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Showing 1 to 12 of 48 entries
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Beyond Gene Panels: Whole Exome Sequencing for Diagnosis of Congenital Heart Disease.

Circulation. Genomic and precision medicine

Paige SL, Saha P, Priest JR.
PMID: 29555674
Circ Genom Precis Med. 2018 Mar;11(3):e002097. doi: 10.1161/CIRCGEN.118.002097.

No abstract available.

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Paige SL, Saha P, Priest JR. Beyond Gene Panels: Whole Exome Sequencing for Diagnosis of Congenital Heart Disease. Circ Genom Precis Med. 2018;11(3):e002097doi: 10.1161/CIRCGEN.118.002097.
Paige, S. L., Saha, P., & Priest, J. R. (2018). Beyond Gene Panels: Whole Exome Sequencing for Diagnosis of Congenital Heart Disease. Circulation. Genomic and precision medicine, 11(3), e002097. https://doi.org/10.1161/CIRCGEN.118.002097
Paige, Sharon L, et al. "Beyond Gene Panels: Whole Exome Sequencing for Diagnosis of Congenital Heart Disease." Circulation. Genomic and precision medicine vol. 11,3 (2018): e002097. doi: https://doi.org/10.1161/CIRCGEN.118.002097
Paige SL, Saha P, Priest JR. Beyond Gene Panels: Whole Exome Sequencing for Diagnosis of Congenital Heart Disease. Circ Genom Precis Med. 2018 Mar;11(3):e002097. doi: 10.1161/CIRCGEN.118.002097. PMID: 29555674; PMCID: PMC6049807.
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The Impact of Whole-Exome Sequencing on Kidney Disease Ontology: The Tip of the Iceberg?.

American journal of kidney diseases : the official journal of the National Kidney Foundation

Geara AS, Kallish S, Hogan JJ.
PMID: 31027884
Am J Kidney Dis. 2019 Aug;74(2):281-283. doi: 10.1053/j.ajkd.2019.03.413. Epub 2019 Apr 23.

No abstract available.

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Geara AS, Kallish S, Hogan JJ. The Impact of Whole-Exome Sequencing on Kidney Disease Ontology: The Tip of the Iceberg?. Am J Kidney Dis. 2019;74(2):281-283doi: 10.1053/j.ajkd.2019.03.413.
Geara, A. S., Kallish, S., & Hogan, J. J. (2019). The Impact of Whole-Exome Sequencing on Kidney Disease Ontology: The Tip of the Iceberg?. American journal of kidney diseases : the official journal of the National Kidney Foundation, 74(2), 281-283. https://doi.org/10.1053/j.ajkd.2019.03.413
Geara, Abdallah S, et al. "The Impact of Whole-Exome Sequencing on Kidney Disease Ontology: The Tip of the Iceberg?." American journal of kidney diseases : the official journal of the National Kidney Foundation vol. 74,2 (2019): 281-283. doi: https://doi.org/10.1053/j.ajkd.2019.03.413
Geara AS, Kallish S, Hogan JJ. The Impact of Whole-Exome Sequencing on Kidney Disease Ontology: The Tip of the Iceberg?. Am J Kidney Dis. 2019 Aug;74(2):281-283. doi: 10.1053/j.ajkd.2019.03.413. Epub 2019 Apr 23. PMID: 31027884.
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Challenges to informed consent for exome sequencing: A best-worst scaling experiment.

Journal of genetic counseling

Gore RH, Bridges JFP, Cohen JS, Biesecker BB.
PMID: 31553105
J Genet Couns. 2019 Dec;28(6):1189-1197. doi: 10.1002/jgc4.1171. Epub 2019 Sep 25.

As exome sequencing expands as a diagnostic tool, patients and providers have voiced concerns about communicating the breadth and scope of potential results when obtaining informed consent. This study aimed to understand how genetic counselors prioritize essential components of...

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Gore RH, Bridges JFP, Cohen JS, et al. Challenges to informed consent for exome sequencing: A best-worst scaling experiment. J Genet Couns. 2019;28(6):1189-1197doi: 10.1002/jgc4.1171.
Gore, R. H., Bridges, J. F. P., Cohen, J. S., & Biesecker, B. B. (2019). Challenges to informed consent for exome sequencing: A best-worst scaling experiment. Journal of genetic counseling, 28(6), 1189-1197. https://doi.org/10.1002/jgc4.1171
Gore, Rachel H, et al. "Challenges to informed consent for exome sequencing: A best-worst scaling experiment." Journal of genetic counseling vol. 28,6 (2019): 1189-1197. doi: https://doi.org/10.1002/jgc4.1171
Gore RH, Bridges JFP, Cohen JS, Biesecker BB. Challenges to informed consent for exome sequencing: A best-worst scaling experiment. J Genet Couns. 2019 Dec;28(6):1189-1197. doi: 10.1002/jgc4.1171. Epub 2019 Sep 25. PMID: 31553105; PMCID: PMC7422696.
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GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form.

Bioinformatics (Oxford, England)

Meng Q, Ochoa I, Hernaez M.
PMID: 32609343
Bioinformatics. 2020 Sep 15;36(18):4810-4812. doi: 10.1093/bioinformatics/btaa604.

MOTIVATION: Sequencing data are often summarized at different annotation levels for further analysis, generally using the general feature format (GFF) or its descendants, gene transfer format (GTF) and GFF3. Existing utilities for accessing these files, like gffutils and gffread,...

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Meng Q, Ochoa I, Hernaez M. GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form. Bioinformatics. 2020;36(18):4810-4812doi: 10.1093/bioinformatics/btaa604.
Meng, Q., Ochoa, I., & Hernaez, M. (2020). GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form. Bioinformatics (Oxford, England), 36(18), 4810-4812. https://doi.org/10.1093/bioinformatics/btaa604
Meng, Qingxi, et al. "GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form." Bioinformatics (Oxford, England) vol. 36,18 (2020): 4810-4812. doi: https://doi.org/10.1093/bioinformatics/btaa604
Meng Q, Ochoa I, Hernaez M. GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form. Bioinformatics. 2020 Sep 15;36(18):4810-4812. doi: 10.1093/bioinformatics/btaa604. PMID: 32609343.
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RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.

Bioinformatics (Oxford, England)

Hagiwara K, Ding L, Edmonson MN, Rice SV, Newman S, Easton J, Dai J, Meshinchi S, Ries RE, Rusch M, Zhang J.
PMID: 31593214
Bioinformatics. 2020 Mar 01;36(5):1382-1390. doi: 10.1093/bioinformatics/btz753.

MOTIVATION: Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome.RESULTS:...

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Hagiwara K, Ding L, Edmonson MN, et al. RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics. 2020;36(5):1382-1390doi: 10.1093/bioinformatics/btz753.
Hagiwara, K., Ding, L., Edmonson, M. N., Rice, S. V., Newman, S., Easton, J., Dai, J., Meshinchi, S., Ries, R. E., Rusch, M., & Zhang, J. (2020). RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics (Oxford, England), 36(5), 1382-1390. https://doi.org/10.1093/bioinformatics/btz753
Hagiwara, Kohei, et al. "RNAIndel: discovering somatic coding indels from tumor RNA-Seq data." Bioinformatics (Oxford, England) vol. 36,5 (2020): 1382-1390. doi: https://doi.org/10.1093/bioinformatics/btz753
Hagiwara K, Ding L, Edmonson MN, Rice SV, Newman S, Easton J, Dai J, Meshinchi S, Ries RE, Rusch M, Zhang J. RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics. 2020 Mar 01;36(5):1382-1390. doi: 10.1093/bioinformatics/btz753. PMID: 31593214; PMCID: PMC7523641.
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Availability and funding of clinical genomic sequencing globally.

BMJ global health

Phillips KA, Douglas MP, Wordsworth S, Buchanan J, Marshall DA.
PMID: 33574068
BMJ Glob Health. 2021 Feb;6(2). doi: 10.1136/bmjgh-2020-004415.

The emergence of next-generation genomic sequencing (NGS) tests for use in clinical care has generated widespread interest around the globe, but little is known about the availability and funding of these tests worldwide. We examined NGS availability across world...

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Phillips KA, Douglas MP, Wordsworth S, et al. Availability and funding of clinical genomic sequencing globally. BMJ Glob Health. 2021;6(2)doi: 10.1136/bmjgh-2020-004415.
Phillips, K. A., Douglas, M. P., Wordsworth, S., Buchanan, J., & Marshall, D. A. (2021). Availability and funding of clinical genomic sequencing globally. BMJ global health, 6(2), . https://doi.org/10.1136/bmjgh-2020-004415
Phillips, Kathryn A, et al. "Availability and funding of clinical genomic sequencing globally." BMJ global health vol. 6,2 (2021). doi: https://doi.org/10.1136/bmjgh-2020-004415
Phillips KA, Douglas MP, Wordsworth S, Buchanan J, Marshall DA. Availability and funding of clinical genomic sequencing globally. BMJ Glob Health. 2021 Feb;6(2). doi: 10.1136/bmjgh-2020-004415. PMID: 33574068; PMCID: PMC7880109.
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Exome sequencing of family trios from the National Birth Defects Prevention Study: Tapping into a rich resource of genetic and environmental data.

Birth defects research

Jenkins MM, Almli LM, Pangilinan F, Chong JX, Blue EE, Shapira SK, White J, McGoldrick D, Smith JD, Mullikin JC, Bean CJ, Nembhard WN, Lou XY, Shaw GM, Romitti PA, Keppler-Noreuil K, Yazdy MM, Kay DM, Carter TC, Olshan AF, Moore KJ, Nascone-Yoder N, Finnell RH, Lupo PJ, Feldkamp ML, Nickerson DA, Bamshad MJ, Brody LC, Reefhuis J.
PMID: 31328417
Birth Defects Res. 2019 Dec 01;111(20):1618-1632. doi: 10.1002/bdr2.1554. Epub 2019 Jul 21.

BACKGROUND: The National Birth Defects Prevention Study (NBDPS) is a multisite, population-based, case-control study of genetic and nongenetic risk factors for major structural birth defects. Eligible women had a pregnancy affected by a birth defect or a liveborn child...

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Jenkins MM, Almli LM, Pangilinan F, et al. Exome sequencing of family trios from the National Birth Defects Prevention Study: Tapping into a rich resource of genetic and environmental data. Birth Defects Res. 2019;111(20):1618-1632doi: 10.1002/bdr2.1554.
Jenkins, M. M., Almli, L. M., Pangilinan, F., Chong, J. X., Blue, E. E., Shapira, S. K., White, J., McGoldrick, D., Smith, J. D., Mullikin, J. C., Bean, C. J., Nembhard, W. N., Lou, X. Y., Shaw, G. M., Romitti, P. A., Keppler-Noreuil, K., Yazdy, M. M., Kay, D. M., Carter, T. C., Olshan, A. F., Moore, K. J., Nascone-Yoder, N., Finnell, R. H., Lupo, P. J., Feldkamp, M. L., Nickerson, D. A., Bamshad, M. J., Brody, L. C., Reefhuis, J. (2019). Exome sequencing of family trios from the National Birth Defects Prevention Study: Tapping into a rich resource of genetic and environmental data. Birth defects research, 111(20), 1618-1632. https://doi.org/10.1002/bdr2.1554
Jenkins, Mary M, et al. "Exome sequencing of family trios from the National Birth Defects Prevention Study: Tapping into a rich resource of genetic and environmental data." Birth defects research vol. 111,20 (2019): 1618-1632. doi: https://doi.org/10.1002/bdr2.1554
Jenkins MM, Almli LM, Pangilinan F, Chong JX, Blue EE, Shapira SK, White J, McGoldrick D, Smith JD, Mullikin JC, Bean CJ, Nembhard WN, Lou XY, Shaw GM, Romitti PA, Keppler-Noreuil K, Yazdy MM, Kay DM, Carter TC, Olshan AF, Moore KJ, Nascone-Yoder N, Finnell RH, Lupo PJ, Feldkamp ML, Nickerson DA, Bamshad MJ, Brody LC, Reefhuis J. Exome sequencing of family trios from the National Birth Defects Prevention Study: Tapping into a rich resource of genetic and environmental data. Birth Defects Res. 2019 Dec 01;111(20):1618-1632. doi: 10.1002/bdr2.1554. Epub 2019 Jul 21. PMID: 31328417; PMCID: PMC6889076.
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Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis.

Genetics in medicine : official journal of the American College of Medical Genetics

Alaimo JT, Glinton KE, Liu N, Xiao J, Yang Y, Reid Sutton V, Elsea SH.
PMID: 32439973
Genet Med. 2020 Sep;22(9):1560-1566. doi: 10.1038/s41436-020-0827-0. Epub 2020 May 22.

PURPOSE: A primary barrier to improving exome sequencing diagnostic rates is the interpretation of variants of uncertain clinical significance. We aimed to determine the contribution of integrated untargeted metabolomics in the analysis of exome sequencing data by retrospective analysis...

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Alaimo JT, Glinton KE, Liu N, et al. Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis. Genet Med. 2020;22(9):1560-1566doi: 10.1038/s41436-020-0827-0.
Alaimo, J. T., Glinton, K. E., Liu, N., Xiao, J., Yang, Y., Reid Sutton, V., & Elsea, S. H. (2020). Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis. Genetics in medicine : official journal of the American College of Medical Genetics, 22(9), 1560-1566. https://doi.org/10.1038/s41436-020-0827-0
Alaimo, Joseph T, et al. "Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis." Genetics in medicine : official journal of the American College of Medical Genetics vol. 22,9 (2020): 1560-1566. doi: https://doi.org/10.1038/s41436-020-0827-0
Alaimo JT, Glinton KE, Liu N, Xiao J, Yang Y, Reid Sutton V, Elsea SH. Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis. Genet Med. 2020 Sep;22(9):1560-1566. doi: 10.1038/s41436-020-0827-0. Epub 2020 May 22. PMID: 32439973; PMCID: PMC7483344.
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MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations.

Methods in molecular biology (Clifton, N.J.)

Bolger M, Schwacke R, Usadel B.
PMID: 34448161
Methods Mol Biol. 2021;2354:195-212. doi: 10.1007/978-1-0716-1609-3_9.

Plant omics research has advanced to the stage where it is feasible to generate data from multiple samples and multiple time points to gain insight into biological processes. This impressive array of data can prove challenging to interpret. In...

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Bolger M, Schwacke R, Usadel B. MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations. Methods Mol Biol. 2021;2354:195-212doi: 10.1007/978-1-0716-1609-3_9.
Bolger, M., Schwacke, R., & Usadel, B. (2021). MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations. Methods in molecular biology (Clifton, N.J.), 2354195-212. https://doi.org/10.1007/978-1-0716-1609-3_9
Bolger, Marie, et al. "MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations." Methods in molecular biology (Clifton, N.J.) vol. 2354 (2021): 195-212. doi: https://doi.org/10.1007/978-1-0716-1609-3_9
Bolger M, Schwacke R, Usadel B. MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations. Methods Mol Biol. 2021;2354:195-212. doi: 10.1007/978-1-0716-1609-3_9. PMID: 34448161.
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Integration of exome sequencing and metabolic evaluation for the diagnosis of children with urolithiasis.

World journal of urology

Zhao Y, Fang X, Fan Y, Sun Y, He L, Xu M, Xu G, Li Y, Huang Y, Yu Y, Geng H.
PMID: 32936332
World J Urol. 2021 Jul;39(7):2759-2765. doi: 10.1007/s00345-020-03449-9. Epub 2020 Sep 16.

PURPOSE: To investigate the prevalence of inherited causes in an early onset urolithiasis cohort and each metabolic subgroup.METHODS: A retrospective analysis of both metabolic and genomic data was performed for the first 105 pediatric urolithiasis patients who underwent exome...

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Zhao Y, Fang X, Fan Y, et al. Integration of exome sequencing and metabolic evaluation for the diagnosis of children with urolithiasis. World J Urol. 2020;39(7):2759-2765doi: 10.1007/s00345-020-03449-9.
Zhao, Y., Fang, X., Fan, Y., Sun, Y., He, L., Xu, M., Xu, G., Li, Y., Huang, Y., Yu, Y., & Geng, H. (2021). Integration of exome sequencing and metabolic evaluation for the diagnosis of children with urolithiasis. World journal of urology, 39(7), 2759-2765. https://doi.org/10.1007/s00345-020-03449-9
Zhao, Yining, et al. "Integration of exome sequencing and metabolic evaluation for the diagnosis of children with urolithiasis." World journal of urology vol. 39,7 (2021): 2759-2765. doi: https://doi.org/10.1007/s00345-020-03449-9
Zhao Y, Fang X, Fan Y, Sun Y, He L, Xu M, Xu G, Li Y, Huang Y, Yu Y, Geng H. Integration of exome sequencing and metabolic evaluation for the diagnosis of children with urolithiasis. World J Urol. 2021 Jul;39(7):2759-2765. doi: 10.1007/s00345-020-03449-9. Epub 2020 Sep 16. PMID: 32936332.
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Benchmarking germline CNV calling tools from exome sequencing data.

Scientific reports

Gordeeva V, Sharova E, Babalyan K, Sultanov R, Govorun VM, Arapidi G.
PMID: 34257369
Sci Rep. 2021 Jul 13;11(1):14416. doi: 10.1038/s41598-021-93878-2.

Whole-exome sequencing is an attractive alternative to microarray analysis because of the low cost and potential ability to detect copy number variations (CNV) of various sizes (from 1-2 exons to several Mb). Previous comparison of the most popular CNV...

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Gordeeva V, Sharova E, Babalyan K, et al. Benchmarking germline CNV calling tools from exome sequencing data. Sci Rep. 2021;11(1):14416doi: 10.1038/s41598-021-93878-2.
Gordeeva, V., Sharova, E., Babalyan, K., Sultanov, R., Govorun, V. M., & Arapidi, G. (2021). Benchmarking germline CNV calling tools from exome sequencing data. Scientific reports, 11(1), 14416. https://doi.org/10.1038/s41598-021-93878-2
Gordeeva, Veronika, et al. "Benchmarking germline CNV calling tools from exome sequencing data." Scientific reports vol. 11,1 (2021): 14416. doi: https://doi.org/10.1038/s41598-021-93878-2
Gordeeva V, Sharova E, Babalyan K, Sultanov R, Govorun VM, Arapidi G. Benchmarking germline CNV calling tools from exome sequencing data. Sci Rep. 2021 Jul 13;11(1):14416. doi: 10.1038/s41598-021-93878-2. PMID: 34257369; PMCID: PMC8277855.
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Impact of concurrency on the performance of a whole exome sequencing pipeline.

BMC bioinformatics

Dall'Olio D, Curti N, Fonzi E, Sala C, Remondini D, Castellani G, Giampieri E.
PMID: 33563206
BMC Bioinformatics. 2021 Feb 09;22(1):60. doi: 10.1186/s12859-020-03780-3.

BACKGROUND: Current high-throughput technologies-i.e. whole genome sequencing, RNA-Seq, ChIP-Seq, etc.-generate huge amounts of data and their usage gets more widespread with each passing year. Complex analysis pipelines involving several computationally-intensive steps have to be applied on an increasing number...

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Dall'Olio D, Curti N, Fonzi E, et al. Impact of concurrency on the performance of a whole exome sequencing pipeline. BMC Bioinformatics. 2021;22(1):60doi: 10.1186/s12859-020-03780-3.
Dall'Olio, D., Curti, N., Fonzi, E., Sala, C., Remondini, D., Castellani, G., & Giampieri, E. (2021). Impact of concurrency on the performance of a whole exome sequencing pipeline. BMC bioinformatics, 22(1), 60. https://doi.org/10.1186/s12859-020-03780-3
Dall'Olio, Daniele, et al. "Impact of concurrency on the performance of a whole exome sequencing pipeline." BMC bioinformatics vol. 22,1 (2021): 60. doi: https://doi.org/10.1186/s12859-020-03780-3
Dall'Olio D, Curti N, Fonzi E, Sala C, Remondini D, Castellani G, Giampieri E. Impact of concurrency on the performance of a whole exome sequencing pipeline. BMC Bioinformatics. 2021 Feb 09;22(1):60. doi: 10.1186/s12859-020-03780-3. PMID: 33563206; PMCID: PMC7874478.
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Showing 1 to 12 of 48 entries