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Publications

Recent Publications

The list below displays 20 of our most recent publications.

  1. Marshall, AE, Lemire, G, Liang, Y, Davila, J, Couse, M, Care4Rare Canada Consortium, Boycott, KM, Kernohan, KD. RNA sequencing reveals deep intronic CEP120 variant: A report of the diagnostic odyssey for two siblings with Joubert syndrome type 31. Am J Med Genet A. 2023; :. doi: 10.1002/ajmg.a.63485.
  2. Ufkes, S, Zuercher, M, Erdman, L, Slorach, C, Mertens, L, Taylor, KL. Automatic Prediction of Paediatric Cardiac Output From Echocardiograms Using Deep Learning Models. CJC Pediatr Congenit Heart Dis. 2023;2 (1):12-19. doi: 10.1016/j.cjcpc.2022.11.001.
  3. de Kock, L, Cuillerier, A, Gillespie, M, Couse, M, Hartley, T, Mears, W, Bernier, FP, Chudley, AE, Frosk, P, Nikkel, SM, Innes, AM, Lauzon, J, Thomas, M, Guerin, A, Armour, CM, Weksberg, R, Scott, JN, Watkins, D, Harvey, S, Cytrynbaum, C, Care4Rare Canada Consortium, Kernohan, KD, Boycott, KM. Molecular characterization of 13 patients with PIK3CA-related overgrowth spectrum using a targeted deep sequencing approach. Am J Med Genet A. 2023; :. doi: 10.1002/ajmg.a.63466.
  4. Marshall, AE, Liang, Y, Couse, M, McConkey, H, Care4Rare Canada Consortium, Sadikovic, B, Boycott, KM, Dyment, DA, Kernohan, KD. Integrated omics analyses clarifies ATRX copy number variant of uncertain significance. J Hum Genet. 2023; :. doi: 10.1038/s10038-023-01203-8.
  5. Apostolides, M, Li, M, Arnoldo, A, Ku, M, Husić, M, Ramani, AK, Brudno, M, Turinsky, A, Hawkins, C, Siddaway, R. Clinical Implementation of MetaFusion for Accurate Cancer-Driving Fusion Detection from RNA Sequencing. J Mol Diagn. 2023;25 (12):921-931. doi: 10.1016/j.jmoldx.2023.09.002.
  6. Warsi, NM, Wong, SM, Germann, J, Boutet, A, Arski, ON, Anderson, R, Erdman, L, Yan, H, Suresh, H, Gouveia, FV, Loh, A, Elias, GJB, Kerr, E, Smith, ML, Ochi, A, Otsubo, H, Sharma, R, Jain, P, Donner, E, Lozano, AM, Snead, OC, Ibrahim, GM. Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography. Neural Netw. 2023;167 :827-837. doi: 10.1016/j.neunet.2023.07.019.
  7. Richter, J, Doktor, F, Good, H, Erdman, L, Kim, JK, Santos, JD, Brownrigg, N, Chua, M, Lorenzo, AJ, Rickard, M, Mieghem, TV, Shinar, S. Trends in Management of Fetuses with Suspected Lower Urinary Tract Obstruction (LUTO): A High-Risk Fetal and Pediatric Center Experience in a Universal-Access-to-Care System. Eur J Pediatr Surg. 2023; :. doi: 10.1055/s-0043-1772172.
  8. Khondker, A, Kwong, JCC, Chancy, M, D'Souza, N, Kim, K, Kim, JK, Tse, LN, Chua, M, Yadav, P, Erdman, L, Weaver, J, Lorenzo, AJ, Rickard, M. Predicting obstruction risk using common ultrasonography parameters in paediatric hydronephrosis with machine learning. BJU Int. 2023; :. doi: 10.1111/bju.16159.
  9. Khondker, A, Kwong, JCC, Yadav, P, Chan, JYH, Singh, A, Erdman, L, Keefe, DT, Rickard, M, Lorenzo, AJ. A quantitative analysis of voiding cystourethrogram features confirms the association between high-grade vesicoureteral reflux with male sex, younger age, and hydronephrosis. Can Urol Assoc J. 2023;17 (8):243-246. doi: 10.5489/cuaj.8460.
  10. Marshall, AE, MacDonald, SK, Liang, Y, Couse, M, Care4Rare Canada Consortium, Boycott, KM, Richer, J, Kernohan, KD. RNA sequencing resolves novel DYNC2H1 variants causing short-rib thoracic dysplasia type 3: Case report. Mol Genet Genomic Med. 2023;11 (10):e2247. doi: 10.1002/mgg3.2247.
  11. Bägli, DJ, Erdman, L. Commentary to deep learning based automatic quantification of urethral plate characteristics using the plate objective scoring tool (POST). J Pediatr Urol. 2023;19 (5):584-585. doi: 10.1016/j.jpurol.2023.06.030.
  12. Ghazisaeidi, S, Muley, MM, Tu, Y, Finn, DP, Kolahdouzan, M, Pitcher, GM, Kim, D, Sengar, AS, Ramani, AK, Brudno, M, Salter, MW. Conserved transcriptional programming across sex and species after peripheral nerve injury predicts treatments for neuropathic pain. Br J Pharmacol. 2023;180 (21):2822-2836. doi: 10.1111/bph.16168.
  13. Peterson, KA, Khalouei, S, Hanafi, N, Wood, JA, Lanza, DG, Lintott, LG, Willis, BJ, Seavitt, JR, Braun, RE, Dickinson, ME, White, JK, Lloyd, KCK, Heaney, JD, Murray, SA, Ramani, A, Nutter, LMJ. Whole genome analysis for 163 gRNAs in Cas9-edited mice reveals minimal off-target activity. Commun Biol. 2023;6 (1):626. doi: 10.1038/s42003-023-04974-0.
  14. Shooshtari, P, Feng, S, Nelakuditi, V, Asakereh, R, Hosseini Naghavi, N, Foong, J, Brudno, M, Cotsapas, C. Developing OCHROdb, a comprehensive quality checked database of open chromatin regions from sequencing data. Sci Rep. 2023;13 (1):8106. doi: 10.1038/s41598-022-26791-x.
  15. Bhola, PT, Marshall, AE, Liang, Y, Couse, M, Wang, X, Miller, E, Morel, CF, Boycott, KM, Kernohan, KD. RNA sequencing to support intronic variant interpretation: A case report of TRAPPC12-related disorder. Am J Med Genet A. 2023;191 (6):1664-1668. doi: 10.1002/ajmg.a.63184.
  16. Deshwar, AR, Yuki, KE, Hou, H, Liang, Y, Khan, T, Celik, A, Ramani, A, Mendoza-Londono, R, Marshall, CR, Brudno, M, Shlien, A, Meyn, MS, Hayeems, RZ, McKinlay, BJ, Klentrou, P, Wilson, MD, Kyriakopoulou, L, Costain, G, Dowling, JJ. Trio RNA sequencing in a cohort of medically complex children. Am J Hum Genet. 2023;110 (5):895-900. doi: 10.1016/j.ajhg.2023.03.006.
  17. Ivanics, T, So, D, Claasen, MPAW, Wallace, D, Patel, MS, Gravely, A, Choi, WJ, Shwaartz, C, Walker, K, Erdman, L, Sapisochin, G. Machine learning-based mortality prediction models using national liver transplantation registries are feasible but have limited utility across countries. Am J Transplant. 2023;23 (1):64-71. doi: 10.1016/j.ajt.2022.12.002.
  18. Sokolowski, DJ, Ahn, J, Erdman, L, Hou, H, Ellis, K, Wang, L, Goldenberg, A, Wilson, MD. Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression. NAR Genom Bioinform. 2023;5 (1):lqad003. doi: 10.1093/nargab/lqad003.
  19. Christensen, E, Luo, P, Turinsky, A, Husić, M, Mahalanabis, A, Naidas, A, Diaz-Mejia, JJ, Brudno, M, Pugh, T, Ramani, A, Shooshtari, P. Evaluation of single-cell RNAseq labelling algorithms using cancer datasets. Brief Bioinform. 2023;24 (1):. doi: 10.1093/bib/bbac561.
  20. Villani, A, Davidson, S, Kanwar, N, Lo, WW, Li, Y, Cohen-Gogo, S, Fuligni, F, Edward, LM, Light, N, Layeghifard, M, Harripaul, R, Waldman, L, Gallinger, B, Comitani, F, Brunga, L, Hayes, R, Anderson, ND, Ramani, AK, Yuki, KE, Blay, S, Johnstone, B, Inglese, C, Hammad, R, Goudie, C, Shuen, A, Wasserman, JD, Venier, RE, Eliou, M, Lorenti, M, Ryan, CA, Braga, M, Gloven-Brown, M, Han, J, Montero, M, Spatare, F, Whitlock, JA, Scherer, SW, Chun, K, Somerville, MJ, Hawkins, C, Abdelhaleem, M, Ramaswamy, V, Somers, GR, Kyriakopoulou, L, Hitzler, J, Shago, M, Morgenstern, DA, Tabori, U, Meyn, S, Irwin, MS, Malkin, D, Shlien, A. The clinical utility of integrative genomics in childhood cancer extends beyond targetable mutations. Nat Cancer. 2023;4 (2):203-221. doi: 10.1038/s43018-022-00474-y.
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