SurvJamda: an R package to predict patients' survival and risk assessment using joint analysis of microarray gene expression data
نویسنده
چکیده
UNLABELLED SurvJamda (Survival prediction by joint analysis of microarray data) is an R package that utilizes joint analysis of microarray gene expression data to predict patients' survival and risk assessment. Joint analysis can be performed by merging datasets or meta-analysis to increase the sample size and to improve survival prognosis. The prognosis performance derived from the combined datasets can be assessed to determine which feature selection approach, joint analysis method and bias estimation provide the most robust prognosis for a given set of datasets. AVAILABILITY The survJamda package is available at the Comprehensive R Archive Network, http://cran.r-project.org. CONTACT [email protected].
منابع مشابه
Feature Selection and Classification of Microarray Gene Expression Data of Ovarian Carcinoma Patients using Weighted Voting Support Vector Machine
We can reach by DNA microarray gene expression to such wealth of information with thousands of variables (genes). Analysis of this information can show genetic reasons of disease and tumor differences. In this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...
متن کاملشناسایی ژنهای مرتبط با بقا در سرطان کلیه با استفاده از روش مؤلفههای اصلی لاسو
Background: Identification of correlated genes with survival by gene expression data is an important application of microarray data. The purpose of this study is to identify correlated genes with survival of conventional renal cell carcinoma (cRCC) patients based on gene expression profiles. Methods: This study is a survival analysis with high dimensional covariates and containing 14814 gene...
متن کاملAnalysis of Gene Expression, Signaling Pathways, and Interaction Networks of Some Effective Genes in Patients with Asthma in Microarray Studies Using R Software
Background and purpose: Asthma is a chronic inflammatory disorder of the airways caused by a combination of complex environmental and genetic interactions. There is an incomplete understanding of this mechanism which affect both severity of the disease and how it responds to treatment. Different gene expressions are reported in patients with asthma and healthy controls. Materials and methods:...
متن کاملModification of the Fast Global K-means Using a Fuzzy Relation with Application in Microarray Data Analysis
Recognizing genes with distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic level. In this paper, fast Global k-means (fast GKM) is developed for clustering the gene expression datasets. Fast GKM is a significant improvement of the k-means clustering method. It is an incremental clustering method which starts with one cluster. Iteratively ...
متن کاملClassification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random Forest
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and smal...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Bioinformatics
دوره 27 8 شماره
صفحات -
تاریخ انتشار 2011