• impute

  • Referenced in 91 articles [sw14376]
  • microarrays. Motivation: Gene expression microarray experiments can generate data sets with multiple missing expression values ... investigate automated methods for estimating missing data. Results: We present a comparative study of several ... estimation of missing values in gene microarray data. We implemented and evaluated three methods ... tools for accurate estimation of missing microarray data under a variety of conditions. Availability...
  • limma

  • Referenced in 48 articles [sw10458]
  • limma: Linear Models for Microarray Data. A survey is given of differential expression analyses using...
  • vsn

  • Referenced in 28 articles [sw06105]
  • Variance stabilization and calibration for microarray data Bioconductor version: Release (2.10) The package implements ... estimator for the stochastic model of microarray data described in the references (see vignette...
  • ARACNE

  • Referenced in 31 articles [sw17200]
  • should enhance our ability to use microarray data to elucidate functional mechanisms that underlie cellular...
  • SparseLOGREG

  • Referenced in 25 articles [sw11449]
  • context of cancer diagnosis using microarray data. Results: The gene selection method suggested in this...
  • penalized

  • Referenced in 24 articles [sw06071]
  • cross-validation results for large data sets which is originally the most computationally demanding situation ... will be applied to several microarray data sets. An R package penalized, which implements...
  • TM4

  • Referenced in 11 articles [sw26846]
  • free, open-source system for microarray data management and analysis. Microarrays have emerged ... often challenged by the large quantities of data produced. Well-designed, user-friendly software ... capture, manage, and analyze effectively data from DNA microarray experiments. The TM4 suite ... tools consist of four major applications, Microarray Data Manager (MADAM), TIGR_Spotfinder, Microarray Data Analysis...
  • uniCox

  • Referenced in 12 articles [sw19131]
  • useful for high-dimensional data, including microarray data...
  • PAGE

  • Referenced in 7 articles [sw23828]
  • enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets ... identify significant biological changes in microarray data sets. GSEA is especially useful when gene expression ... changes in a given microarray data set is minimal or moderate. Results: We developed ... detect significantly changed gene sets from microarray data irrespective of different Affymetrix probe level analysis...
  • GEOquery

  • Referenced in 9 articles [sw17285]
  • BioConductor. Microarray technology has become a standard molecular biology tool. Experimental data have been generated ... analysis and comprehension of genomic data. The tools contained in the BioConductor project represent many ... methods for the analysis of microarray and genomics data. We have developed a software tool ... Facilitating analyses and meta-analyses of microarray data will increase the efficiency with which biologically...
  • marrayClasses

  • Referenced in 7 articles [sw08346]
  • Exploratory Analysis and Normalization of cDNA Microarray Data. This chapter describes a collection of four ... normalization of two-color cDNA microarray fluorescence intensity data. R’s object-oriented class/method mechanism ... tcltk widgets to automate data input and the creation of microarray-specific R objects ... storing these data. Functions for diagnostic plots of microarray spot statistics, such as boxplots, scatterplots...
  • varSelRF

  • Referenced in 8 articles [sw08253]
  • applications in high-dimensional data (e.g., microarray data, and other genomics and proteomics applications...
  • superpc

  • Referenced in 8 articles [sw19130]
  • useful for high-dimnesional data, including microarray data. This function uses a form of cross...
  • edgeR

  • Referenced in 44 articles [sw06936]
  • data. t is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies ... functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies...
  • BicAT

  • Referenced in 13 articles [sw12371]
  • exploration of the gene expression data, e.g. microarrays...
  • FABIA

  • Referenced in 8 articles [sw23382]
  • biclusters from true biclusters. On 100 simulated data sets with known true, artificially implanted biclusters ... competitors. FABIA was tested on microarray data sets which known, biological verfified subclusters and performed...
  • daMA

  • Referenced in 8 articles [sw06093]
  • statistical analysis of factorial microarray data. Statistical details are described in Bretz...
  • HykGene

  • Referenced in 9 articles [sw23981]
  • genes for phenotype classification using microarray gene expression data. MOTIVATION: Recent studies have shown that ... microarray gene expression data are useful for phenotype classification of many diseases. A major problem...
  • marrayInput

  • Referenced in 5 articles [sw08347]
  • Exploratory Analysis and Normalization of cDNA Microarray Data. This chapter describes a collection of four ... normalization of two-color cDNA microarray fluorescence intensity data. R’s object-oriented class/method mechanism ... tcltk widgets to automate data input and the creation of microarray-specific R objects ... storing these data. Functions for diagnostic plots of microarray spot statistics, such as boxplots, scatterplots...
  • marrayNorm

  • Referenced in 5 articles [sw08348]
  • Exploratory Analysis and Normalization of cDNA Microarray Data. This chapter describes a collection of four ... normalization of two-color cDNA microarray fluorescence intensity data. R’s object-oriented class/method mechanism ... tcltk widgets to automate data input and the creation of microarray-specific R objects ... storing these data. Functions for diagnostic plots of microarray spot statistics, such as boxplots, scatterplots...