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Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

HGG advances

Chen H, Majumdar A, Wang L, Kar S, Brown KM, Feng H, Turman C, Dennis J, Easton D, Michailidou K, Simard J, Bishop T, Cheng IC, Huyghe JR, Schmit SL, O'Mara TA, Spurdle AB, Gharahkhani P, Schumacher J, Jankowski J, Gocke I, Bondy ML, Houlston RS, Jenkins RB, Melin B, Lesseur C, Ness AR, Diergaarde B, Olshan AF, Amos CI, Christiani DC, Landi MT, McKay JD, Brossard M, Iles MM, Law MH, MacGregor S, Beesley J, Jones MR, Tyrer J, Winham SJ, Klein AP, Petersen G, Li D, Wolpin BM, Eeles RA, Haiman CA, Kote-Jarai Z, Schumacher FR, Brennan P, Chanock SJ, Gaborieau V, Purdue MP, Pharoah P, Hung RJ, Amundadottir LT, Kraft P, Pasaniuc B, Lindström S.
PMID: 34355204
HGG Adv. 2021 Jul 08;2(3). doi: 10.1016/j.xhgg.2021.100041. Epub 2021 Jun 12.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we...

Cite
Chen H, Majumdar A, Wang L, et al. Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals. HGG Adv. 2021;2(3)doi: 10.1016/j.xhgg.2021.100041.
Chen, H., Majumdar, A., Wang, L., Kar, S., Brown, K. M., Feng, H., Turman, C., Dennis, J., Easton, D., Michailidou, K., Simard, J., Bishop, T., Cheng, I. C., Huyghe, J. R., Schmit, S. L., O'Mara, T. A., Spurdle, A. B., Gharahkhani, P., Schumacher, J., Jankowski, J., Gocke, I., Bondy, M. L., Houlston, R. S., Jenkins, R. B., Melin, B., Lesseur, C., Ness, A. R., Diergaarde, B., Olshan, A. F., Amos, C. I., Christiani, D. C., Landi, M. T., McKay, J. D., Brossard, M., Iles, M. M., Law, M. H., MacGregor, S., Beesley, J., Jones, M. R., Tyrer, J., Winham, S. J., Klein, A. P., Petersen, G., Li, D., Wolpin, B. M., Eeles, R. A., Haiman, C. A., Kote-Jarai, Z., Schumacher, F. R., Brennan, P., Chanock, S. J., Gaborieau, V., Purdue, M. P., Pharoah, P., Hung, R. J., Amundadottir, L. T., Kraft, P., Pasaniuc, B., & Lindström, S. (2021). Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals. HGG advances, 2(3), . https://doi.org/10.1016/j.xhgg.2021.100041
Chen, Hongjie, et al. "Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals." HGG advances vol. 2,3 (2021). doi: https://doi.org/10.1016/j.xhgg.2021.100041
Chen H, Majumdar A, Wang L, Kar S, Brown KM, Feng H, Turman C, Dennis J, Easton D, Michailidou K, Simard J, Bishop T, Cheng IC, Huyghe JR, Schmit SL, O'Mara TA, Spurdle AB, Gharahkhani P, Schumacher J, Jankowski J, Gocke I, Bondy ML, Houlston RS, Jenkins RB, Melin B, Lesseur C, Ness AR, Diergaarde B, Olshan AF, Amos CI, Christiani DC, Landi MT, McKay JD, Brossard M, Iles MM, Law MH, MacGregor S, Beesley J, Jones MR, Tyrer J, Winham SJ, Klein AP, Petersen G, Li D, Wolpin BM, Eeles RA, Haiman CA, Kote-Jarai Z, Schumacher FR, Brennan P, Chanock SJ, Gaborieau V, Purdue MP, Pharoah P, Hung RJ, Amundadottir LT, Kraft P, Pasaniuc B, Lindström S. Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals. HGG Adv. 2021 Jul 08;2(3). doi: 10.1016/j.xhgg.2021.100041. Epub 2021 Jun 12. PMID: 34355204; PMCID: PMC8336922.
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The Use Of Genetic Correlation And Mendelian Randomization Studies To Increase Our Understanding of Relationships Between Complex Traits.

Current epidemiology reports

Kraft P, Chen H, Lindström S.
PMID: 33552841
Curr Epidemiol Rep. 2020 Jun;7(2):104-112. doi: 10.1007/s40471-020-00233-6. Epub 2020 May 16.

PURPOSE OF THE REVIEW: Increasing access to large-scale genetic datasets in population-based studies allows for genetic association studies as a means to examine previously known and novel relationships among complex traits. In this review, we discuss two widely used...

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Kraft P, Chen H, Lindström S. The Use Of Genetic Correlation And Mendelian Randomization Studies To Increase Our Understanding of Relationships Between Complex Traits. Curr Epidemiol Rep. 2020;7(2):104-112doi: 10.1007/s40471-020-00233-6.
Kraft, P., Chen, H., & Lindström, S. (2020). The Use Of Genetic Correlation And Mendelian Randomization Studies To Increase Our Understanding of Relationships Between Complex Traits. Current epidemiology reports, 7(2), 104-112. https://doi.org/10.1007/s40471-020-00233-6
Kraft, Peter, et al. "The Use Of Genetic Correlation And Mendelian Randomization Studies To Increase Our Understanding of Relationships Between Complex Traits." Current epidemiology reports vol. 7,2 (2020): 104-112. doi: https://doi.org/10.1007/s40471-020-00233-6
Kraft P, Chen H, Lindström S. The Use Of Genetic Correlation And Mendelian Randomization Studies To Increase Our Understanding of Relationships Between Complex Traits. Curr Epidemiol Rep. 2020 Jun;7(2):104-112. doi: 10.1007/s40471-020-00233-6. Epub 2020 May 16. PMID: 33552841; PMCID: PMC7863746.
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Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

HGG advances

Chen H, Majumdar A, Wang L, Kar S, Brown KM, Feng H, Turman C, Dennis J, Easton D, Michailidou K, Simard J, Bishop T, Cheng IC, Huyghe JR, Schmit SL, O'Mara TA, Spurdle AB, Gharahkhani P, Schumacher J, Jankowski J, Gocke I, Bondy ML, Houlston RS, Jenkins RB, Melin B, Lesseur C, Ness AR, Diergaarde B, Olshan AF, Amos CI, Christiani DC, Landi MT, McKay JD, Brossard M, Iles MM, Law MH, MacGregor S, Beesley J, Jones MR, Tyrer J, Winham SJ, Klein AP, Petersen G, Li D, Wolpin BM, Eeles RA, Haiman CA, Kote-Jarai Z, Schumacher FR, Brennan P, Chanock SJ, Gaborieau V, Purdue MP, Pharoah P, Hung RJ, Amundadottir LT, Kraft P, Pasaniuc B, Lindström S.
PMID: 34355204
HGG Adv. 2021 Jul 08;2(3). doi: 10.1016/j.xhgg.2021.100041. Epub 2021 Jun 12.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we...

Cite
Chen H, Majumdar A, Wang L, et al. Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals. HGG Adv. 2021;2(3)doi: 10.1016/j.xhgg.2021.100041.
Chen, H., Majumdar, A., Wang, L., Kar, S., Brown, K. M., Feng, H., Turman, C., Dennis, J., Easton, D., Michailidou, K., Simard, J., Bishop, T., Cheng, I. C., Huyghe, J. R., Schmit, S. L., O'Mara, T. A., Spurdle, A. B., Gharahkhani, P., Schumacher, J., Jankowski, J., Gocke, I., Bondy, M. L., Houlston, R. S., Jenkins, R. B., Melin, B., Lesseur, C., Ness, A. R., Diergaarde, B., Olshan, A. F., Amos, C. I., Christiani, D. C., Landi, M. T., McKay, J. D., Brossard, M., Iles, M. M., Law, M. H., MacGregor, S., Beesley, J., Jones, M. R., Tyrer, J., Winham, S. J., Klein, A. P., Petersen, G., Li, D., Wolpin, B. M., Eeles, R. A., Haiman, C. A., Kote-Jarai, Z., Schumacher, F. R., Brennan, P., Chanock, S. J., Gaborieau, V., Purdue, M. P., Pharoah, P., Hung, R. J., Amundadottir, L. T., Kraft, P., Pasaniuc, B., & Lindström, S. (2021). Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals. HGG advances, 2(3), . https://doi.org/10.1016/j.xhgg.2021.100041
Chen, Hongjie, et al. "Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals." HGG advances vol. 2,3 (2021). doi: https://doi.org/10.1016/j.xhgg.2021.100041
Chen H, Majumdar A, Wang L, Kar S, Brown KM, Feng H, Turman C, Dennis J, Easton D, Michailidou K, Simard J, Bishop T, Cheng IC, Huyghe JR, Schmit SL, O'Mara TA, Spurdle AB, Gharahkhani P, Schumacher J, Jankowski J, Gocke I, Bondy ML, Houlston RS, Jenkins RB, Melin B, Lesseur C, Ness AR, Diergaarde B, Olshan AF, Amos CI, Christiani DC, Landi MT, McKay JD, Brossard M, Iles MM, Law MH, MacGregor S, Beesley J, Jones MR, Tyrer J, Winham SJ, Klein AP, Petersen G, Li D, Wolpin BM, Eeles RA, Haiman CA, Kote-Jarai Z, Schumacher FR, Brennan P, Chanock SJ, Gaborieau V, Purdue MP, Pharoah P, Hung RJ, Amundadottir LT, Kraft P, Pasaniuc B, Lindström S. Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals. HGG Adv. 2021 Jul 08;2(3). doi: 10.1016/j.xhgg.2021.100041. Epub 2021 Jun 12. PMID: 34355204; PMCID: PMC8336922.
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BATMAN: Fast and Accurate Integration of Single-Cell RNA-Seq Datasets via Minimum-Weight Matching.

iScience

Mandric I, Hill BL, Freund MK, Thompson M, Halperin E.
PMID: 32504875
iScience. 2020 Jun 26;23(6):101185. doi: 10.1016/j.isci.2020.101185. Epub 2020 May 20.

Single-cell RNA-sequencing (scRNA-seq) is a set of technologies used to profile gene expression at the level of individual cells. Although the throughput of scRNA-seq experiments is steadily growing in terms of the number of cells, large datasets are not...

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Mandric I, Hill BL, Freund MK, et al. BATMAN: Fast and Accurate Integration of Single-Cell RNA-Seq Datasets via Minimum-Weight Matching. iScience. 2020;23(6):101185doi: 10.1016/j.isci.2020.101185.
Mandric, I., Hill, B. L., Freund, M. K., Thompson, M., & Halperin, E. (2020). BATMAN: Fast and Accurate Integration of Single-Cell RNA-Seq Datasets via Minimum-Weight Matching. iScience, 23(6), 101185. https://doi.org/10.1016/j.isci.2020.101185
Mandric, Igor, et al. "BATMAN: Fast and Accurate Integration of Single-Cell RNA-Seq Datasets via Minimum-Weight Matching." iScience vol. 23,6 (2020): 101185. doi: https://doi.org/10.1016/j.isci.2020.101185
Mandric I, Hill BL, Freund MK, Thompson M, Halperin E. BATMAN: Fast and Accurate Integration of Single-Cell RNA-Seq Datasets via Minimum-Weight Matching. iScience. 2020 Jun 26;23(6):101185. doi: 10.1016/j.isci.2020.101185. Epub 2020 May 20. PMID: 32504875; PMCID: PMC7276436.
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Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits.

PLoS computational biology

Johnson R, Burch KS, Hou K, Paciuc M, Pasaniuc B, Sankararaman S.
PMID: 34673766
PLoS Comput Biol. 2021 Oct 21;17(10):e1009483. doi: 10.1371/journal.pcbi.1009483. eCollection 2021 Oct.

The number of variants that have a non-zero effect on a trait (i.e. polygenicity) is a fundamental parameter in the study of the genetic architecture of a complex trait. Although many previous studies have investigated polygenicity at a genome-wide...

Cite
Johnson R, Burch KS, Hou K, et al. Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits. PLoS Comput Biol. 2021;17(10):e1009483doi: 10.1371/journal.pcbi.1009483.
Johnson, R., Burch, K. S., Hou, K., Paciuc, M., Pasaniuc, B., & Sankararaman, S. (2021). Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits. PLoS computational biology, 17(10), e1009483. https://doi.org/10.1371/journal.pcbi.1009483
Johnson, Ruth, et al. "Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits." PLoS computational biology vol. 17,10 (2021): e1009483. doi: https://doi.org/10.1371/journal.pcbi.1009483
Johnson R, Burch KS, Hou K, Paciuc M, Pasaniuc B, Sankararaman S. Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits. PLoS Comput Biol. 2021 Oct 21;17(10):e1009483. doi: 10.1371/journal.pcbi.1009483. eCollection 2021 Oct. PMID: 34673766; PMCID: PMC8562817.
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Showing 1 to 5 of 5 entries