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

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

(2017). Toward the human cellular microRNAome. Genome Research.

Preprint Dataset Paper Research@URMC

(2016). Complex Sources of Variation in Tissue Expression Data: Analysis of the GTEx Lung Transcriptome. The American Journal of Human Genetics.


(2014). On Non-Detects in qPCR Data. Bioinformatics.

Code Paper GenomeWeb

(2010). Frozen Robust Multi-Array Analysis (fRMA). Biostatistics.

Code Paper

Recent Publications

More Publications

(2018). Kras and Tp53 mutations cause cholangiocyte- and hepatocyte-derived cholangiocarcinoma. Cancer Research.


(2018). xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells. Scientific Reports.


(2018). Big Strides in Cellular MicroRNA Expression. Trends in Genetics.


(2017). Statistical Approches to Decreasing the Discrepancy of Non-detects in qPCR Data. BioRxiv.

Preprint Code



Preprocessing and analysis for single microarrays and microarray batches.


Tools for advanced use of the frma package.


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.


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.


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


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


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


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


Raymond Feng has been accepted to the Simons Summer Research Program at Stony Brook University, which gives academically talented, motivated high school students the opportunity to engage in hands-on research in science, math or engineering at Stony Brook University. Simons Fellows work with distinguished faculty mentors, learn laboratory techniques and tools, become part of active research teams, and experience life at a research university. You can read more about this program here: https://www.


Valeriia Sherina has been awarded the William Jackson Hall Graduate Student Fellowship. This merit-based fellowship recognizes Statistics doctoral students whose academic record reflects the major cornerstones of Jack Hall’s distinguished career. Recipients have distinguished themselves through outstanding performance in coursework and qualifying exams, excellence in their service as a graduate student teaching assistant, and timely completion of a dissertation containing work judged to be of particular significance in both its methodological contribution and potential impact in applications.


Congratulations to Valeriia Sherina who won an ENAR Distinguished Student Paper Award for the 2018 ENAR Spring Meeting in Atlanta, GA. The award recognizes her paper entitled, Statistical Approaches to Decreasing the Discrepancy of Non-detects in qPCR Data. You can read the preprint here:


Dr. Marc Halushka’s R01, Fine Dissection of Atherosclerosis Microenvironment RNA Expression, has been funded! The proposed research represents the first in-depth analysis of expression in human coronary atherosclerotic plaques to uncover cell-specific gene expression differences. The McCall Lab has received a subcontract to analyze transcriptomic data from the cell types present in an atherosclerotic plaque and assess the ability of mRNA- and miRNA-seq to distinguish between cell types. We will estimate the cellular composition of ~800 GTEx coronary artery samples.