Journal of Probability and Statistics

Advanced Designs and Statistical Methods for Genetic and Genomic Studies of Complex Diseases


Publishing date
17 Aug 2012
Status
Published
Submission deadline
30 Mar 2012

Lead Editor

1Division of Biostatistics, New York University School of Medicine, New York, NY, USA

2Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA

3Biometrics Research, Merck Research Laboratories, Whitehouse Station, NJ, USA


Advanced Designs and Statistical Methods for Genetic and Genomic Studies of Complex Diseases

Description

The completion of the Human Genome Project and the International HapMap Project, coupled with rapid advancements of high-throughput biotechnology including next-generation sequencing (NGS), has facilitated the discovery of genetic and genomic variants linked to many human diseases. Massive amount of data from genetic and genomic studies provides a great opportunity for researchers to investigate and propose novel statistical methods and algorithms that can effectively identify disease-associated or causal genetic/genomic markers while avoiding an abundance of false positive results.

Despite many recent advances in statistical designs and methods for the analysis of genetic and genomic studies of complex diseases, numerous challenges still remain. For example, complex diseases including many cancers are heterogeneous in both disease phenotypes and disease etiology. The specification of disease phenotype and measurement of risk factors or environmental exposures are often subject to missing data, measurement errors, or oversimplification. Disease susceptibility is often affected by heterogeneous genetic/genomic factors including rare variants and further altered by various environmental exposures. Therefore, novel study designs and analysis methods are essential for proper adjustment of latent heterogeneity and for robust inferences using data with misspecification of disease phenotypes, incompletely measured exposures, or other complexities.

We invite investigators to submit original research articles as well as review articles that propose innovative study designs, novel probabilistic and statistical models, and analysis methods/algorithms for genetic and genomic studies of complex diseases. Potential topics include, but are not limited to:

  • Novel study designs that can effectively control false negative and false positive rates
  • Innovative models and methods to adjust for latent population heterogeneity
  • Methods for analyzing genome-wide data and developing effective risk assessment models
  • Design and analysis of high-throughput screening studies
  • Methods and algorithms for robust analysis of data with measurement error or incompleteness
  • Advanced methods for combining evidence from different types of data or studies

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/jps/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2012
  • - Article ID 805426
  • - Editorial

Advanced Designs and Statistical Methods for Genetic and Genomic Studies of Complex Diseases

Yongzhao Shao | Wei Pan | Xiaohua Douglas Zhang
  • Special Issue
  • - Volume 2012
  • - Article ID 256574
  • - Research Article

The Transmission Disequilibrium/Heterogeneity Test with Parental-Genotype Reconstruction for Refined Genetic Mapping of Complex Diseases

Jing Han | Yongzhao Shao
  • Special Issue
  • - Volume 2012
  • - Article ID 524724
  • - Research Article

Design and Statistical Analysis of Pooled Next Generation Sequencing for Rare Variants

Tao Wang | Chang-Yun Lin | ... | Kenny Ye
  • Special Issue
  • - Volume 2012
  • - Article ID 817948
  • - Research Article

Sample Size Calculation for Controlling False Discovery Proportion

Shulian Shang | Qianhe Zhou | ... | Yongzhao Shao
  • Special Issue
  • - Volume 2012
  • - Article ID 935621
  • - Research Article

Sample Size Growth with an Increasing Number of Comparisons

Chi-Hong Tseng | Yongzhao Shao
  • Special Issue
  • - Volume 2012
  • - Article ID 151259
  • - Research Article

Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors

Iryna Lobach | Ruzong Fan
  • Special Issue
  • - Volume 2012
  • - Article ID 873570
  • - Research Article

Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer

Alexander Pearlman | Christopher Campbell | ... | Harry Ostrer
  • Special Issue
  • - Volume 2012
  • - Article ID 478680
  • - Review Article

High-Dimensional Cox Regression Analysis in Genetic Studies with Censored Survival Outcomes

Jinfeng Xu
  • Special Issue
  • - Volume 2012
  • - Article ID 652569
  • - Review Article

Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies

Qiong Yang | Yuanjia Wang
  • Special Issue
  • - Volume 2012
  • - Article ID 913560
  • - Research Article

Robust Semiparametric Optimal Testing Procedure for Multiple Normal Means

Peng Liu | Chong Wang
Journal of Probability and Statistics
 Journal metrics
Acceptance rate20%
Submission to final decision49 days
Acceptance to publication28 days
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