Publications

Special Issue in HuMu cover

Human Mutation Special Issue of 2017

  • Beer MA. 2017. Predicting enhancer activity and variant impact using gkm-SVM. Hum Mutat 38:1251-1258. PMCID:PMC5526747. doi:10.1002/humu.23185
  • Cai B, Li B, Kiga N, Thusberg J, Bergquist T, Chen Y-C, Niknafs N, Carter H, Tokheim C, Beleva-Guthrie V, Douville C, Bhattacharya R, Yeo HTG, Fan J, Sengupta S, Kim D, Cline M, Turner T, Diekhans M, Zaucha J, Pal LR, Cao C, Yu C-H, Yin Y, Carraro M, Giollo M, Ferrari C, Leonardi E, Tosatto SCE, Bobe J, Ball M, Hoskins RA, Repo S, Church G, Brenner SE, Moult J, Gough J, Stanke M, Karchin R, Mooney SD. 2017. Matching phenotypes to whole genomes: Lessons learned from four iterations of the personal genome project community challenges. Hum Mutat 38:1266-1276. doi:10.1002/humu.23265
  • Capriotti E, Martelli PL, Fariselli P, Casadio R. 2017. Blind prediction of deleterious amino acid variations with SNPs&GO. Hum Mutat 38:1266-1276. doi:10.1002/humu.23179
  • Carraro M, Minervini G, Giollo M, Bromberg Y, Capriotti E, Casadio R, Dunbrack R, Elefanti L, Fariselli P, Ferrari C, Gough J, Katsonis P, Leonardi E, Lichtarge O, Menin C, Martelli PL, Niroula A, Pal LR, Repo S, Scaini MC, Vihinen M, Wei Q, Xu Q, Yang Y, Yin Y, Zaucha J, Zhao H, Zhou Y, Brenner SE, Moult J, Tosatto SCE. 2017. Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI. Hum Mutat 38:1042–1050. doi:10.1002/humu.23235
  • Chandonia J-M, Adhikari A, Carraro M, Chhibber A, Cutting GR, Fu Y, Gasparini A, Jones DT, Kramer A, Kundu K, Lam HYK, Leonardi E, Moult J, Pal LR, Searls DB, Shah S, Sunyaev S, Tosatto SCE, Yin Y, Buckley BA. 2017. Lessons from the CAGI-4 Hopkins clinical panel challenge. Hum Mutat 38:1155-1168. doi:10.1002/humu.23225
  • Daneshjou R, Wang Y, Bromberg Y, Bovo S, Martelli PL, Babbi G, Lena P Di, Casadio R, Edwards M, Gifford D, Jones DT, Sundaram L, Bhat R, Li X, Pal LR, Kundu K, Yin Y, Moult J, Jiang Y, Pejaver V, Pagel KA, Li B, Mooney SD, Radivojac P, Shah S, Carraro M, Gasparini A, Leonardi E, Giollo M, Ferrari C, Tosatto SCE, Bachar E, Azaria JR, Ofran Y, Unger R, Niroula A, Vihinen M, Chang B, Wang MH, Franke A, Petersen B-S, Pirooznia M, Zandi P, McCombie R, Potash JB, Altman R, Klein TE, Hoskins R, Repo S, Brenner SE, Morgan AA. 2017. Working towards precision medicine: predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges. Hum Mutat 38:1182-1192. doi:10.1002/humu.23280
  • Giollo M, Jones DT, Carraro M, Leonardi E, Ferrari C, Tosatto SCE. 2017. Crohn disease risk prediction-Best practices and pitfalls with exome data. Hum Mutat 38:1193-1200. PMCID:PMC5509518. doi:10.1002/humu.23177
  • Hoskins RA, Repo S, Barsky D, Andreoletti G, Moult J, Brenner SE.2017. Reports from CAGI: The Critical Assessment of Genome Interpretation. Hum Mutat 38:1072-1084. doi:10.1002/humu.23290
  • Katsonis P, Lichtarge O. 2017. Objective assessment of the evolutionary action equation for the fitness effect of missense mutations across CAGI-blinded contests. Hum Mutat 38:1072-1084. doi:10.1002/humu.23266
  • Kreimer A, Zeng H, Edwards MD, Guo Y, Tian K, Shin S, Welch R, Wainberg M, Mohan R, Sinnott-Armstrong NA, Li Y, Eraslan G, AMIN T Bin, Goke J, Mueller NS, Kellis M, Kundaje A, Beer MA, Keles S, Gifford DK, Yosef N. 2017. Predicting gene expression in massively parallel reporter assays: A comparative study. Hum Mutat 38:1240-1250. doi:10.1002/humu.23197
  • Kundu K, Pal LR, Yin Y, Moult J. 2017. Determination of disease phenotypes and pathogenic variants from exome sequence data in the CAGI 4 gene panel challenge. Hum Mutat 38:1201-1216. doi:10.1002/humu.23249
  • Laksshman S, Bhat RR, Viswanath V, Li X. 2017. Deep bipolar: Identifying genomic mutations for bipolar disorder via deep learning. Hum Mutat 38:1217-1224. doi:10.1002/humu.23272
  • Niroula A, Vihinen M. 2017. PON-P and PON-P2 predictor performance in CAGI challenges: Lessons learned. Hum Mutat 38:1085-1091. PMCID:PMC5561442. doi:10.1002/humu.23199
  • Pal LR, Kundu K, Yin Y, Moult J. 2017a. CAGI4 Crohn’s exome challenge: Marker SNP versus exome variant models for assigning risk of Crohn disease. Hum Mutat 38:1225-1234. doi:10.1002/humu.23256
  • Pal LR, Kundu K, Yin Y, Moult J. 2017b. CAGI4 SickKids clinical genomes challenge: A pipeline for identifying pathogenic variants. Hum Mutat 38: 1169–1181. doi:10.1002/humu.23257
  • Pejaver V, Mooney SD, Radivojac P. 2017. Missense variant pathogenicity predictors generalize well across a range of function-specific prediction challenges. Hum Mutat 38:1092-1108. PMCID:PMC5561458. doi:10.1002/humu.23258
  • Tang Q, Fenton AW. 2017. Whole-protein alanine-scanning mutagenesis of allostery: A large percentage of a protein can contribute to mechanism. Hum Mutat 38:1132-1143. PMCID:PMC5561450. doi:10.1002/humu.23231
  • Tang, Q, Aileen Y. Alontaga, Todd Holyoak and Aron W. Fenton Exploring the limits of the usefulness of mutagenesis in studies of allosteric mechanisms. Hum Mutat 38:1144-1154. PMCID:PMC5561510. DOI: 10.1002/humu.23239
  • Wang MH, Chang B, Sun R, Hu I, Xia X, Wu WKK, Chong KC, Zee BC-Y. 2017. Stratified polygenic risk prediction model with application to CAGI bipolar disorder sequencing data. Hum Mutat 38:1235-1239. PMCID:PMC5561515. doi:10.1002/humu.23229
  • Xu Q, Tang Q, Katsonis P, Lichtarge O, Jones D, Bovo S, Babbi G, Martelli PL, Casadio R, Lee GR, Seok C, Fenton AW, Dunbrack RL. 2017. Benchmarking predictions of allostery in liver pyruvate kinase in CAGI4. Hum Mutat 38:1123-1131. PMCID:PMC5561472. doi:10.1002/humu.23222
  • Yin Y, Kundu K, Pal LR, Moult J. 2017. Ensemble variant interpretation methods to predict enzyme activity and assign pathogenicity in the CAGI4 NAGLU (Human N-acetyl-glucosaminidase) and UBE2I (Human SUMO-ligase) challenges. Hum Mutat 38:1109-1122. doi:10.1002/humu.23267
  • Zeng H, Edwards MD, Guo Y, Gifford DK. 2017. Accurate eQTL prioritization with an ensemble-based framework. Hum Mutat 38:1259-1265. PMCID:PMC5561514. doi:10.1002/humu.23198
  • Zhang J, Kinch LN, Cong Q, Weile J, Sun S, Cote AG, Roth FP, Grishin NV. 2017. Assessing predictions of fitness effects of missense mutations in SUMO-conjugating enzyme UBE2I. Hum Mutat 38:1051-1063. doi:doi:10.1002/humu.23293

Papers in preparation

  • LeBowitz J, Yu KG, Hengl L, Aoyagi-Scharber M, and Wyatt TC. 2017. N-acetyl-glucosaminidase (NAGLU): predict the effect of naturally occurring missense mutations on cellular enzymatic activity. Human Mutation
  • Fridberg I. 2017. CBS challenges. Human Mutation
  • Üstünkar G, Döm HA, Yılmaz A, Son YA. 2017. Analytic Hierarchy Process Based Structured SNP Prioritization Scheme for Multi-hierarchical Filtering of Informative SNPs. Human Mutation
  • Meyn S, et al.2017. Predict patients’ clinical descriptions and pathogenic variants from their genome sequences. Human Mutation

CAGI flagship paper Findings from the Critical Assessment of Genome Interpretation (CAGI): community experiments to evaluate predictions of phenotype from genomic variation. CAGI participants. In preparation.

Authors include: Adebali O, Adhikari A, Adzhubey I, Altman R, Amin T, Andreoletti G, Arkin AP, Azaria JR, Babbi G, Babbitt P, Bachar E, Bachman B, Baek M, Ball MP, Barsky D, Beer M, Beleva-Guthrie V, Berger B, Bernard B, Bhat R, Bhattacharya R, Bobe J, Bonvini P, Bovo S, Breese M, Brenner SE, Brodie AS, Bromberg Y, Buckley B, Butte A, Cai B, Campbell C, Cao C, Capriotti E, Carraro M, Casadio R, Carter H, Chandonia JM, Chang BHW, Chellappan A, Chen CY, Chen F, Chen R, Chen SC, Chen YC, Church G, Clark WT, Cline M, Corredor A, Cui C, Cutting GR, D’Andrea E, Dabbiru N, Daneshjou R, Davis C, De Baets G, Di Lena P, Diekhans M, Dogan RI, Douville C, Driver I, Dunbrack R, van Durme J, Eakin A, Edwards M, L. Elefanti, L. Elnitski, Eraslan G, H. Fang, Fenton AW, Ferrari C, Flynn A, L. Folkman, Ford CT, Franke A, Frankish A, Franklin Z, Friedberg I, Fu Y, Gasparini A, Gaunt T, Getz G, Gifford D, Giollo M, Gonzaludo N, Gotea V, Gough J, Gray JW, Grishin N, Guo Y, Harrow J, Hart R, Hasenahuer M, Heo L, Hernandez R, Homayouni R, Hoskins RA, Hosur R, Huang CLV, Hubbard T, Huwe P, Hwang S, Imanishi T, Jacobsen J, Jannson L, Jeong CS, Y. Jiang, Jones DT, Jordan D, Kahn S, Kane JP, B. Kang, Karchin R, Katsonis P, Keles S, Kellis M, Kiga N, Kim D, Kim E, Kirsch JF, Kleyman M, Kraemer A, Kreimer A, Kundaje A, Kundu K, Kwok PY, Lam E, Lathrop R, LeBowitz JH, Lee D, Lee G, Lee I, Leonardi E, Li A, Li B, Li JM, Li Y, Lichtarge O, Lin CF, Lovisa F, Lua RC, Ly MK, Mak ACY, Mak A, Malloy MJ, Martelli PL, Masica D, McCombie R, Medoff Z, Menin C, Meyn MS, Meyn S, Mezlini AM, Mohan R, Monzon AM, Mooney SD, Morgan AA, Mort M, Moult J, Mount S, Mucaki E, Mudge J, Mueller N, Mungall C, Murakami K, Nagai Y, Neumann AJ, Ng P, Niknafs N, Niroula A, Nodzak CML, Nussbaum R, Ofran Y, Olatubosun A, Organization NY, Pagel K, Pal LR, Pandey G, Park T, Pearson N, Pejaver V, Peng J, Petersen BS, Pirooznia M, Piryatinska A, Plotts C, Potash JB, Pullinger CR, Radivojac P, Rana S, Rao AR, Rao A, Repo S, Rine J, Ritchie G, Rogan P, Roth F, Rousseau F, Sabeti P, Sanford J, Scaini MC, Schmitt N, Schwarz JM, Schymkowitz J, Searls DB, Seok C, Shackelford G, Shah S, Shatsky M, Shendure J, Sheridan M, Shigeta R, Shihab HA, Shim JE, Shin J, Shin S, Shmulevich I, Shon J, Silver BR, Sinnott-Armstrong N, Smithers B, Snyder M, Sokolov A, Son YA, Srinivasan R, Stanke M, Sterne-Weiler T, Stitziel N, Stuart J, Su A, Sundaram L, Sunyaev S, Tang PLF, Tang P, Tavtigian S, Teerakulkittipong N, Tewhey R, Thurlby N, Thusberg J, Tian K, Tokheim C, Tosatto SCE, Tuncel Y, Turner T, Unger RS, Uppal A, Ustunkar G, Valiaho J, Veltman J, Vihinen M, Wahl M, Wainberg M, Wang LS, Wang M, Wang M, Wang X, Wang Y, Wei L, Wei Q, Wei L, Weile J, Welch R, Wilson S, Wu C, Xu L, Xu Q, Yang Y, Yates C, Yee S, Yeleswarapu SJ, Yin Y, Yu CH, Yu GK, Yuan D, Zandi P, Zaucha J, Zeng H, and Zuhl M.