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Professor Emeritus

Dept. of Statistics
Huck Institute of Life Sciences


CV

New Researcher’s Guide (IMS)

Points of Significance Articles

Summary of research interests

Dr. Altman’s interest in statistics stems from her broad interests in the application of the mathematical sciences to problems in other disciplines in particular, medical and biological sciences, earth and environmental sciences, and social sciences. Her statistical interests include bioinformatics, high dimensional data, nonparametric smoothing, model selection and analysis of functional and longitudinal data. Dr. Altman’s current research is in bioinformatics and dimension reduction.

Dr. Altman’s bioinformatics work includes the design and analysis of microarray and RNA-seq studies, functional genomics and gene clustering (by position on the chromosome, by sequence structure, and by function). Much of this work is currently in collaboration with biologists such as Claude dePamphilis (plants) and Iliana Baums (coral). She also works in more applied areas such as social insects with Christina Grozinger and plant pathology with Tim McNellis. In medical bioinformatics, Dr. Altman has been working on single cell RNA-seq for circulating tumor cells with Gary Clawson, the analysis of microbiome data and on the analysis of protein microarrays for antigen analysis.

Altman’s work in functional data analysis and nonparametricsmoothing has focused on problems in which the errors are correlated,and parametric covariate effects are of interest. Current areas of interest include inference for self-modeling regression when curves are the response in a comparative experiment and fitting and inference for longitudinal and spatial data with a smooth component.

Altman’s work in high dimensional data has taken two directions. She is working on multiple testing and other high dimensional estimation and testing problems which occur in parallel estimation and testing situations such as the analysis of `omics’ data. She also works on dimension reduction focusing on extensions of supervised and unsupervised methods based on matrix decompositions.

Altman is also a member of the Huck Institutes of Life Sciences specializing in Bioinformatics and Genomics.

Dr. Altman has directed 14 MS theses and directed or co-directed 6 Ph.D. theses, as of 2023.

Dr. Altman retired in 2019, but continues to write articles and collaborate with scientists in other fields.

Nature Methods Articles – Points of Significance

Altman is co-author, with the incredible Martin Krzywinski and occasionally others, of the Points of Significance Articles. in Nature Methods. These articles cover a number of topics in statistics which should be useful to biologists and bioinformaticians. It is part of the Nature Publishing Reproducibility Initiative.

Complete list of Points of Significance Articles

There is a companion set of articles on creating good graphics Points of View. Altman is not a co-author but highly recommends these articles.

Teaching

Stat 414 Introduction to Probability
Stat 440 Statistical Computing
Stat 503 Experimental Design 2
Stat 511 Applied Linear Regression
Stat 512 Design of Experiments
Stat 540 Computationally Intensive Statistical Inference
Stat 555 Statistical Analysis of High Throughput Biology Experiments
Stat 580 Statistical Computing
Stat 597C Computing Environments for Statistics
Stat/Bio/CSE 598D Bioinformatics II – Microarrays
Stat/IBIOS 598A Current Research in Statistical Genomics

Talks

Bioinformatics Talks

Statistics Talks

Publications

Complete list of publications

Representative publications: Statistics

Altman, N. S. (2016) Comment on The ASA’s Statement on p-Values: Context, Process, and Purpose.(R. Wasserstein and N. Lazar) The American Statistician, 70(2) doi:/10.1080/00031305.2016.1154108

Dialsingh, I., Austin, S. and Altman, N.S. (2015) Estimating the Percentage of True Null Hypotheses when the
Statistics are Discrete. Bioinformatics, 31 (14) 2303–2309,doi:10.1093/bioinformatics/btv104 oxfordJournals

Stefanie R. Austin, Isaac Dialsingh, Naomi Altman. (2014) Multiple Hypothesis Testing: A review. J. Indian
Soc. Of Agricultural Stat. 68:303-314. JISAS

Luo, W. and Altman, N. S.  (2013) A Characterization of Conjugate Priors in Linear Exponential Families with application to Dimension Reduction. Statistics and Probability Letters, 83, 650-654.sciencedirect

Li, B., Kim, M.K. and Altman, N.S.  (2010) On dimension folding of matrix or array valued statistical objects. Annals of
Statistics, 38, 1094-1121; arxiv.org

Altman, N.S. and J. Villarreal. (2004). Self-modeling regression with random effects using penalized splines, Canadian Journal of Statistics, 32, 251-268. https://doi.org/10.2307/3315928, jstor WileyOnline

Altman, N.S. (2000) Krige, smooth, both or neither? (with discussion). Australian and New Zealand Journal of Statistics, 42: 441-461. Wiley

Altman, N.S. and C. Léger. (1997) On the optimality of prediction-based selection criteria and the convergence rates of estimators. Journal Royal Statistical Society, Series B, 59, 205-216. jstor

Altman, N.S. and G. Casella.(1995) Nonparametric empirical Bayes growth curve analysis. J. of the Amer. Stat. Assoc. 90, 508-515. https://doi.org/10.2307/2291061 jstor

Léger, C. and Altman, N.S., (1993) Assessing Influence in Variable Selection Problems. J. of the Amer. Stat. Assoc., 88, 547-556. https://doi.org/10.2307/2290335

Altman, N.S, (1990) Kernel Smoothing of Data with Correlated Errors. J. of the Amer. Stat. Assoc., 85, 749-758. jstor https://doi.org/10.2307/2290011


Representative publications: Bioinformatics

Jessica Waite, Elizabeth Kelly, Huiting Zhang, Heidi Hargarten, Sumyya Waliullah, Naomi Altman, Claude dePamphilis, Loren Honaas, Lee Kalcsits (2023) Transcriptomic approach to uncover dynamic events in the development of mid-season sunburn in apple fruit. G3: Genes, Genomes, Genetics G3

Voelkl B, Altman NS, Forsman A, Forstmeier W, Gurevitch J, Jaric I , Karp NA, Kas MJ, Schielzeth H, Van de Casteele T, Würbel H. (2020) Reproducibility of animal research in light of biological variation. Nat Rev Neurosci, 21, 384–393. https://doi.org/10.1038/s41583-020-0313-3

Loren A. Honaas, Sam Jones, Nina Farell, William Kamerow, Huiting Zhang, Kathryn Vescio, Naomi S. Altman, John I. Yoder and Claude W. dePamphilis. (2019) Risk versus reward: host dependent parasite mortality rates and phenotypes in the facultative generalist Triphysaria versicolor. BMC Plant Biology. 19, 334. https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-019-1856-1

Qingyu Wang, Cooduvalli S. Shashikant, Naomi S. Altman, Santhosh Girirajan. (2017) . Novel metrics to measure coverage in whole exome sequencing datasets reveal local and global non-uniformity. Scientific Reports, 7(1), 885. SciRep

Honaas L.A., Altman N.S., Krzywinski M. (2016) Study Design for Sequencing Studies. In: Mathé E., Davis S. (eds) Statistical Genomics. Methods in Molecular Biology, vol 1418. Humana Press, New York, NY https://link.springer.com/protocol/10.1007/978-1-4939-3578-9_3

Zhenzhen Yang, Eric K. Wafula, Loren A. Honaas, Huiting Zhang, Malay Das, Monica Fernandez-Aparicio, Kan Huang, Pradeepa C.G. Bandaranayake, Biao Wu, Joshua P. Der, Christopher R. Clarke, Paula E. Ralph, Lena Landherr, Naomi S. Altman, Michael P. Timko, John, I. Yoder, James H. Westwood, and Claude W. dePamphilis. (2014) Comparative transcriptome analyses reveal core parasitism genes and suggest gene duplication and repurposing as sources of structural novelty. Molecular Biology and Evolution. DOI:10.1093/molbev/msu343 oxfordjournals

Philip J Jensen, Gennaro Fazio, Naomi Altman, Craig Praul and Timothy McNellis.(2014) Mapping in an apple (Malus x
domestica) F1 segregating population based on physical clustering of differentially expressed genes. BMC Genomics 15, 261 http://www.biomedcentral.com/1471-2164/15/261

Amborella Genome Project(2013) “The Amborella Genome and the Evolution of Flowering Plants” Science.
342, DOI:10.1126/science.1241089 science

Smyth, G.K. and Altman, N.S. (2013) Separate-Channel Analysis of Two-Channel Microarrays: recovering inter-spot information. BMC Bioinformatics 14, 165. doi:10.1186/1471-2105-14-165 BMC

Zahn, LM, Ma,X, Altman, NS, Zhang, Q, Wall, PK, Tian, D., Gibas, CJ, Gharaibeh,R, Leebens-Mack, JH, dePamphilis, CW and Ma, H. (2010) Comparative transcriptomics among floral organs of the basal eudicot Eschscholzia californica as reference for floral evolutionary developmental studies. Genome Biology, 11:R101. http://genomebiology.com/2010/11/10/R101

Altman, N.S., Wang, Q., Karwa, V. and Slavkovic, A. (2010) Resolving Isoform Expression using Digital Gene Expression Data. Journal of the Indian Society of Agricultural Statistics, special issue on Statistical Genomics, 4, 19-31. pdf

Altman, N.S. (2009) Batches and Blocks, Sample Pools and Subsamples in the Design and Analysis of Gene Expression Studies. in Batch Effects and Noise in Microarray Experiments: Sources and Solutions. A. Scherer (editor). John Wiley & Sons, Chichester. https://onlinelibrary.wiley.com/doi/10.1002/9780470685983.ch4

Han, X., X. Wu, W.-Y. Chung, T., Li, A. Nekrutenko, N. Altman, G. Chen, and H. Ma (2009) Transcriptome of embryonic and neonatal mouse cortex by high-throughput RNA sequencing. Proceedings
of the National Academy of Sciences, 106 (31), pp. 12741-6. PNAS

Wall, P.K., J. H. Leebens-Mack, A. Barakat, A. Chanderbali, L. Landherr, N. Altman, J.E. Carlson, H. Ma, W. Miller, S. Schuster, D.E. Soltis, P.S. Soltis, and C.W. dePamphilis. (2008) Comparison of next generation sequencing technologies for de novo transcriptome characterization. BMC Genomics. BMC Genomics

Han, B., Altman, N.S., Mong, J.A., Klein, L.C., Pfaff, D.W. and Vandenbergh, D. (2008) Comparing Quantitative Trait Loci and Gene Expression Data Associated with a Complex Trait, Advances in Bioinformatics. Hindawi Press

P. Kerr Wall, Jim Leebens-Mack, Kai Müller, Dawn Field, Naomi S. Altman, Claude W. dePamphilis. (2007) PlantTribes: A gene and gene family resource for comparative genomics in plants. Nucleic Acid Research, 36, 970-976. NAR

Soltis D.E., H. Ma, M.W. Frohlich, P.S. Soltis, V.A. Albert, D.G. Oppenheimer, N.S. Altman, C.W. dePamphilis and J.H. Leebens-Mack. (2007) The floral genome: an evolutionary history of gene duplication and shifting patterns of gene expression. Trends in Plant Science, 12(8):358-367. PSU

Altman, N.S., Hua, J. (2006) Extending the loop design for 2-channel microarray experiments Genetical Research, Vol 88, No. 3, p. 153-163.Cambridge

Altman, N.S. (2005) Replication, variation and normalization in microarray experiments. Applied Bioinformatics, 4, 33-44.Springer

 

Last updated: 22 June, 2023