM, Koenig BA, Kohane IS, Leroy B, Maschke KJ, McGeveran W, Ossorio P, Parker LS, Petersen GM, Richardson HS, Scott JA, Terry SF, Wilfond BS, Wolf WA. (2012). Managing incidental findings and research results in genomic research involving biobanks and archived data sets. Genet Med. 14(4):361-84.

Worthey EA, Mayer AN, Syverson GD, Helbling D, Bonacci BB, Decker B, Serpe JM, Dasu T, Tschannen MR, Veith RL, Basehore MJ, Broeckel U, Tomita-Mitchell A, Arca MJ, Casper JT, Margolis DA, Bick DP, Hessner MJ, Routes JM, Verbsky JW, Jacob HJ, Dimmock DP. (2011). Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease. Genet Med. 13(3):255-62.

Websites

ACMG Policy
http://www.acmg.net/StaticContent/PPG/Clinical_Application_of_Genomic_Sequencing.pdf

ACMG Recommendations:
http://www.acmg.net/resources/policies/pol-027.pdf

CAP accreditation checklist
http://www.cap.org

FDA Meeting on Clinical NGS
http://www.fda.gov/downloads/MedicalDevices/NewsEvents/WorkshopsConferences/UCM266607.pdf
http://www.fda.gov/MedicalDevices/NewsEvents/WorkshopsConferences/ucm284442.htm

NIST Genome in a Bottle
http://www.nist.gov/mml/biochemical/biomolecular/upload/120803-Genomes-in-a-Bottle-Work-Plan.pdf

XPrize
http://genomics.xprize.org/