Search

Your search keyword '"KELLEHER J"' showing total 1,322 results
Start Over Author "KELLEHER J"
1,322 results on '"KELLEHER J"'

1. Investigation of α-Ti plastic anisotropy under thermomechanical loadings: temperature influence on deformation mechanisms

Author

Agbovi K. E., Fajoui J., Girault B., Gloaguen D., Kabra S., Kelleher J., and Kockelmann W.

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

In situ neutron diffraction method has been used to investigate deformation mechanisms (slip and twinning deformation modes) during uniaxial tensile tests of extruded a-titanium alloy at room temperature, 100 and 300 °C. For this purpose, the prediction of an Elasto-Plastic Self-Consistent (EPSC) model was compared with the experimental data. Results show that there is a good agreement between the simulations and neutron diffraction measurements. The EPSC model enables realistic predictions of not only the elastic lattice strains developed in variously oriented grain families but also the macroscopic stress-strain response within the bulk material.

Published
2020
Full Text
View/download PDF

3. Electronic structure of semiconductor nanostructures: A modified localization landscape theory

Author

Chaudhuri, D., Kelleher, J. C., O'Brien, M. R., O'Reilly, E. P., and Schulz, S.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

In this paper we present a modified localization landscape theory to calculate localized/confined electron and hole states and the corresponding energy eigenvalues without solving a (large) eigenvalue problem. We motivate and demonstrate the benefit of solving $\hat{H}^2u=1$ in the modified localization landscape theory in comparison to $\hat{H}u=1$, solved in the localization landscape theory. We detail the advantages by fully analytic considerations before targeting the numerical calculation of electron and hole states and energies in III-N heterostructures. We further discuss how the solution of $\hat{H}^2u=1$ is used to extract an effective potential $W$ that is comparable to the effective potential obtained from $\hat{H}u=1$, ensuring that it can for instance be used to introduce quantum corrections to drift-diffusion transport calculations. Overall, we show that the proposed modified localization landscape theory keeps all the benefits of the recently introduced localization landscape theory but further improves factors such as convergence of the calculated energies and the robustness of the method against the chosen integration region for $u$ to obtain the corresponding energies. We find that this becomes especially important for here studied $c$-plane InGaN/GaN quantum wells with higher In contents. All these features make the proposed approach very attractive for calculation of localized states in highly disordered systems, where partitioning the systems into different subregions can be difficult., Comment: 14 pages, 6 figures

Published
2019
Full Text
View/download PDF

4. Design of a High Strength, High Ductility 12 wt% Mn Medium Manganese Steel With Hierarchical Deformation Behaviour

Author

Kwok, T W J, Rahman, K M, Xu, X, Bantounas, I, Kelleher, J F, Daswari, S, Alam, T, Banerjee, R, and Dye, D

Subjects
Condensed Matter - Materials Science
Abstract

A novel medium Mn steel of composition Fe-12Mn-4.8Al-2Si-0.32C-0.3V was manufactured with 1.09 GPa yield strength, 1.26 GPa tensile strength and 54% elongation. The thermomechanical process route was designed to be industrially translatable and consists of hot and then warm rolling before a 30 min intercritical anneal. The resulting microstructure comprised of coarse elongated austenite grains in the rolling direction surrounded by necklace layers of fine austenite and ferrite grains. The tensile behaviour was investigated by in-situ neutron diffraction and the evolution of microstructure studied with Electron Backscattered Diffraction (EBSD). It was found that the coarse austenite grains contributed to the first stage of strain hardening by transforming into martensite and the fine austenite necklace grains contributed to the second stage of strain hardening by a mixture of twinning and transformation induced plasticity (TWIP and TRIP) mechanisms. This hierarchical deformation behaviour contributed to the exceptional ductility of this steel., Comment: Updated on resubmission, minor clarifications

Published
2019
Full Text
View/download PDF

7. Spectral neutron tomography

Author

Tran, K.V., Woracek, R., Kardjilov, N., Markötter, H., Hilger, A., Kockelmann, W., Kelleher, J., Puplampu, S.B., Penumadu, D., Tremsin, A.S., Banhart, J., and Manke, I.

Published
2021
Full Text
View/download PDF

16. The urgency of transforming the Midwestern U.S. landscape into more than corn and soybean

Author

Prokopy, Linda S., Gramig, Benjamin M., Bower, Alisha, Church, Sarah P., Ellison, Brenna, Gassman, Philip W., Genskow, Ken, Gucker, Douglas, Hallett, Steve G., Hill, Jason, Hunt, Natalie, Johnson, Kris A., Kaplan, Ian, Kelleher, J. Paul, Kok, Hans, Komp, Michael, Lammers, Peter, LaRose, Sarah, Liebman, Matthew, Margenot, Andrew, Mulla, David, O’Donnell, Michael J., Peimer, Alex W., Reaves, Elizabeth, Salazar, Kara, Schelly, Chelsea, Schilling, Keith, Secchi, Silvia, Spaulding, Aslihan D., Swenson, David, Thompson, Aaron W., and Ulrich-Schad, Jessica D.

Published
2020
Full Text
View/download PDF

25. Bayesian inference of ancestral recombination graphs

Author

Kosakovsky Pond, SL, Mahmoudi, A, Koskela, J, Kelleher, J, Chan, Y-B, Balding, D, Kosakovsky Pond, SL, Mahmoudi, A, Koskela, J, Kelleher, J, Chan, Y-B, and Balding, D

Abstract

We present a novel algorithm, implemented in the software ARGinfer, for probabilistic inference of the Ancestral Recombination Graph under the Coalescent with Recombination. Our Markov Chain Monte Carlo algorithm takes advantage of the Succinct Tree Sequence data structure that has allowed great advances in simulation and point estimation, but not yet probabilistic inference. Unlike previous methods, which employ the Sequentially Markov Coalescent approximation, ARGinfer uses the Coalescent with Recombination, allowing more accurate inference of key evolutionary parameters. We show using simulations that ARGinfer can accurately estimate many properties of the evolutionary history of the sample, including the topology and branch lengths of the genealogical tree at each sequence site, and the times and locations of mutation and recombination events. ARGinfer approximates posterior probability distributions for these and other quantities, providing interpretable assessments of uncertainty that we show to be well calibrated. ARGinfer is currently limited to tens of DNA sequences of several hundreds of kilobases, but has scope for further computational improvements to increase its applicability.

Published
2022

26. Who is at risk of death from nephrectomy? An analysis of thirty‐day mortality after 21 380 nephrectomies in 3 years of the British Association of Urological Surgeons (BAUS) National Nephrectomy Audit

Author

Fernando, Archie, Fowler, Sarah, Van Hemelrijck, Mieke, OʼBrien, Tim, Abbasi, Z., Adamson, A. S., Addla, S. K., Adeyoju, A. A., Adshead, J. M., Afzal, N., Aho, T. F., Akhtar, M., Al‐Akraa, M., Al‐Sudani, M., Alam, A., Allan, J., Almond, D. J., Anderson, C. J., Andrews, S. J., Apakama, I., Armitage, T., Armitage, J., Awsare, N., Ayres, B., Banerjee, G. K., Barber, N. J., Barua, J. M., Basu, S., Bdesha, A. S., Beacock, C. J. M., Beatty, J., O Beck, R., Belal, M., Bell, C. R. W., Bhanot, S. M., Bhatt, R., Bhatti, A., Biyani, C. S., Blacker, A. J., Blades, R. A., Blake, C., Blake‐James, B., Boddy, J., Bromage, S. J., Bromwich, E., Brown, C., Browning, A. J., Bryan, N. P., Burgess, N. A., Burns‐Cox, N., Butterworth, P. C., Bycroft, J., Calleary, J. G., Calvert, R. C., Campbell, I., Campbell, C. A., Cannon, A., Carter, P. G., Carter, C. J. M., Cartledge, J. J., Casey, R., Chakravarti, A., Challacombe, B., Chandrasekharan, S., Chappell, B. G., Chaudry, A., Chen, T. F., Cherian, J., Choi, W. H., Chow, K., Clavijo Eisele, J., Cliff, A. M., Cohen, N. P., Cole, O. J., Collins, J., Connolly, S., Cooke, P. W., Cooksey, G., Cornaby, A. J., Cornford, P. A., Corr, J. G., Coulthard, R., Cranston, D. W., Cresswell, J., Crundwell, M. C., Cutinha, P. E., Cynk, M., Daruwala, P. D., Dasgupta, P., Datta, S. N., Davenport, K., de Bolla, A. R., Devarajan, R., Dickerson, D. A. G., Dickinson, A. J., Doherty, A. P., Donaldson, P. J., Dudderidge, T., Dyer, J., Eaton, J., Eddy, B., Eden, C. G., Elsaghir, M., Evans, S. D., Fiala, R., Fordham, M. V. P., Foster, M. C., French, A. J., Frymann, R. J., Gall, Z. J., Gallegos, C. R. R., Gana, H. B. Y., Garnett, S., Ghei, M., Gibbons, N., Gilbert, H. W., Gillatt, D. A., Glackin, A., Godbole, H. C., Golash, A., Goodman, C. M., Gowardhan, B., Green, J. S. A., Griffiths, T. R. L., Gujral, S., Gunendran, T., Hagan, C. M., Haldar, N., Hanbury, D. C., Harney, J., Hasan, S. T., Hawkyard, S. J., Hayes, M. C., Haynes, M. D., Henderson, A., Hicks, J. A., Hindley, R. G., Hodgson, D. J., Hotston, M., Howell, G. P., Hrouda, D., Hughes, O. D. M., Hunter‐Campbell, P., Ilie, C., Issa, R., Jain, S., Jain, A., Janjua, K. S., Javle, P., Johnson, P., Johnson, M. I., Jones, A., Joshi, H., Joyce, A. D., Kanaga‐Sundaram, S., Karim, O. M. A., Keeley, F. X., Kelkar, A., Kelleher, J. P., Khan, A., Khattak, A. Q., Khoubehi, B., Kimuli, M., Kirollos, M. M., Kockelbergh, R. C., Kooiman, G., Koupparis, A., Kumar, P., Kynaston, H. G., Laniado, M. E., Larner, T., Latif, Z., Lau, M. W., le Roux, P. J., Leung, S., Leveckis, J., Lewis, G., Liston, T. G., Lockyer, C. R. W., Lodge, R. N., Luscombe, C. J., Lynch, M., Lynch, C., Lynn, N. N. K., MacDermott, J. P., Mackie, S., Madaan, S., Maddineni, S.B., Maheshkumar, P., Makar, A. A., Makunde, J. T., Manikandan, R., Mann, G. S., Mantle, M., Mark, I. R., Matanhelia, S. S., McCabe, J., McClinton, S., McFarlane, J. P., McInerney, P. D., McIntyre, I. G., McLarty, E., McLornan, M. E., McLoughlin, J., McNeill, S. A., Mehta, S., Mellon, J. K., Menezes, P., Mills, R. D., Mokete, M., Montague, R., Morton, A. L., Motiwala, H. G., Mulholland, C. K., Mumtaz, F. H., Munro, N., Myatt, A., Nair, M., Namasivayam, S., Napier‐Hemy, R. D., Nathan, S., Neilson, D., Nicol, D. L., Nuttall, M., OʼBrien, T. S., OʼKane, H. F., OʼRiordan, A., Oades, G., Oakley, N., Okeke, A. A., Olsburgh, J., Paez, E., Page, T., Parkin, J., Parys, B. T., Patel, P., Patel, N., Patel, B., Pathak, S., Patil, K., Paul, A. B., Payne, D., Peracha, A. M., Peters, J. L., Phillips, S. M. A., Phillips, J. T., Phipps, S., Pillai, M. K., Potter, J. M., Prescott, S., Rajan, T. N., Rajjayabun, P., Ramani, V. A. C., Rane, A., Ravi, R., Ravichandran, S., Riddick, A. C. P., Rimington, P. D., Rix, G. H., Rix, D., Robinson, L. Q., Rochester, M., Rogawski, K. M., Rogers, A. G., Rowe, E., Sahadevan, K., Samsudin, A., Sandhu, S., Sangar, V. K., Sells, H., Shackley, D. C., Shah, Z., Shaikh, N. N. A., Sharma, H., Sherwood, B., Singh, S., Singh, G., Smith, D. J., Solomon, L., Soomro, N. A., Srinivasan, V., Sriprasad, S. I., Stephenson, R. N., Stewart, A., Stubington, S. R., Subramonian, K., Sullivan, M. E., Taneja, S., Thilagarajah, R., Thomas, S. A., Thomas, D. J., Thomas, B., Thompson, A. C., Thurston, A.V., Turner, K. J., Umez‐Eronini, O. N., Upsdell, S. M., Vale, J. A., Varadaraj, H., Vesey, S. G., Viney, R., Vohra, A. K., Walton, T., Warburton, H. E., Waymont, B., Webster, J. J., Webster, G. M., Wedderburn, A., Wemyss‐Holden, G. D., Weston, R., Whittlestone, T., Wilkinson, S., Wilkinson, B., Williams, S., Wills, M. I., Wilson, J. R., Wilson, I. D., Woodhouse, C. R. J., Wright, M., Yates, D. R., and Young, J. G.

Published
2017
Full Text
View/download PDF

36. High-tech composites to ancient metals

Author

Zhang, S.Y., Godfrey, E., Kockelmann, W., Paradowska, A., Bull, M.J., Korsunsky, A.M., Abbey, B., Xu, P., Tomota, Y., Liljedahl, D., Zanellato, O., Fitzpatrick, M., Daymond, M.R., Toda, R.M., Holt, R.A., Kelleher, J., Siano, S., and Santisteban, J.

Published
2009
Full Text
View/download PDF

38. GA4GH: International policies and standards for data sharing across genomic research and healthcare.

Author

Rehm, HL, Page, AJH, Smith, L, Adams, JB, Alterovitz, G, Babb, LJ, Barkley, MP, Baudis, M, Beauvais, MJS, Beck, T, Beckmann, JS, Beltran, S, Bernick, D, Bernier, A, Bonfield, JK, Boughtwood, TF, Bourque, G, Bowers, SR, Brookes, AJ, Brudno, M, Brush, MH, Bujold, D, Burdett, T, Buske, OJ, Cabili, MN, Cameron, DL, Carroll, RJ, Casas-Silva, E, Chakravarty, D, Chaudhari, BP, Chen, SH, Cherry, JM, Chung, J, Cline, M, Clissold, HL, Cook-Deegan, RM, Courtot, M, Cunningham, F, Cupak, M, Davies, RM, Denisko, D, Doerr, MJ, Dolman, LI, Dove, ES, Dursi, LJ, Dyke, SOM, Eddy, JA, Eilbeck, K, Ellrott, KP, Fairley, S, Fakhro, KA, Firth, HV, Fitzsimons, MS, Fiume, M, Flicek, P, Fore, IM, Freeberg, MA, Freimuth, RR, Fromont, LA, Fuerth, J, Gaff, CL, Gan, W, Ghanaim, EM, Glazer, D, Green, RC, Griffith, M, Griffith, OL, Grossman, RL, Groza, T, Auvil, JMG, Guigó, R, Gupta, D, Haendel, MA, Hamosh, A, Hansen, DP, Hart, RK, Hartley, DM, Haussler, D, Hendricks-Sturrup, RM, Ho, CWL, Hobb, AE, Hoffman, MM, Hofmann, OM, Holub, P, Hsu, JS, Hubaux, J-P, Hunt, SE, Husami, A, Jacobsen, JO, Jamuar, SS, Janes, EL, Jeanson, F, Jené, A, Johns, AL, Joly, Y, Jones, SJM, Kanitz, A, Kato, K, Keane, TM, Kekesi-Lafrance, K, Kelleher, J, Kerry, G, Khor, S-S, Knoppers, BM, Konopko, MA, Kosaki, K, Kuba, M, Lawson, J, Leinonen, R, Li, S, Lin, MF, Linden, M, Liu, X, Udara Liyanage, I, Lopez, J, Lucassen, AM, Lukowski, M, Mann, AL, Marshall, J, Mattioni, M, Metke-Jimenez, A, Middleton, A, Milne, RJ, Molnár-Gábor, F, Mulder, N, Munoz-Torres, MC, Nag, R, Nakagawa, H, Nasir, J, Navarro, A, Nelson, TH, Niewielska, A, Nisselle, A, Niu, J, Nyrönen, TH, O'Connor, BD, Oesterle, S, Ogishima, S, Wang, VO, Paglione, LAD, Palumbo, E, Parkinson, HE, Philippakis, AA, Pizarro, AD, Prlic, A, Rambla, J, Rendon, A, Rider, RA, Robinson, PN, Rodarmer, KW, Rodriguez, LL, Rubin, AF, Rueda, M, Rushton, GA, Ryan, RS, Saunders, GI, Schuilenburg, H, Schwede, T, Scollen, S, Senf, A, Sheffield, NC, Skantharajah, N, Smith, AV, Sofia, HJ, Spalding, D, Spurdle, AB, Stark, Z, Stein, LD, Suematsu, M, Tan, P, Tedds, JA, Thomson, AA, Thorogood, A, Tickle, TL, Tokunaga, K, Törnroos, J, Torrents, D, Upchurch, S, Valencia, A, Guimera, RV, Vamathevan, J, Varma, S, Vears, DF, Viner, C, Voisin, C, Wagner, AH, Wallace, SE, Walsh, BP, Williams, MS, Winkler, EC, Wold, BJ, Wood, GM, Woolley, JP, Yamasaki, C, Yates, AD, Yung, CK, Zass, LJ, Zaytseva, K, Zhang, J, Goodhand, P, North, K, Birney, E, Rehm, HL, Page, AJH, Smith, L, Adams, JB, Alterovitz, G, Babb, LJ, Barkley, MP, Baudis, M, Beauvais, MJS, Beck, T, Beckmann, JS, Beltran, S, Bernick, D, Bernier, A, Bonfield, JK, Boughtwood, TF, Bourque, G, Bowers, SR, Brookes, AJ, Brudno, M, Brush, MH, Bujold, D, Burdett, T, Buske, OJ, Cabili, MN, Cameron, DL, Carroll, RJ, Casas-Silva, E, Chakravarty, D, Chaudhari, BP, Chen, SH, Cherry, JM, Chung, J, Cline, M, Clissold, HL, Cook-Deegan, RM, Courtot, M, Cunningham, F, Cupak, M, Davies, RM, Denisko, D, Doerr, MJ, Dolman, LI, Dove, ES, Dursi, LJ, Dyke, SOM, Eddy, JA, Eilbeck, K, Ellrott, KP, Fairley, S, Fakhro, KA, Firth, HV, Fitzsimons, MS, Fiume, M, Flicek, P, Fore, IM, Freeberg, MA, Freimuth, RR, Fromont, LA, Fuerth, J, Gaff, CL, Gan, W, Ghanaim, EM, Glazer, D, Green, RC, Griffith, M, Griffith, OL, Grossman, RL, Groza, T, Auvil, JMG, Guigó, R, Gupta, D, Haendel, MA, Hamosh, A, Hansen, DP, Hart, RK, Hartley, DM, Haussler, D, Hendricks-Sturrup, RM, Ho, CWL, Hobb, AE, Hoffman, MM, Hofmann, OM, Holub, P, Hsu, JS, Hubaux, J-P, Hunt, SE, Husami, A, Jacobsen, JO, Jamuar, SS, Janes, EL, Jeanson, F, Jené, A, Johns, AL, Joly, Y, Jones, SJM, Kanitz, A, Kato, K, Keane, TM, Kekesi-Lafrance, K, Kelleher, J, Kerry, G, Khor, S-S, Knoppers, BM, Konopko, MA, Kosaki, K, Kuba, M, Lawson, J, Leinonen, R, Li, S, Lin, MF, Linden, M, Liu, X, Udara Liyanage, I, Lopez, J, Lucassen, AM, Lukowski, M, Mann, AL, Marshall, J, Mattioni, M, Metke-Jimenez, A, Middleton, A, Milne, RJ, Molnár-Gábor, F, Mulder, N, Munoz-Torres, MC, Nag, R, Nakagawa, H, Nasir, J, Navarro, A, Nelson, TH, Niewielska, A, Nisselle, A, Niu, J, Nyrönen, TH, O'Connor, BD, Oesterle, S, Ogishima, S, Wang, VO, Paglione, LAD, Palumbo, E, Parkinson, HE, Philippakis, AA, Pizarro, AD, Prlic, A, Rambla, J, Rendon, A, Rider, RA, Robinson, PN, Rodarmer, KW, Rodriguez, LL, Rubin, AF, Rueda, M, Rushton, GA, Ryan, RS, Saunders, GI, Schuilenburg, H, Schwede, T, Scollen, S, Senf, A, Sheffield, NC, Skantharajah, N, Smith, AV, Sofia, HJ, Spalding, D, Spurdle, AB, Stark, Z, Stein, LD, Suematsu, M, Tan, P, Tedds, JA, Thomson, AA, Thorogood, A, Tickle, TL, Tokunaga, K, Törnroos, J, Torrents, D, Upchurch, S, Valencia, A, Guimera, RV, Vamathevan, J, Varma, S, Vears, DF, Viner, C, Voisin, C, Wagner, AH, Wallace, SE, Walsh, BP, Williams, MS, Winkler, EC, Wold, BJ, Wood, GM, Woolley, JP, Yamasaki, C, Yates, AD, Yung, CK, Zass, LJ, Zaytseva, K, Zhang, J, Goodhand, P, North, K, and Birney, E

Abstract

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Published
2021

41. Bioconda: Sustainable and comprehensive software distribution for the life sciences

Author

Dale, R, Gruning, B, Sjodin, A, Rowe, J, Chapman, B, Tomkins-Tinch, C, Valieris, R, Batut, B, Caprez, A, Cokelaer, T, Yusuf, D, Beauchamp, K, Brinda, K, Wollmann, T, Corguille, G, Ryan, D, Bretaudeau, A, Hoogstrate, Y, Pedersen, B, Heeringen, S, Raden, M, Luna-Valero, S, Soranzo, N, Smet, M, Kuster, G, Kirchner, R, Pantano, L, Charlop-Powers, Z, Thornton, K, Martin, M, Beek, M, Maticzka, D, Miladi, M, Will, S, Gravouil, K, Unneberg, P, Brueffer, C, Blank, C, Piro, V, Wolff, J, Antao, T, Gladman, S, Shlyakhter, I, Hollander, M, Mabon, P, Shen, W, Boekel, J, Holtgrewe, M, Bouvier, D, de Ruiter, J, Cabral, J, Choudhary, S, Harding, N, Kleinkauf, R, Enns, E, Eggenhofer, F, Brown, J, Cock, P, Timm, H, Thomas, C, Zhang, X, Chambers, M, Turaga, N, Seiler, E, Brislawn, C, Pruesse, E, Fallmann, J, Kelleher, J, Nguyen, H, Parsons, L, Fang, Z, Stovner, E, Stoler, N, Ye, S, Wohlers, I, Farouni, R, Freeberg, M, Johnson, J, Bargull, M, Kensche, P, Webster, T, Eppley, J, Stahl, C, Rose, A, Reynolds, A, Wang, L, Garnier, X, Dirmeier, S, Knudsen, M, Taylor, J, Srivastava, A, Rai, V, Agren, R, Junge, A, Guimera, R, Khan, A, Schmeier, S, He, G, Pinello, L, Hagglund, E, Mikheyev, A, Preussner, J, Waters, N, Li, W, Capellades, J, Chande, A, Pirola, Y, Hiltemann, S, Bendall, M, Singh, S, Dunn, W, Drouin, A, Domenico, T, Bruijn, I, Larson, D, Chicco, D, Grassi, E, Gonnella, G, B, J, Giacomoni, F, Clarke, E, Blankenberg, D, Tran, C, Patro, R, Laurent, S, Gopez, M, Sennblad, B, Baaijens, J, Ewels, P, Wright, P, Enache, O, Roger, P, Dampier, W, Koppstein, D, Devisetty, U, Rausch, T, Cornwell, M, Salatino, A, Seiler, J, Jung, M, Kornobis, E, Cumbo, F, Stocker, B, Moskalenko, O, Bogema, D, Workentine, M, Newhouse, S, Leprevost, F, Arvai, K, Koster, J, Dale R., Gruning B., Sjodin A., Rowe J., Chapman B. A., Tomkins-Tinch C. H., Valieris R., Batut B., Caprez A., Cokelaer T., Yusuf D., Beauchamp K. A., Brinda K., Wollmann T., Corguille G. L., Ryan D., Bretaudeau A., Hoogstrate Y., Pedersen B. S., Heeringen S., Raden M., Luna-Valero S., Soranzo N., Smet M. D., Kuster G. V., Kirchner R., Pantano L., Charlop-Powers Z., Thornton K., Martin M., Beek M. D., Maticzka D., Miladi M., Will S., Gravouil K., Unneberg P., Brueffer C., Blank C., Piro V. C., Wolff J., Antao T., Gladman S., Shlyakhter I., Hollander M., Mabon P., Shen W., Boekel J., Holtgrewe M., Bouvier D., de Ruiter J. R., Cabral J., Choudhary S., Harding N., Kleinkauf R., Enns E., Eggenhofer F., Brown J., Cock P. J. A., Timm H., Thomas C., Zhang X. -O., Chambers M., Turaga N., Seiler E., Brislawn C., Pruesse E., Fallmann J., Kelleher J., Nguyen H., Parsons L., Fang Z., Stovner E. B., Stoler N., Ye S., Wohlers I., Farouni R., Freeberg M., Johnson J. E., Bargull M., Kensche P. R., Webster T. H., Eppley J. M., Stahl C., Rose A. S., Reynolds A., Wang L. -B., Garnier X., Dirmeier S., Knudsen M., Taylor J., Srivastava A., Rai V., Agren R., Junge A., Guimera R. V., Khan A., Schmeier S., He G., Pinello L., Hagglund E., Mikheyev A. S., Preussner J., Waters N. R., Li W., Capellades J., Chande A. T., Pirola Y., Hiltemann S., Bendall M. L., Singh S., Dunn W. A., Drouin A., Domenico T. D., Bruijn I., Larson D. E., Chicco D., Grassi E., Gonnella G., B J., Wang L., Giacomoni F., Clarke E., Blankenberg D., Tran C., Patro R., Laurent S., Gopez M., Sennblad B., Baaijens J. A., Ewels P., Wright P. R., Enache O. M., Roger P., Dampier W., Koppstein D., Devisetty U. K., Rausch T., Cornwell M., Salatino A. E., Seiler J., Jung M., Kornobis E., Cumbo F., Stocker B. K., Moskalenko O., Bogema D. R., Workentine M. L., Newhouse S. J., Leprevost F. D. V., Arvai K., Koster J., Dale, R, Gruning, B, Sjodin, A, Rowe, J, Chapman, B, Tomkins-Tinch, C, Valieris, R, Batut, B, Caprez, A, Cokelaer, T, Yusuf, D, Beauchamp, K, Brinda, K, Wollmann, T, Corguille, G, Ryan, D, Bretaudeau, A, Hoogstrate, Y, Pedersen, B, Heeringen, S, Raden, M, Luna-Valero, S, Soranzo, N, Smet, M, Kuster, G, Kirchner, R, Pantano, L, Charlop-Powers, Z, Thornton, K, Martin, M, Beek, M, Maticzka, D, Miladi, M, Will, S, Gravouil, K, Unneberg, P, Brueffer, C, Blank, C, Piro, V, Wolff, J, Antao, T, Gladman, S, Shlyakhter, I, Hollander, M, Mabon, P, Shen, W, Boekel, J, Holtgrewe, M, Bouvier, D, de Ruiter, J, Cabral, J, Choudhary, S, Harding, N, Kleinkauf, R, Enns, E, Eggenhofer, F, Brown, J, Cock, P, Timm, H, Thomas, C, Zhang, X, Chambers, M, Turaga, N, Seiler, E, Brislawn, C, Pruesse, E, Fallmann, J, Kelleher, J, Nguyen, H, Parsons, L, Fang, Z, Stovner, E, Stoler, N, Ye, S, Wohlers, I, Farouni, R, Freeberg, M, Johnson, J, Bargull, M, Kensche, P, Webster, T, Eppley, J, Stahl, C, Rose, A, Reynolds, A, Wang, L, Garnier, X, Dirmeier, S, Knudsen, M, Taylor, J, Srivastava, A, Rai, V, Agren, R, Junge, A, Guimera, R, Khan, A, Schmeier, S, He, G, Pinello, L, Hagglund, E, Mikheyev, A, Preussner, J, Waters, N, Li, W, Capellades, J, Chande, A, Pirola, Y, Hiltemann, S, Bendall, M, Singh, S, Dunn, W, Drouin, A, Domenico, T, Bruijn, I, Larson, D, Chicco, D, Grassi, E, Gonnella, G, B, J, Giacomoni, F, Clarke, E, Blankenberg, D, Tran, C, Patro, R, Laurent, S, Gopez, M, Sennblad, B, Baaijens, J, Ewels, P, Wright, P, Enache, O, Roger, P, Dampier, W, Koppstein, D, Devisetty, U, Rausch, T, Cornwell, M, Salatino, A, Seiler, J, Jung, M, Kornobis, E, Cumbo, F, Stocker, B, Moskalenko, O, Bogema, D, Workentine, M, Newhouse, S, Leprevost, F, Arvai, K, Koster, J, Dale R., Gruning B., Sjodin A., Rowe J., Chapman B. A., Tomkins-Tinch C. H., Valieris R., Batut B., Caprez A., Cokelaer T., Yusuf D., Beauchamp K. A., Brinda K., Wollmann T., Corguille G. L., Ryan D., Bretaudeau A., Hoogstrate Y., Pedersen B. S., Heeringen S., Raden M., Luna-Valero S., Soranzo N., Smet M. D., Kuster G. V., Kirchner R., Pantano L., Charlop-Powers Z., Thornton K., Martin M., Beek M. D., Maticzka D., Miladi M., Will S., Gravouil K., Unneberg P., Brueffer C., Blank C., Piro V. C., Wolff J., Antao T., Gladman S., Shlyakhter I., Hollander M., Mabon P., Shen W., Boekel J., Holtgrewe M., Bouvier D., de Ruiter J. R., Cabral J., Choudhary S., Harding N., Kleinkauf R., Enns E., Eggenhofer F., Brown J., Cock P. J. A., Timm H., Thomas C., Zhang X. -O., Chambers M., Turaga N., Seiler E., Brislawn C., Pruesse E., Fallmann J., Kelleher J., Nguyen H., Parsons L., Fang Z., Stovner E. B., Stoler N., Ye S., Wohlers I., Farouni R., Freeberg M., Johnson J. E., Bargull M., Kensche P. R., Webster T. H., Eppley J. M., Stahl C., Rose A. S., Reynolds A., Wang L. -B., Garnier X., Dirmeier S., Knudsen M., Taylor J., Srivastava A., Rai V., Agren R., Junge A., Guimera R. V., Khan A., Schmeier S., He G., Pinello L., Hagglund E., Mikheyev A. S., Preussner J., Waters N. R., Li W., Capellades J., Chande A. T., Pirola Y., Hiltemann S., Bendall M. L., Singh S., Dunn W. A., Drouin A., Domenico T. D., Bruijn I., Larson D. E., Chicco D., Grassi E., Gonnella G., B J., Wang L., Giacomoni F., Clarke E., Blankenberg D., Tran C., Patro R., Laurent S., Gopez M., Sennblad B., Baaijens J. A., Ewels P., Wright P. R., Enache O. M., Roger P., Dampier W., Koppstein D., Devisetty U. K., Rausch T., Cornwell M., Salatino A. E., Seiler J., Jung M., Kornobis E., Cumbo F., Stocker B. K., Moskalenko O., Bogema D. R., Workentine M. L., Newhouse S. J., Leprevost F. D. V., Arvai K., and Koster J.

Abstract

Bioinformatics software comes in a variety of programming languages and requires diverse installation methods. This heterogeneity makes management of a software stack complicated, error-prone, and inordinately time-consuming. Whereas software deployment has traditionally been handled by administrators, ensuring the reproducibility of data analyses1–3 requires that the researcher be able to maintain full control of the software environment, rapidly modify it without administrative privileges, and reproduce the same software stack on different machines.

Published
2018

42. Accounting for long-range correlations in genome-wide simulations of large cohorts

Author

Nelson, D, Kelleher, J, Ragsdale, AP, Moreau, C, McVean, G, and Gravel, S

Subjects
Cancer Research, Heredity, Population genetics, QH426-470, Biochemistry, Linkage Disequilibrium, Coalescent theory, Cohort Studies, 0302 clinical medicine, Effective population size, Range (statistics), Quantitative Biology::Populations and Evolution, Genome Evolution, Genetics (clinical), Recombination, Genetic, 0303 health sciences, Genome, Simulation and Modeling, Population size, Genomics, Quantitative Biology::Genomics, Nucleic acids, Algorithms, Research Article, Genome evolution, DNA recombination, Population Size, Demographic history, Biology, Research and Analysis Methods, Molecular Evolution, Evolution, Molecular, 03 medical and health sciences, Population Metrics, Effective Population Size, Genetics, Humans, Computer Simulation, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Evolutionary Biology, Base Sequence, Models, Genetic, Biology and life sciences, Population Biology, Computational Biology, DNA, Genetics, Population, Sample size determination, Evolutionary biology, Sample Size, Genetic Polymorphism, Population Genetics, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Coalescent simulations are widely used to examine the effects of evolution and demographic history on the genetic makeup of populations. Thanks to recent progress in algorithms and data structures, simulators such as the widely-used msprime now provide genome-wide simulations for millions of individuals. However, this software relies on classic coalescent theory and its assumptions that sample sizes are small and that the region being simulated is short. Here we show that coalescent simulations of long regions of the genome exhibit large biases in identity-by-descent (IBD), long-range linkage disequilibrium (LD), and ancestry patterns, particularly when the sample size is large. We present a Wright-Fisher extension to msprime, and show that it produces more realistic distributions of IBD, LD, and ancestry proportions, while also addressing more subtle biases of the coalescent. Further, these extensions are more computationally efficient than state-of-the-art coalescent simulations when simulating long regions, including whole-genome data. For shorter regions, efficiency can be maintained via a hybrid model which simulates the recent past under the Wright-Fisher model and uses coalescent simulations in the distant past., Author summary Coalescent theory has provided deep theoretical insight into patterns of human diversity. Implementations of coalescent models in simulation software such as ms have further provided tools to interpret thousands of genomic studies. Recent technical progress has allowed for a dramatic increase in the scale at which genomes can be both measured and simulated, opening up opportunities for a finer understanding of evolutionary biology. However, we show that coalescent simulations of long regions of the genome exhibit large biases in sample relatedness, distorting haplotype sharing and ancestry patterns in simulated cohorts. We trace these biases to basic assumptions of the coalescent model, and show how the assumptions can be relaxed to provide a better description of the observed patterns of genetic polymorphism at a fraction of the computational cost.

Published
2020

50. Bioconda: sustainable and comprehensive software distribution for the life sciences

Author

Dale R., Gruning B., Sjodin A., Rowe J., Chapman B. A., Tomkins-Tinch C. H., Valieris R., Batut B., Caprez A., Cokelaer T., Yusuf D., Beauchamp K. A., Brinda K., Wollmann T., Corguille G. L., Ryan D., Bretaudeau A., Hoogstrate Y., Pedersen B. S., Heeringen S., Raden M., Luna-Valero S., Soranzo N., Smet M. D., Kuster G. V., Kirchner R., Pantano L., Charlop-Powers Z., Thornton K., Martin M., Beek M. D., Maticzka D., Miladi M., Will S., Gravouil K., Unneberg P., Brueffer C., Blank C., Piro V. C., Wolff J., Antao T., Gladman S., Shlyakhter I., Hollander M., Mabon P., Shen W., Boekel J., Holtgrewe M., Bouvier D., de Ruiter J. R., Cabral J., Choudhary S., Harding N., Kleinkauf R., Enns E., Eggenhofer F., Brown J., Cock P. J. A., Timm H., Thomas C., Zhang X. -O., Chambers M., Turaga N., Seiler E., Brislawn C., Pruesse E., Fallmann J., Kelleher J., Nguyen H., Parsons L., Fang Z., Stovner E. B., Stoler N., Ye S., Wohlers I., Farouni R., Freeberg M., Johnson J. E., Bargull M., Kensche P. R., Webster T. H., Eppley J. M., Stahl C., Rose A. S., Reynolds A., Wang L. -B., Garnier X., Dirmeier S., Knudsen M., Taylor J., Srivastava A., Rai V., Agren R., Junge A., Guimera R. V., Khan A., Schmeier S., He G., Pinello L., Hagglund E., Mikheyev A. S., Preussner J., Waters N. R., Li W., Capellades J., Chande A. T., Pirola Y., Hiltemann S., Bendall M. L., Singh S., Dunn W. A., Drouin A., Domenico T. D., Bruijn I., Larson D. E., Chicco D., Grassi E., Gonnella G., B J., Wang L., Giacomoni F., Clarke E., Blankenberg D., Tran C., Patro R., Laurent S., Gopez M., Sennblad B., Baaijens J. A., Ewels P., Wright P. R., Enache O. M., Roger P., Dampier W., Koppstein D., Devisetty U. K., Rausch T., Cornwell M., Salatino A. E., Seiler J., Jung M., Kornobis E., Cumbo F., Stocker B. K., Moskalenko O., Bogema D. R., Workentine M. L., Newhouse S. J., Leprevost F. D. V., Arvai K., Koster J., Albert-Ludwigs-Universität Freiburg, National Institutes of Health [Bethesda] (NIH), Swedish Defence Research Agency [Stockholm] (FOI), Umeå University, Harvard T.H. Chan School of Public Health, New York University [Abu Dhabi], NYU System (NYU), Harvard University [Cambridge], Hospital Camargo Sao Paulo, Partenaires INRAE, University of Duisburg-Essen, This work was supported by the Intramural Program of the National Institute of Diabetes and Digestive and Kidney Diseases, US National Institutes of Health (R.D.), the Netherlands Organisation for Scientific Research (NWO) (VENI grant 016.Veni.173.076 to J.K.), the German Research Foundation (SFB 876 to J.K.), and the NYU Abu Dhabi Research Institute for the NYU Abu Dhabi Center for Genomics and Systems Biology, program number CGSB1 (grant to J.R. and A. Yousif)., We thank all contributors, the conda-forge team, and Anaconda Inc. for excellent cooperation. Further, we thank Travis CI (https://travis-ci.com) and Circle CI (https://circleci.com) for providing free Linux and macOS computing capacity. Finally, we thank ELIXIR (https://www.elixir-europe.org) for constant support and donation of staff., Etienne Kornobis (Epigenetic Regulation Unit, Institut Pasteur, Paris, France) fait partie de Bioconda Team, Bioinformatics Group, Department ​ ​ of ​ ​ Computer ​ ​ Science, University of Freiburg [Freiburg], Laboratory of Cellular and Developmental Biology (LCDB), NIDDK, NIH, Department of Organismic and Evolutionary Biology, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Microbiologie Environnement Digestif Santé (MEDIS), INRA Clermont-Ferrand-Theix-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Umea Plant Science Center (UPSC), Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences (SLU)-Swedish University of Agricultural Sciences (SLU), Laboratoire Microorganismes : Génome et Environnement (LMGE), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Harvard University, Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Dale, R, Gruning, B, Sjodin, A, Rowe, J, Chapman, B, Tomkins-Tinch, C, Valieris, R, Batut, B, Caprez, A, Cokelaer, T, Yusuf, D, Beauchamp, K, Brinda, K, Wollmann, T, Corguille, G, Ryan, D, Bretaudeau, A, Hoogstrate, Y, Pedersen, B, Heeringen, S, Raden, M, Luna-Valero, S, Soranzo, N, Smet, M, Kuster, G, Kirchner, R, Pantano, L, Charlop-Powers, Z, Thornton, K, Martin, M, Beek, M, Maticzka, D, Miladi, M, Will, S, Gravouil, K, Unneberg, P, Brueffer, C, Blank, C, Piro, V, Wolff, J, Antao, T, Gladman, S, Shlyakhter, I, Hollander, M, Mabon, P, Shen, W, Boekel, J, Holtgrewe, M, Bouvier, D, de Ruiter, J, Cabral, J, Choudhary, S, Harding, N, Kleinkauf, R, Enns, E, Eggenhofer, F, Brown, J, Cock, P, Timm, H, Thomas, C, Zhang, X, Chambers, M, Turaga, N, Seiler, E, Brislawn, C, Pruesse, E, Fallmann, J, Kelleher, J, Nguyen, H, Parsons, L, Fang, Z, Stovner, E, Stoler, N, Ye, S, Wohlers, I, Farouni, R, Freeberg, M, Johnson, J, Bargull, M, Kensche, P, Webster, T, Eppley, J, Stahl, C, Rose, A, Reynolds, A, Wang, L, Garnier, X, Dirmeier, S, Knudsen, M, Taylor, J, Srivastava, A, Rai, V, Agren, R, Junge, A, Guimera, R, Khan, A, Schmeier, S, He, G, Pinello, L, Hagglund, E, Mikheyev, A, Preussner, J, Waters, N, Li, W, Capellades, J, Chande, A, Pirola, Y, Hiltemann, S, Bendall, M, Singh, S, Dunn, W, Drouin, A, Domenico, T, Bruijn, I, Larson, D, Chicco, D, Grassi, E, Gonnella, G, B, J, Giacomoni, F, Clarke, E, Blankenberg, D, Tran, C, Patro, R, Laurent, S, Gopez, M, Sennblad, B, Baaijens, J, Ewels, P, Wright, P, Enache, O, Roger, P, Dampier, W, Koppstein, D, Devisetty, U, Rausch, T, Cornwell, M, Salatino, A, Seiler, J, Jung, M, Kornobis, E, Cumbo, F, Stocker, B, Moskalenko, O, Bogema, D, Workentine, M, Newhouse, S, Leprevost, F, Arvai, K, Koster, J, Urology, and Pathology

Subjects
0301 basic medicine, Computer science, [SDV]Life Sciences [q-bio], Medizin, computer.software_genre, Biochemistry, User-Computer Interface, 03 medical and health sciences, 0302 clinical medicine, Software system, Molecular Biology, ComputingMilieux_MISCELLANEOUS, Social software engineering, Database, business.industry, Software development, INF/01 - INFORMATICA, Computational Biology, Cell Biology, Software distribution, 030104 developmental biology, Software construction, [SDE]Environmental Sciences, Package development process, Backporting, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business, computer, Software, 030217 neurology & neurosurgery, Biotechnology
Abstract

International audience; We present Bioconda (https://bioconda.github.io), a distribution of bioinformatics software for the lightweight, multi- platform and language-agnostic package manager Conda. Currently, Bioconda o ers a collection of over 3000 software packages, which is continuously maintained, updated, and extended by a growing global community of more than 200 contributors. Bio- conda improves analysis reproducibility by allowing users to de ne isolated environments with de ned software versions, all of which are easily installed and managed without administrative privileges.

Published
2018

Catalog

Books, media, physical & digital resources
See catalog results