Software

Organized by topic

 

adaptBayes

  • This package contains R functions implementing the adaptive priors described in Boonstra and Barbaro (2018).
  • Language(s): R
  • Faculty: Philip S. Boonstra. Download: Github.
  • Reference: Boonstra, Philip S. and Barbaro, Ryan P., "Incorporating Historical Models with Adaptive Bayesian Updates" (2018) Biostatistics https://doi.org/10.1093/biostatistics/kxy053

Bama

  • Mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. Bayesian Mediation Analysis (BAMA), developed by Song et al (2018) <doi:10.1101/467399>.
  • Faculty: Bhramar Mukherjee, Min Zhang, Xiang Zhou. Download: CRAN.
  • Song, Y., Zhou, X., Zhang, M., Zhao, W., Liu, Y., Kardia, S., Roux, A.D., Needham, B., Smith, J.A. and Mukherjee, B., 2018. Bayesian Shrinkage Estimation of High Dimensional Causal Mediation Effects in Omics Studies. bioRxiv, p.467399.

BEHAVIOUR

fast-opt

  • Package for fast computation of the Optional Polya Tree (OPT).
  • Faculty: Hui Jiang. Download: Website.

Glmnet for MATLAB

  • A matlab wrapper for glmnet, a solver for fitting Lasso (L1) and elastic-net regularized generalized linear models.
  • Faculty: Hui Jiang. Download: Website.

LGEWIS

  • Functions for genome-wide association studies (GWAS)/gene-environment-wide interaction studies (GEWIS) with longitudinal outcomes and exposures.
  • Faculty: Seunggeun Shawn Lee, Bhramar Mukherjee, Min Zhang. Download: CRAN.
  • References: He et al. (2017) "Set-Based Tests for Gene-Environment Interaction in Longitudinal Studies" and He et al. (2017) "Rare-variant association tests in longitudinal studies, with an application to the Multi-Ethnic Study of Atherosclerosis (MESA)". 

Lodi

  • Impute observed values below the limit of detection (LOD) via censored likelihood multiple imputation (CLMI) in single-pollutant models, developed by Boss et al (2019) <doi:10.1097/EDE.0000000000001052>.
  • Faculty: Seunggeun Shawn Lee, Bhramar Mukherjee, Min Zhang. Download: CRAN.
  • References: Boss, J., Mukherjee, B., Ferguson, K.K., Aker, A., Alshawabkeh, A.N., Cordero, J.F., Meeker, J.D. and Kim, S., 2019. Estimating outcome-exposure associations when exposure biomarker detection limits vary across batches. Epidemiology, 30(5), pp.746-755.

MMCR

nltm

  • Non-linear transformation models (nltm) for analyzing survival data.
  • Faculty: Alexander Tsodikov. Download: Github.
  • Reference: Tsodikov, A., 2003. Semiparametric models: a generalized self‐consistency approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 65(3), pp.759-774.

RankModeling

  • Penalized multistage models for ordered data.
  • Language(s): R
  • Faculty: Philip S. Boonstra. Download: Github.
  • Reference: Boonstra, Philip S. and Krauss, John C., "Inferring a consensus problem list using penalized multistage models for ordered data" (October 2019) The University of Michigan Department of Biostatistics Working Paper Series. Working Paper 126.

 

CisGenome Browser

  • A flexible stand-alone tool for genomic data visualization.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Jiang, H., Wang, F., Dyer, N.P., Wong, W.H. (2010) CisGenome Browser: A Flexible Tool For Genomic Data Visualization, Bioinformatics, 26 (14).

CisGenome

  • An integrated tool for tiling array, genome and cis-regulatory element analysis, working together with CisGenome Browser. 
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Hongkai Ji, Hui Jiang, Wenxiu Ma, David S. Johnson, Richard M. Myers and Wing H. Wong (2008) An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nature Biotechnology, 26: 1293-1300. doi:10.1038/nbt.1505.

iBAG

mseq

  • An R package for modeling non-uniformity in short-read rates in RNA-Seq data.
  • Faculty: Hui Jiang. Download: CRAN Archive.

PRECISE

  • Proteomic based integrated subject-specific networks in cancer.
  • Faculty: Veera Baladandayuthapani. Download: Github, Website.
  • Reference: Ha, M.J., Banerjee, S., Akbani, R., Liang, H., Mills, G.B., Do, K.A. and Baladandayuthapani, V., 2018. Personalized Integrated Network Modeling of the Cancer Proteome Atlas. Scientific reports, 8(1), p.14924. <doi:10.1038/s41598-018-32682-x>.

rSeqNP

  • A non-parametric approach for detecting differential expression and splicing from RNA-Seq data.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Shi, Y., Chinnaiyan, A. M., Jiang, H. (2015) rSeqNP: A non-parametric approach for detecting differential ex-pression and splicing from RNA-Seq data Bioinformatics, in press.

rSeqDiff

  • Detecting differential isoform expression from RNA-seq data.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Shi, Y., Jiang, H. (2013). rSeqDiff: Detecting differential isoform expression from RNA-Seq data using hierarchical likelihood ratio test, PLoS One, 8 (11): e79448.

SeqAlto

  • Fast and accurate read alignment for resequencing.
  • Faculty: Hui Jiang. Download: Website.
  • References: John C. Mu, Hui Jiang, Amirhossein Kiani, Marghoob Mohiyuddin, Narges Bani Asadi and Wing H. Wong, Fast and Accurate Read Alignment for Resequencing, Bioinformatics, 2012.

SeqMap

  • A tool for mapping millions of short sequences to the genome.
  • Faculty: Hui Jiang. Download: Website.
  • References: Jiang, H., Wong, W.H. (2008) SeqMap: Mapping Massive Amount of Oligonucleotides to the Genome, Bioinformatics, 24(20).

SpliceMap

  • SpliceMap is a de novo splice junction discovery and alignment tool. It offers high sensitivity and support for arbitrary RNA-seq read lengths.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Kin Fai Au, Hui Jiang, Lan Lin, Yi Xing, and Wing Hung Wong. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Research, Advance access published on April 5, 2010.

Tnseq

  • Identification of conditionally essential genes using high-throughput sequencing data from transposon mutant libraries.
  • Faculty: Lili Zhao. Download: CRAN.
  • Reference: Zhao, L., Anderson, M.T., Wu, W., Mobley, H.L. and Bachman, M.A., 2017. TnseqDiff: identification of conditionally essential genes in transposon sequencing studies. BMC bioinformatics, 18(1), p.326.

 

SMART Sample Size Calculator

  • Sample size calculator applet for SMART studies.
  • Faculty: Kelley Kidwell. Download: Shiny Application.
  • Reference: Oetting, A., Levy, J., Weiss, R. and Murphy, S. (2007), "Statistical methodology for a SMART design in the development of adaptive treatment strategies ," in Causality and Psychopathology: Finding the Determinants of Disorders and their Cures (American Psychopathological Association), Arlington, VA: American Psychiatric Publishing, Inc., pp. 179-205.

snSMART

  • Small n Sequential, Multiple Assignment, Randomized Trial (snSMART) calculation applet.
  • Faculty: Kelley Kidwell. Download: Website.
  • Reference: Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M., 2018. A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs). Statistics in medicine, 37(26), pp.3723-3732.

subgxe

  • R package that implements p-value assisted subset testing for association (pASTA), a method developed by Yu et al. (2019) <doi:10.1159/000496867>.
  • Faculty: Bhramar Mukherjee, Xiang Zhou, Seunggeun Shawn Lee. Download: CRAN.
  • References: Yu, Y., Xia, L., Lee, S., Zhou, X., Stringham, H.M., Boehnke, M. and Mukherjee, B., 2018. Subset-Based Analysis using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes. Human heredity, 83(6), pp.283-314.

 

PRSweb

SAMBA

  • Misclassification of EHR (Electronic Health Record)-derived disease status and lack of representativeness of the study sample can result in substantial bias in effect estimates and can impact power and type I error for association tests. 'SAMBA' implements several methods for obtaining bias-corrected point estimates along with valid standard errors as proposed in Beesley and Mukherjee (2020) <doi:10.1101/2019.12.26.19015859>, currently under review.
  • Faculty: Bhramar Mukherjee. Download: CRAN, Github.
  • References: Beesley, L.J. and Mukherjee, B., 2019. Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification. medRxiv.

Organized by faculty

BEHAVIOUR

iBAG

MMCR

PRECISE

  • Proteomic based integrated subject-specific networks in cancer.
  • Faculty: Veera Baladandayuthapani. Download: Github, Website.
  • Reference: Ha, M.J., Banerjee, S., Akbani, R., Liang, H., Mills, G.B., Do, K.A. and Baladandayuthapani, V., 2018. Personalized Integrated Network Modeling of the Cancer Proteome Atlas. Scientific reports, 8(1), p.14924. <doi:10.1038/s41598-018-32682-x>.

adaptBayes

  • This package contains R functions implementing the adaptive priors described in Boonstra and Barbaro (2018).
  • Language(s): R
  • Faculty: Philip S. Boonstra. Download: Github.
  • Reference: Boonstra, Philip S. and Barbaro, Ryan P., "Incorporating Historical Models with Adaptive Bayesian Updates" (2018) Biostatistics https://doi.org/10.1093/biostatistics/kxy053

RankModeling

  • Penalized multistage models for ordered data.
  • Language(s): R
  • Faculty: Philip S. Boonstra. Download: Github.
  • Reference: Boonstra, Philip S. and Krauss, John C., "Inferring a consensus problem list using penalized multistage models for ordered data" (October 2019) The University of Michigan Department of Biostatistics Working Paper Series. Working Paper 126.

Bama

  • Mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. Bayesian Mediation Analysis (BAMA), developed by Song et al (2018) <doi:10.1101/467399>.
  • Faculty: Bhramar Mukherjee, Min Zhang, Xiang Zhou. Download: CRAN.
  • Song, Y., Zhou, X., Zhang, M., Zhao, W., Liu, Y., Kardia, S., Roux, A.D., Needham, B., Smith, J.A. and Mukherjee, B., 2018. Bayesian Shrinkage Estimation of High Dimensional Causal Mediation Effects in Omics Studies. bioRxiv, p.467399.

LGEWIS

  • Functions for genome-wide association studies (GWAS)/gene-environment-wide interaction studies (GEWIS) with longitudinal outcomes and exposures.
  • Faculty: Seunggeun Shawn Lee, Bhramar Mukherjee, Min Zhang. Download: CRAN.
  • References: He et al. (2017) "Set-Based Tests for Gene-Environment Interaction in Longitudinal Studies" and He et al. (2017) "Rare-variant association tests in longitudinal studies, with an application to the Multi-Ethnic Study of Atherosclerosis (MESA)". 

Lodi

  • Impute observed values below the limit of detection (LOD) via censored likelihood multiple imputation (CLMI) in single-pollutant models, developed by Boss et al (2019) <doi:10.1097/EDE.0000000000001052>.
  • Faculty: Seunggeun Shawn Lee, Bhramar Mukherjee, Min Zhang. Download: CRAN.
  • References: Boss, J., Mukherjee, B., Ferguson, K.K., Aker, A., Alshawabkeh, A.N., Cordero, J.F., Meeker, J.D. and Kim, S., 2019. Estimating outcome-exposure associations when exposure biomarker detection limits vary across batches. Epidemiology, 30(5), pp.746-755.

PRSweb

SAMBA

  • Misclassification of EHR (Electronic Health Record)-derived disease status and lack of representativeness of the study sample can result in substantial bias in effect estimates and can impact power and type I error for association tests. 'SAMBA' implements several methods for obtaining bias-corrected point estimates along with valid standard errors as proposed in Beesley and Mukherjee (2020) <doi:10.1101/2019.12.26.19015859>, currently under review.
  • Faculty: Bhramar Mukherjee. Download: CRAN, Github.
  • References: Beesley, L.J. and Mukherjee, B., 2019. Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification. medRxiv.

subgxe

  • R package that implements p-value assisted subset testing for association (pASTA), a method developed by Yu et al. (2019) <doi:10.1159/000496867>.
  • Faculty: Bhramar Mukherjee, Xiang Zhou, Seunggeun Shawn Lee. Download: CRAN.
  • References: Yu, Y., Xia, L., Lee, S., Zhou, X., Stringham, H.M., Boehnke, M. and Mukherjee, B., 2018. Subset-Based Analysis using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes. Human heredity, 83(6), pp.283-314.

SMART Sample Size Calculator

  • Sample size calculator applet for SMART studies.
  • Faculty: Kelley Kidwell. Download: Shiny Application.
  • Reference: Oetting, A., Levy, J., Weiss, R. and Murphy, S. (2007), "Statistical methodology for a SMART design in the development of adaptive treatment strategies ," in Causality and Psychopathology: Finding the Determinants of Disorders and their Cures (American Psychopathological Association), Arlington, VA: American Psychiatric Publishing, Inc., pp. 179-205.

snSMART 

  • Small n Sequential, Multiple Assignment, Randomized Trial (snSMART) calculation applet.
  • Faculty: Kelley Kidwell. Download: Website.
  • Reference: Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M., 2018. A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs). Statistics in medicine, 37(26), pp.3723-3732.

Tnseq

  • Identification of conditionally essential genes using high-throughput sequencing data from transposon mutant libraries.
  • Faculty: Lili Zhao. Download: CRAN.
  • Reference: Zhao, L., Anderson, M.T., Wu, W., Mobley, H.L. and Bachman, M.A., 2017. TnseqDiff: identification of conditionally essential genes in transposon sequencing studies. BMC bioinformatics, 18(1), p.326.

CisGenome Browser

  • A flexible stand-alone tool for genomic data visualization.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Jiang, H., Wang, F., Dyer, N.P., Wong, W.H. (2010) CisGenome Browser: A Flexible Tool For Genomic Data Visualization, Bioinformatics, 26 (14).

CisGenome

  • An integrated tool for tiling array, genome and cis-regulatory element analysis, working together with CisGenome Browser. 
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Hongkai Ji, Hui Jiang, Wenxiu Ma, David S. Johnson, Richard M. Myers and Wing H. Wong (2008) An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nature Biotechnology, 26: 1293-1300. doi:10.1038/nbt.1505.

fast-opt

  • Package for fast computation of the Optional Polya Tree (OPT).
  • Faculty: Hui Jiang. Download: Website.

Glmnet for MATLAB

  • A matlab wrapper for glmnet, a solver for fitting Lasso (L1) and elastic-net regularized generalized linear models.
  • Faculty: Hui Jiang. Download: Website.

mseq

  • An R package for modeling non-uniformity in short-read rates in RNA-Seq data.
  • Faculty: Hui Jiang. Download: CRAN Archive.

rSeqNP

  • A non-parametric approach for detecting differential expression and splicing from RNA-Seq data.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Shi, Y., Chinnaiyan, A. M., Jiang, H. (2015) rSeqNP: A non-parametric approach for detecting differential ex-pression and splicing from RNA-Seq data Bioinformatics, in press.

rSeqDiff

  • Detecting differential isoform expression from RNA-seq data.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Shi, Y., Jiang, H. (2013). rSeqDiff: Detecting differential isoform expression from RNA-Seq data using hierarchical likelihood ratio test, PLoS One, 8 (11): e79448.

rSeq

  • rSeq is a set of tools for RNA-Seq data analysis. It consists of programs that deal with many aspects of RNA-Seq data analysis, such as read quality assessment, reference sequence generation, sequence mapping, gene and isoform expressions (RPKMs) estimation, etc.
  • Faculty: Hui Jiang. Download: Website.
  • References: [1] Jiang, H., Wong, W.H. (2009) Statistical Inferences for Isoform Expression in RNA-Seq, Bioinformatics, 25(8), 1026–1032. [2] Salzman, J., Jiang, H., Wong, W. H. (2011) Statistical Modeling of RNA-Seq Data, Statistical Science, 26 (1): 62-83.

SeqAlto

  • Fast and accurate read alignment for resequencing.
  • Faculty: Hui Jiang. Download: Website.
  • References: John C. Mu, Hui Jiang, Amirhossein Kiani, Marghoob Mohiyuddin, Narges Bani Asadi and Wing H. Wong, Fast and Accurate Read Alignment for Resequencing, Bioinformatics, 2012.

SeqMap

  • A tool for mapping millions of short sequences to the genome.
  • Faculty: Hui Jiang. Download: Website.
  • References: Jiang, H., Wong, W.H. (2008) SeqMap: Mapping Massive Amount of Oligonucleotides to the Genome, Bioinformatics, 24(20).

SpliceMap

  • SpliceMap is a de novo splice junction discovery and alignment tool. It offers high sensitivity and support for arbitrary RNA-seq read lengths.
  • Faculty: Hui Jiang. Download: Website.
  • Reference: Kin Fai Au, Hui Jiang, Lan Lin, Yi Xing, and Wing Hung Wong. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Research, Advance access published on April 5, 2010.

nltm

  • Non-linear transformation models (nltm) for analyzing survival data.
  • Faculty: Alexander Tsodikov. Download: Github.
  • Reference: Tsodikov, A., 2003. Semiparametric models: a generalized self‐consistency approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 65(3), pp.759-774.