Works (22)
Updated: September 1st, 2024 05:36
2024 journal article
WEAK SIGNAL INCLUSION UNDER DEPENDENCE AND APPLICATIONS IN GENOME-WIDE ASSOCIATION STUDY
ANNALS OF APPLIED STATISTICS, 18(1), 841–857.
author keywords: Arbitrary covariance dependence; false negative control; underpowered GWAS; high- dimensional data; user-adaptive method
TL;DR:
The challenge of retaining true signals that are not strong enough to be individually separable from a large amount of noise is addressed and false negative control (FNC) screening is presented, a data-driven method to efficiently regulate false negative proportion at a user-specified level.
(via Semantic Scholar)
open access via arxiv.org (repository)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: March 25, 2024
2023 journal article
Estimating the proportion of signal variables under arbitrary covariance dependence
Electronic Journal of Statistics, 17(1), 950–979.
author keywords: Dependence adaptivity; high-dimension data; lower bound estimator; sparse signal
TL;DR:
This paper defines mean absolute correlation (MAC) to measure the overall dependence strength and investigates a family of estimators for their performances in the full range of MAC and proposes a new estimator to better adapt to arbitrary covariance dependence.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, NC State University Libraries, Crossref
Added: November 20, 2023
2023 journal article
Transfer learning with false negative control improves polygenic risk prediction
PLOS Genetics, 19(11), e1010597.
Ed(s): M. Epstein
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, Crossref, NC State University Libraries
Added: March 4, 2024
2020 journal article
Effective SNP ranking improves the performance of eQTL mapping
GENETIC EPIDEMIOLOGY, 44(6), 611–619.
author keywords: HC ranking; hotspot; multivariate response; penalized regression; trans-eQTL
MeSH headings : Computer Simulation; Data Analysis; Gene Expression Regulation; Genome-Wide Association Study; Humans; Models, Genetic; Polymorphism, Single Nucleotide / genetics; Quantitative Trait Loci / genetics
TL;DR:
This paper illustrates how the HC-based SNP ranking can effectively prioritize eQTL signals over noise, greatly reduce the burden of joint modeling, and improve the power for eZTL mapping.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: April 14, 2020
2020 journal article
FastLORS: Joint modelling for expression quantitative trait loci mapping in R
STAT, 9(1).
author keywords: block coordinate descent; eQTL mapping; low-rank approximation; proximal gradient descent; sparse regression
TL;DR:
FastLORS is a software package that implements a new algorithm to solve sparse multivariate regression for expression quantitative trait loci (eQTLs) mapping that reduces the computational cost compared with LORS.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: May 7, 2020
2020 journal article
Model Selection With Mixed Variables on the Lasso Path
SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS, 83(1), 170–184.
author keywords: Jayanta K; Ghosh; Large p small n; Penalized regression; Variable selection; Primary; Secondary
TL;DR:
A new variable selection procedure is developed to control over-selection of the noise variables ranking after the last relevant variable, and, at the same time, retain a high proportion of relevant variables ranking before the first noise variable.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: May 18, 2020
2019 journal article
Variable selection via adaptive false negative control in linear regression
ELECTRONIC JOURNAL OF STATISTICS, 13(2), 5306–5333.
author keywords: debiased Lasso; FNC-Reg; post-selection inference; variable screening
TL;DR:
This paper proposes to directly estimate the false negative proportion (FNP) of a decision rule and select the smallest subset of predictors that has the estimated FNP less than a user-specified control level.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
16. Peace, Justice and Strong Institutions
(OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: January 27, 2020
2018 journal article
Efficient Signal Inclusion With Genomic Applications
Journal of the American Statistical Association, 114(528), 1–23.
author keywords: Dimension reduction; False-negative control; False-positive control; Ultrahigh dimension; Variable screening
TL;DR:
The signal missing rate (SMR) is proposed as a new measure for false-negative control to account for the variability offalse-negative proportion and novel data-adaptive procedures are developed to control SMR without incurring many unnecessary false positives under dependence.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: ORCID, Crossref, NC State University Libraries
Added: February 21, 2020
2018 journal article
High-dimensional inference for personalized treatment decision
ELECTRONIC JOURNAL OF STATISTICS, 12(1), 2074–2089.
author keywords: Large p small n; model misspecification; optimal treatment regime; robust regression
TL;DR:
An asymptotically unbiased estimator based on Lasso solution for the interaction coefficients is proposed and the limiting distribution of the estimator is derived when baseline function of the regression model is unknown and possibly misspecified.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018
2018 journal article
Predictor ranking and false discovery proportion control in high-dimensional regression
JOURNAL OF MULTIVARIATE ANALYSIS, 171, 163–175.
TL;DR:
The procedure can consistently estimate the FDP of variable selection as long as the de-sparsified Lasso estimator is asymptotically normal and compares favorably to existing methods in ranking efficiency and FDP control.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: April 22, 2019
2016 journal article
Detecting weak signals in high dimensions
JOURNAL OF MULTIVARIATE ANALYSIS, 147, 234–246.
author keywords: False negative control; Multiple testing; Variable screening; Variable selection; Trichotomous analysis
TL;DR:
This paper seeks to facilitate the detection of weak signals by introducing a new approach based on false negative instead of false positive control, which shows in theory its efficiency and adaptivity to the unknown features of the data including signal intensity and sparsity.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018
2016 journal article
Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level
PLOS Computational Biology, 12(6), e1004993.
Ed(s): P. Radivojac
Sources: ORCID, Crossref, NC State University Libraries, NC State University Libraries
Added: August 6, 2018
2015 journal article
A Statistical Method for Identifying Trait-Associated Copy Number Variants
Human Heredity, 79(3-4), 147–156.
Sources: Crossref, NC State University Libraries
Added: August 20, 2024
2014 journal article
Censored rank independence screening for high-dimensional survival data
Biometrika, 101(4), 799–814.
author keywords: High-dimensional survival data; Rank independence screening; Sure screening property
TL;DR:
Simulations and an analysis of real data demonstrate that the proposed method performs competitively on survival data sets of moderate size and high-dimensional predictors, even when these are contaminated.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries, Crossref
Added: August 6, 2018
2014 journal article
Parametric modeling of whole-genome sequencing data for CNV identification
BIOSTATISTICS, 15(3), 427–441.
author keywords: Natural exponential family; Sparse segment identification; Variance stabilization
MeSH headings : DNA Copy Number Variations / genetics; Genome, Human / genetics; Humans; Models, Statistical; Sequence Analysis, DNA / methods
TL;DR:
This paper considers parametric modeling of the read depth (RD) data from whole-genome sequencing with the aim of identifying the CNVs, including both Poisson and negative-binomial modeling of such count data, and proposes a unified approach of using a mean-matching variance stabilizing transformation.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018
2013 report
Identification of signal, noise, and indistinguishable subsets in high-dimensional data analysis
(ArXiv Preprint No. 1305.0220).
Sources: NC State University Libraries, NC State University Libraries
Added: August 25, 2024
2012 journal article
Robust Detection and Identification of Sparse Segments in Ultra-High Dimensional Data Analysis.
Journal of the Royal Statistical Society. Series B, Statistical Methodology.
Source: ORCID
Added: August 12, 2024
2012 journal article
Simultaneous discovery of rare and common segment variants
BIOMETRIKA, 100(1), 157–172.
author keywords: DNA copy number variant; Information pooling; Population structural variant
TL;DR:
A proportion adaptive segment selection procedure that automatically adjusts to the unknown proportions of the carriers of the segment variants that is applied to analyze neuroblastoma samples and identifies a large number of copy number variants that are missed by single-sample methods.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018
2011 journal article
Optimal Detection of Heterogeneous and Heteroscedastic Mixtures
Journal of Royal Statistical Society, Series B,
Source: ORCID
Added: August 12, 2024
2011 journal article
Sparse covariance thresholding for high-dimensional variable selection
Statistica Sinica, 21(2), 625.
Sources: Crossref, NC State University Libraries
Added: August 20, 2024
2010 journal article
Optimal Sparse Segment Identification With Application in Copy Number Variation Analysis
Journal of the American Statistical Association, 105(491), 1156–1166,
Source: ORCID
Added: August 12, 2024
2008 journal article
Shrinkage and model selection with correlated variables via weighted fusion
Computational Statistics & Data Analysis, 53(4), 1284–1298.
TL;DR:
The weighted fusion can potentially incorporate information redundancy among correlated variables for estimation and variable selection and allows the selection of more than n variables in a motivated way when the number of predictors p is larger than thenumber of observations n.
(via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: August 28, 2020
Employment
Updated: August 13th, 2024 16:09
2018 - present
North Carolina State University Raleigh, North Carolina, US
Associate Professor
Statistics
2012 - 2018
North Carolina State University Raleigh, NC, US
Assistant Professor
Statistics
Education
Updated: August 13th, 2024 16:09
2009 - 2012
University of Pennsylvania Philadelphia, PA, US
Postdoctoral Fellow
Biostatistics, Epidemiology and Informatics
Purdue University West Lafayette, IN, US
PhD
Statistics
University of Chicago Chicago, IL, US
MS
Statistics
Columbia University New York, NY, US
MA
Mathematics of Finance
Fudan University Shanghai, Shanghai, CN
BA
Management
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