Developing a Comprehensive Database Management System for Organization and Evaluation of Mammography Datasets
We aimed to design and develop a comprehensive mammography database system (CMDB) to collect clinical datasets for outcome assessment and development of decision support tools. A Health Insurance Portability and Accountability Act (HIPAA) compliant CMDB was created to store multi-relational datasets of demographic risk factors and mammogram results using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. The CMDB collected both biopsy pathology outcomes, in a breast pathology lexicon compiled by extending BI-RADS, and our institutional breast cancer registry. The audit results derived from the CMDB were in acc...
Source: Cancer Informatics - October 16, 2014 Category: Cancer & Oncology Authors: Yirong WuDaniel L. RubinRyan W. WoodsMai ElezabyElizabeth S. Burnside Source Type: research
StickWRLD as an Interactive Visual Pre-Filter for Canceromics-Centric Expression Quantitative Trait Locus Data
In this study, we applied StickWRLD to a semi-synthetic dataset constructed from two published human datasets. In addition to detecting high-probability correlations in this dataset, we were able to quickly identify gene–SNP correlations that would have gone undetected using more traditional approaches due to issues of low penetrance. (Source: Cancer Informatics)
Source: Cancer Informatics - October 16, 2014 Category: Cancer & Oncology Authors: Robert Wolfgang RumpfSamuel L. WolockWilliam C. Ray Source Type: research
Network-Based Identification of Biomarkers Coexpressed with Multiple Pathways
Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implicatio...
Source: Cancer Informatics - October 16, 2014 Category: Cancer & Oncology Authors: Nancy Lan GuoYing-Wooi Wan Source Type: research
A Comprehensive Comparison of Normalization Methods for Loading Control and Variance Stabilization of Reverse-Phase Protein Array Data
In this study, we compare eight different normalization methods for LC and variance stabilization. The invariant marker set concept was first applied to the normalization of high-throughput gene expression data. A set of “invariant” markers are selected to create a virtual reference sample. Then all the samples are normalized to the virtual reference. We propose a variant of this method in the context of RPPA data normalization and compare it with seven other normalization methods previously reported in the literature. The invariant marker set method performs well with respect to LC, variance stabilization and associat...
Source: Cancer Informatics - October 16, 2014 Category: Cancer & Oncology Authors: Wenbin LiuZhenlin JuYiling LuGordon B. MillsRehan Akbani Source Type: research
Automated Recommendation for Cervical Cancer Screening and Surveillance
Because of the complexity of cervical cancer prevention guidelines, clinicians often fail to follow best-practice recommendations. Moreover, existing clinical decision support (CDS) systems generally recommend a cervical cytology every three years for all female patients, which is inappropriate for patients with abnormal findings that require surveillance at shorter intervals. To address this problem, we developed a decision tree-based CDS system that integrates national guidelines to provide comprehensive guidance to clinicians. Validation was performed in several iterations by comparing recommendations generated by the s...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Kavishwar B. WagholikarKathy L. MacLaughlinPetra M. CaseyThomas M. KastnerMichael R. HenryRonald A. HankeySteve G. PetersRobert A. GreenesChristopher G. ChuteHongfang LiuRajeev Chaudhry Source Type: research
Quality Control for RNA-Seq (QuaCRS): An Integrated Quality Control Pipeline
QuaCRS (Quality Control for RNA-Seq) is an integrated, simplified quality control (QC) system for RNA-seq data that allows easy execution of several open-source QC tools, aggregation of their output, and the ability to quickly identify quality issues by performing meta-analyses on QC metrics across large numbers of samples in different studies. It comprises two main sections. First is the QC Pack wrapper, which executes three QC tools: FastQC, RNA-SeQC, and selected functions from RSeQC. Combining these three tools into one wrapper provides increased ease of use and provides a much more complete view of sample data quality...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Karl W. KrollNima E. MokaramAlexander R. PelletierDavid E. FrankhouserMaximillian S. WestphalPaige A. StumpCameron L. StumpRalf BundschuhJames S. BlachlyPearlly Yan Source Type: research
Network-based Prediction of Cancer under Genetic Storm
Classification of cancer patients using traditional methods is a challenging task in the medical practice. Owing to rapid advances in microarray technologies, currently expression levels of thousands of genes from individual cancer patients can be measured. The classification of cancer patients by supervised statistical learning algorithms using the gene expression datasets provides an alternative to the traditional methods. Here we present a new network-based supervised classification technique, namely the NBC method. We compare NBC to five traditional classification techniques (support vector machines (SVM), k-nearest ne...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Ahmet AyDihong GongTamer Kahveci Source Type: research
Master Regulators, Regulatory Networks, and Pathways of Glioblastoma Subtypes
Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype-specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-spec...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Serdar BozdagAiguo LiMehmet Baysanand Howard A. Fine Source Type: research
Profiling the microRNA Expression in Human iPS and iPS-derived Retinal Pigment Epithelium
The purpose of this study is to characterize the microRNA (miRNA) expression profiles of induced pluripotent stem (iPS) cells and retinal pigment epithelium (RPE) derived from induced pluripotent stem cells (iPS-RPE). MiRNAs have been demonstrated to play critical roles in both maintaining pluripotency and facilitating differentiation. Gene expression networks accountable for maintenance and induction of pluripotency are linked and share components with those networks implicated in oncogenesis. Therefore, we hypothesize that miRNA expression profiling will distinguish iPS cells from their iPS-RPE progeny. To identify and a...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Heuy-Ching WangWhitney A. GreeneRamesh R. KainiJane Shen-GuntherHung-I H ChenHong CaiYufeng Wang Source Type: research
CORM: An R Package Implementing the Clustering of Regression Models Method for Gene Clustering
We report a new R package implementing the clustering of regression models (CORM) method for clustering genes using gene expression data and provide data examples illustrating each clustering function in the package. The CORM package is freely available at CRAN from http://cran.r-project.org. (Source: Cancer Informatics)
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Jiejun ShiLi-Xuan Qin Source Type: research
Unsupervised Outlier Profile Analysis
In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some s...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Debashis GhoshSong Li Source Type: research
TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile
The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in gen...
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Yen-Tsung HuangThomas HsuDavid C. Christiani Source Type: research
Mapping Splicing Quantitative Trait Loci in RNA-Seq
Conclusions: We have evaluated three statistical methods for the analysis of sQTLs in RNA-Seq. Results from our study will be instructive for researchers in selecting the appropriate statistical methods for sQTL analysis. (Source: Cancer Informatics)
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Cheng JiaYu HuYichuan LiuMingyao Li Source Type: research
Toolbox for Mobile-Element Insertion Detection on Cancer Genomes
In this study, we report a new feature that enables TANGRAM to be used on alignments generated by any mainstream short-read mapper, making it accessible for many genomic users. To demonstrate its utility for cancer genome analysis, we have applied TANGRAM to the TCGA (The Cancer Genome Atlas) mutation calling benchmark 4 dataset. TANGRAM is fast, accurate, easy to use, and open source on https://github.com/jiantao/Tangram. (Source: Cancer Informatics)
Source: Cancer Informatics - October 15, 2014 Category: Cancer & Oncology Authors: Wan-Ping LeeJiantao WuGabor T. Marth Source Type: research
Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis
This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driv...
Source: Cancer Informatics - October 14, 2014 Category: Cancer & Oncology Authors: Seyed M. IranmaneshNancy L. Guo Source Type: research
