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>.
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>.
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.
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.
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.
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.
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.
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.
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.
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.
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>.
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
Interactive PheWAS results from analyses conducted using Michigan Genomics Initiative
and UK Biobank data.
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.
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
R/Shiny web application for kidney renal clear cell carcinoma.
Reference: Boonstra, Philip S. and Barbaro, Ryan P., "Incorporating Historical Models with Adaptive
Bayesian Updates" (2018) Biostatistics https://doi.org/10.1093/biostatistics/kxy053
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>.
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>.
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.
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>.
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.
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.
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.
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).
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.
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.
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.
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.
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.
