Matthew N. McCall

Assistant Professor of Biostatistics and Biomedical Genetics

University of Rochester

Biography

Matthew McCall is an Associate Professor at the University of Rochester Medical Center. He is currently developing methods to estimate gene regulatory networks from gene perturbation experiments, to address within-subject heterogeneity in genomic tumor biomarkers, to preprocess and analyze genomic data, and to examine the effect of cellular composition on tissue-level gene expression.

My complete curriculum vitae in pdf format is available here.

Interests

Statistical Genomics
Systems Biology
Bioinformatics

Education

PhD in Biostatistics, 2010

Johns Hopkins University
MHS in Bioinformatics, 2010

Johns Hopkins University
BS in Statistics, 2004

University of Michigan

Lab Members

Qingyan (Lilly) Xie

Postdoctoral Associate

Isar Nassiri

Postdoctoral Associate

Yun Zhang

Statistics PhD Student

Valeriia Sherina

Statistics PhD Student

David Burton

Statistics PhD Student

Zachary Brehm

Statistics PhD Student

Jeremiah Jones

Statistics PhD Student

Jonavelle Cuerdo

Data Science Undergraduate

Lauren Kemperman

Data Science Undergraduate

Benjamin Hsu

Statistics Undergraduate

Kailey Ferger

Comp Bio Undergraduate

Oleg Demus

Comp Bio Undergraduate

Winslow Powers

BME Undergraduate

Qidi Yang

Biochemistry Undergraduate

Jeffrey Hrebenach

Data Science Undergraduate

Alida Mooney

Mathematics Undergraduate

Allison Maier

Biology Undergraduate

Lindsey Barden

Biostatistics Undergraduate

Scott Onestak

Data Science Undergraduate

Fatimar Umar

High School Student

Raymond Feng

High School Student

Selected Publications

Nassiri I, McCall MN (2018). Systematic exploration of cell morphological phenotypes associated with a transcriptomic query. Nucleic Acids Research.

Code Paper

McCall MN, Kim MS, Adil M, Patil AH, Lu Y, Mitchell CJ, Leal-Rojas P, Xu J, Kumar M, Dawson VL, Dawson TM, Baras AS, Rosenberg AZ, Arking DE, Burns KH, Pandey A, Halushka MK (2017). Toward the human cellular microRNAome. Genome Research.

Preprint Dataset Paper Research@URMC

McCall MN, Illei PB, Halushka MK (2016). Complex Sources of Variation in Tissue Expression Data: Analysis of the GTEx Lung Transcriptome. The American Journal of Human Genetics.

Paper

Xie QY, Almudevar A, Whitney-Miller CL, Barry CT, McCall MN (2016). A microRNA biomarker of hepatocellular carcinoma recurrence following liver transplantation accounting for within-patient heterogeneity. BMC Medical Genomics.

Paper

McCall MN, McMurray H, Land H, Almudevar A (2014). On Non-Detects in qPCR Data. Bioinformatics.

Code Paper GenomeWeb

McCall MN, Uppal K, Jaffee HA, Zilliox MJ, Irizarry RA (2011). The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes. Nucleic Acids Research.

Code Paper Website

McCall MN, Bolstad BM, Irizarry RA (2010). Frozen Robust Multi-Array Analysis (fRMA). Biostatistics.

Code Paper

Recent Publications

More Publications

Spinelli P, Latchney SE, Reed JM, Fields A, Baier BS, Lu X, McCall MN, Murphy SP, Mak W, Susiarjo M (2018). Identification of the novel Ido1 imprinted locus and its potential epigenetic role in pregnancy loss. Human Molecular Genetics.

Paper

Hill MA, Alexander WB, Guo B, Kato Y, Patra KC, O’Dell MR, McCall MN, Whitney-Miller CL, Bardeesy N, Hezel AF (2018). Kras and Tp53 mutations cause cholangiocyte- and hepatocyte-derived cholangiocarcinoma. Cancer Research.

Paper

Rosenberg AZ, Wright C, Fox-Talbot K, Rajpurohit A, Williams C, Porter C, Kovbasnjuk O, McCall MN, Shin JH, Halushka MK (2018). xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells. Scientific Reports.

Paper

Halushka MK, Fromm B, Peterson KJ, McCall MN (2018). Big Strides in Cellular MicroRNA Expression. Trends in Genetics.

Paper

Sherina V, McMurray HR, Powers W, Land H, Love TMT, McCall MN (2017). Statistical Approches to Decreasing the Discrepancy of Non-detects in qPCR Data. BioRxiv.

Preprint Code

Software

frma

Preprocessing and analysis for single microarrays and microarray batches.

frmaTools

Tools for advanced use of the frma package.

miRcomp

Based on a large miRNA dilution study, this package provides tools to read in the raw amplification data and use these data to assess the performance of methods that estimate expression from the amplification curves.

miRcompData

Raw amplification data from a large microRNA mixture / dilution study. These data are used by the miRcomp package to assess the performance of methods that estimate expression from the amplification curves.

microRNAome

This package provides a SummarizedExperiment object of read counts for microRNAs across tissues, cell-types, and cancer cell-lines.

nondetects

Methods to model and impute non-detects in the results of qPCR experiments.

spkTools

The package contains functions that can be used to compare expression measures on different array platforms.

ternarynet

A computational Bayesian approach to ternary gene regulatory network estimation from gene perturbation experiments.

News

Presentation at Rocky 2018

Valeriia Sherina is presenting at Rocky 2018. Title: Fully Bayesian model for non-random missing data in qPCR. Abstract: We propose a new statistical approach to obtain differential gene expression of non-detects in quantitative real-time PCR (qPCR) experiments through Bayesian hierarchical modeling. We propose to treat non-detects as non-random missing data, model the missing data mechanism, and use this model to impute Ct values or obtain direct estimates of relevant model parameters.

2018-11-16 departures

Valeriia Sherina starts job at GSK

Congratulations to Valeriia Sherina on starting a new job at GlaxoSmithKline! She’ll be back in early 2019 to defend her thesis.

2018-09-10 arrivals

Kailey Ferger joins the lab

Kailey Ferger, a senior Computational Biology major, has joined the lab where she will be working on analysis of microRNA expression data.

2018-08-16 arrivals

Oleg Demus joins the lab

Oleg Demus, a senior Computational Biology major, has joined the lab where he will be working to combine multiple publicly available RNA-seq data sets to address questions of tissue composition in atherosclerosis.