Your browser doesn't support javascript.
loading
Assessing predictions on fitness effects of missense variants in HMBS in CAGI6.
Zhang, Jing; Kinch, Lisa; Katsonis, Panagiotis; Lichtarge, Olivier; Jagota, Milind; Song, Yun S; Sun, Yuanfei; Shen, Yang; Kuru, Nurdan; Dereli, Onur; Adebali, Ogun; Alladin, Muttaqi Ahmad; Pal, Debnath; Capriotti, Emidio; Turina, Maria Paola; Savojardo, Castrense; Martelli, Pier Luigi; Babbi, Giulia; Casadio, Rita; Pucci, Fabrizio; Rooman, Marianne; Cia, Gabriel; Tsishyn, Matsvei; Strokach, Alexey; Hu, Zhiqiang; van Loggerenberg, Warren; Roth, Frederick P; Radivojac, Predrag; Brenner, Steven E; Cong, Qian; Grishin, Nick V.
Afiliação
  • Zhang J; Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Kinch L; Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Katsonis P; Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Lichtarge O; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Jagota M; Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Song YS; Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Sun Y; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
  • Shen Y; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
  • Kuru N; Computer Science Division, University of California, Berkeley, CA, 94720, USA.
  • Dereli O; Computer Science Division, University of California, Berkeley, CA, 94720, USA.
  • Adebali O; Department of Statistics, University of California, Berkeley, Berkeley, CA, 94720, USA.
  • Alladin MA; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA.
  • Pal D; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA.
  • Capriotti E; Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Turkey.
  • Turina MP; Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Turkey.
  • Savojardo C; Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Turkey.
  • Martelli PL; Department of Computational and Data Sciences, Indian Institute of Science, Bangaluru, 560012, India.
  • Babbi G; Department of Computational and Data Sciences, Indian Institute of Science, Bangaluru, 560012, India.
  • Casadio R; Department of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
  • Pucci F; Department of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
  • Rooman M; Department of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
  • Cia G; Department of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
  • Tsishyn M; Department of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
  • Strokach A; Department of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
  • Hu Z; Computational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
  • van Loggerenberg W; Computational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
  • Roth FP; Computational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
  • Radivojac P; Computational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
  • Brenner SE; Department of Computer Science, University of Toronto, Toronto, ON, M5S 2E4, Canada.
  • Cong Q; Department of Plant and Microbial Biology, University of California, Berkeley, CA, 94720, USA.
  • Grishin NV; Center for Computational Biology, University of California, Berkeley, Berkeley, CA, 94720, USA.
Hum Genet ; 2024 Aug 07.
Article em En | MEDLINE | ID: mdl-39110250
ABSTRACT
This paper presents an evaluation of predictions submitted for the "HMBS" challenge, a component of the sixth round of the Critical Assessment of Genome Interpretation held in 2021. The challenge required participants to predict the effects of missense variants of the human HMBS gene on yeast growth. The HMBS enzyme, critical for the biosynthesis of heme in eukaryotic cells, is highly conserved among eukaryotes. Despite the application of a variety of algorithms and methods, the performance of predictors was relatively similar, with Kendall's tau correlation coefficients between predictions and experimental scores around 0.3 for a majority of submissions. Notably, the median correlation (≥ 0.34) observed among these predictors, especially the top predictions from different groups, was greater than the correlation observed between their predictions and the actual experimental results. Most predictors were moderately successful in distinguishing between deleterious and benign variants, as evidenced by an area under the receiver operating characteristic (ROC) curve (AUC) of approximately 0.7 respectively. Compared with the recent two rounds of CAGI competitions, we noticed more predictors outperformed the baseline predictor, which is solely based on the amino acid frequencies. Nevertheless, the overall accuracy of predictions is still far short of positive control, which is derived from experimental scores, indicating the necessity for considerable improvements in the field. The most inaccurately predicted variants in this round were associated with the insertion loop, which is absent in many orthologs, suggesting the predictors still heavily rely on the information from multiple sequence alignment.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Hum Genet Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Hum Genet Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos