References in zbMATH (referenced in 48 articles )

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  1. Daghyani, Masoud; Zamzami, Nuha; Bouguila, Nizar: Toward an efficient computation of log-likelihood functions in statistical inference: overdispersed count data clustering (2020)
  2. Jia, Chen: Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data (2020)
  3. Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Vatanen, Tommi; Huttenhower, Curtis; Trippa, Lorenzo: Bayesian mixed effects models for zero-inflated compositions in microbiome data analysis (2020)
  4. Bandara, Udika; Gill, Ryan; Mitra, Riten: On computing maximum likelihood estimates for the negative binomial distribution (2019)
  5. Kuan-Hao Chao, Yi-Wen Hsiao, Yi-Fang Lee, Chien-Yueh Lee, Liang-Chuan Lai, Mong-Hsun Tsai, Tzu-Pin Lu, Eric Y. Chuang: RNASeqR: an R package for automated two-group RNA-Seq analysis workflow (2019) arXiv
  6. Li, Xiaohong; Wu, Dongfeng; Cooper, Nigel G. F.; Rai, Shesh N.: Sample size calculations for the differential expression analysis of RNA-seq data using a negative binomial regression model (2019)
  7. Monod, Anthea; Kališnik, Sara; Patiño-Galindo, Juan Ángel; Crawford, Lorin: Tropical sufficient statistics for persistent homology (2019)
  8. Plunkett, Amanda; Park, Junyong: Two-sample test for sparse high-dimensional multinomial distributions (2019)
  9. Dadaneh, Siamak Zamani; Qian, Xiaoning; Zhou, Mingyuan: BNP-seq: Bayesian nonparametric differential expression analysis of sequencing count data (2018)
  10. Liu, Lydia T.; Dobriban, Edgar; Singer, Amit: (e)PCA: high dimensional exponential family PCA (2018)
  11. Qiu, Yumou; Chen, Song Xi; Nettleton, Dan: Detecting rare and faint signals via thresholding maximum likelihood estimators (2018)
  12. Song, Wei; Liu, Huaping; Wang, Jiajia; Kong, Yan; Yin, Xia; Zang, Weidong: MATHT: a web server for comprehensive transcriptome data analysis (2018)
  13. Yang, Tae Young; Jeong, Seongmun: Controlling the false-discovery rate by procedures adapted to the length bias of RNA-seq (2018)
  14. Bécu, Jean-Michel; Grandvalet, Yves; Ambroise, Christophe; Dalmasso, Cyril: Beyond support in two-stage variable selection (2017)
  15. Fu, Rong; Wang, Pei; Ma, Weiping; Taguchi, Ayumu; Wong, Chee-Hong; Zhang, Qing; Gazdar, Adi; Hanash, Samir M.; Zhou, Qinghua; Zhong, Hua; Feng, Ziding: A statistical method for detecting differentially expressed SNVs based on next-generation RNA-seq data (2017)
  16. Lun, Aaron T. L.; Smyth, Gordon K.: No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq data (2017)
  17. Martella, Francesca; Alfò, Marco: A finite mixture approach to joint clustering of individuals and multivariate discrete outcomes (2017)
  18. Shang, Kan; Reilly, Cavan: Non parametric Bayesian analysis of the two-sample problem with censoring (2017)
  19. Bonafede, Elisabetta; Picard, Franck; Robin, Stéphane; Viroli, Cinzia: Modeling overdispersion heterogeneity in differential expression analysis using mixtures (2016)
  20. Cui, Shiqi; Ji, Tieming; Li, Jilong; Cheng, Jianlin; Qiu, Jing: What if we ignore the random effects when analyzing RNA-seq data in a multifactor experiment (2016)

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