The HIMA R package is described in:

Zhang H, Zheng Y, Hou L, Liu L (2025). “HIMA: An R Package for High-Dimensional Mediation Analysis.” Journal of Data Science, 1-15. doi:10.6339/25-JDS1192.

The classic HIMA method is described in:

Zhang H, Zheng Y, Zhang Z, Gao T, Joyce B, Yoon G, Zhang W, Schwartz J, Just A, Colicino E, Vokonas P, Zhao L, Lv J, Baccarelli A, Hou L, Liu L (2016). “Estimating and Testing High-dimensional Mediation Effects in Epigenetic Studies.” Bioinformatics, 32(20), 3150-3154. doi:10.1093/bioinformatics/btw351.

The survival HIMA method is described in:

Zhang H, Zheng Y, Hou L, Liu L (2021). “Mediation Analysis for Survival Data with High-Dimensional Mediators.” Bioinformatics, 37(21), 3815-3821. doi:10.1093/bioinformatics/btab564.

The microbiome HIMA method is described in:

Zhang H, Chen J, Feng Y, Wang C, Li H, Liu L (2021). “Mediation effect selection in high-dimensional and compositional microbiome data.” Statistics in Medicine, 40(4), 885-896. doi:10.1002/sim.8808.

The DBlasso HIMA method is described in:

Perera C, Zhang H, Zheng Y, Hou L, Qu A, Zheng C, Xie K, Liu L (2022). “HIMA2: high-dimensional mediation analysis and its application in epigenome-wide DNA methylation data.” BMC Bioinformatics, 23(1), 296. doi:10.1186/s12859-022-04748-1.

The quantile HIMA method is described in:

Zhang H, Hong X, Zheng Y, Hou L, Zheng C, Wang X, Liu L (2024). “High-Dimensional Quantile Mediation Analysis with Application to a Birth Cohort Study of Mother–Newborn Pairs.” Bioinformatics, 40(2). doi:10.1093/bioinformatics/btae055.

The efficient HIMA method is described in:

Bai X, Zheng Y, Hou L, Zheng C, Liu L, Zhang H (2024). “An Efficient Testing Procedure for High-dimensional Mediators with FDR Control.” Statistics in Biosciences, 17, 615-629. doi:10.1007/s12561-024-09447-4.

The longitudinal survival HIMA method is described in:

Liu L, Zhang H, Zheng Y, Gao T, Zheng C, Zhang K, Hou L, Liu L (2025). “High-dimensional mediation analysis for longitudinal mediators and survival outcomes.” Briefings in Bioinformatics, 26(3). doi:10.1093/bib/bbaf206.

Corresponding BibTeX entries:

  @Article{hima,
    title = {{HIMA: An R Package for High-Dimensional Mediation
      Analysis}},
    author = {Haixiang Zhang and Yinan Zheng and Lifang Hou and Lei
      Liu},
    journal = {Journal of Data Science},
    year = {2025},
    pages = {1-15},
    doi = {10.6339/25-JDS1192},
  }

  @Article{hima_classic,
    title = {{Estimating and Testing High-dimensional Mediation Effects
      in Epigenetic Studies}},
    author = {Haixiang Zhang and Yinan Zheng and Zhou Zhang and Tao Gao
      and Brian Joyce and Grace Yoon and Wei Zhang and Joel Schwartz
      and Allan Just and Elena Colicino and Pantel Vokonas and Lihui
      Zhao and Jinchi Lv and Andrea Baccarelli and Lifang Hou and Lei
      Liu},
    journal = {Bioinformatics},
    year = {2016},
    volume = {32},
    number = {20},
    pages = {3150-3154},
    doi = {10.1093/bioinformatics/btw351},
    pubmed = {27357171},
  }

  @Article{hima_survival,
    title = {{Mediation Analysis for Survival Data with
      High-Dimensional Mediators}},
    author = {Haixiang Zhang and Yinan Zheng and Lifang Hou and Lei
      Liu},
    journal = {Bioinformatics},
    year = {2021},
    volume = {37},
    number = {21},
    pages = {3815-3821},
    doi = {10.1093/bioinformatics/btab564},
    pubmed = {34343267},
  }

  @Article{hima_microbiome,
    title = {{Mediation effect selection in high-dimensional and
      compositional microbiome data}},
    author = {Haixiang Zhang and Jun Chen and Yang Feng and Chan Wang
      and Huilin Li and Lei Liu},
    journal = {Statistics in Medicine},
    year = {2021},
    volume = {40},
    number = {4},
    pages = {885-896},
    doi = {10.1002/sim.8808},
    pubmed = {33205470},
  }

  @Article{hima_dblasso,
    title = {{HIMA2: high-dimensional mediation analysis and its
      application in epigenome-wide DNA methylation data}},
    author = {Chamila Perera and Haixiang Zhang and Yinan Zheng and
      Lifang Hou and Annie Qu and Cheng Zheng and Ke Xie and Lei Liu},
    journal = {BMC Bioinformatics},
    year = {2022},
    volume = {23},
    number = {1},
    pages = {296},
    doi = {10.1186/s12859-022-04748-1},
    pubmed = {35879655},
  }

  @Article{hima_quantile,
    title = {{High-Dimensional Quantile Mediation Analysis with
      Application to a Birth Cohort Study of Mother–Newborn Pairs}},
    author = {Haixiang Zhang and Xiumei Hong and Yinan Zheng and Lifang
      Hou and Cheng Zheng and Xiaobin Wang and Lei Liu},
    journal = {Bioinformatics},
    year = {2024},
    volume = {40},
    number = {2},
    doi = {10.1093/bioinformatics/btae055},
    pubmed = {38290773},
  }

  @Article{hima_efficient,
    title = {{An Efficient Testing Procedure for High-dimensional
      Mediators with FDR Control}},
    author = {Xueyan Bai and Yinan Zheng and Lifang Hou and Cheng Zheng
      and Lei Liu and Haixiang Zhang},
    journal = {Statistics in Biosciences},
    year = {2024},
    volume = {17},
    pages = {615-629},
    doi = {10.1007/s12561-024-09447-4},
  }

  @Article{hima_longitudinal,
    title = {{High-dimensional mediation analysis for longitudinal
      mediators and survival outcomes}},
    author = {Lili Liu and Haixiang Zhang and Yinan Zheng and Tao Gao
      and Cheng Zheng and Kai Zhang and Lifang Hou and Lei Liu},
    journal = {Briefings in Bioinformatics},
    year = {2025},
    volume = {26},
    number = {3},
    doi = {10.1093/bib/bbaf206},
    pubmed = {40350699},
  }