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Automatic Clustering of Flow Cytometry Data with Density-Based MergingEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
We describe methodology and software to automatically identify cell populations in flow cytometry data. Our approach advances the paradigm of manually gating sequential two-dimensional projections of the data to a procedure that automatically produces gates based on statistical theory. Our approach is nonparametric and can reproduce nonconvex subpopulations that are known to occur in flow cytometry samples, but which cannot be produced with current parametric model-based approaches. We illustrate the methodology with a sample of mouse spleen and peritoneal cavity cells. (Source: Advances in Bioinformatics)
Source: Advances in Bioinformatics - November 19, 2009 Category: Bioinformatics Source Type: journals

Fluorescence Intensity Normalisation: Correcting for Time Effects in Large-Scale Flow Cytometric AnalysisEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several...
Source: Advances in Bioinformatics - November 17, 2009 Category: Bioinformatics Source Type: journals

Assessing the Quality of Whole Genome Alignments in BacteriaEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Comparing genomes is an essential preliminary step to solve many problems in biology. Matching long similar segments between two genomes is a precondition for their evolutionary, genetic, and genome rearrangement analyses. Though various comparison methods have been developed in recent years, a quantitative assessment of their performance is lacking. Here, we describe two families of assessment measures whose purpose is to evaluate bacteria-oriented comparison tools. The first measure is based on how well the genome segmentation fits the gene annotation of the studied organisms; the second uses the number of segments creat...
Source: Advances in Bioinformatics - November 15, 2009 Category: Bioinformatics Source Type: journals

Merging Mixture Components for Cell Population Identification in Flow CytometryEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated flow cytometry data distributions. Our framework allows the automated selection of the number of distinct cell subpopulations and we are able to identify cases where the algorithm fails, thus making it suitable for applicati...
Source: Advances in Bioinformatics - November 12, 2009 Category: Bioinformatics Source Type: journals

iFlow: A Graphical User Interface for Flow Cytometry Tools in BioconductorEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Flow cytometry (FCM) has become an important analysis technology in health care and medical research, but the large volume of data produced by modern high-throughput experiments has presented significant new challenges for computational analysis tools. The development of an FCM software suite in Bioconductor represents one approach to overcome these challenges. In the spirit of the R programming language (Tree Star Inc., “FlowJo”), these tools are predominantly console-driven, allowing for programmatic access and rapid development of novel algorithms. Using this software requires a solid understanding of progra...
Source: Advances in Bioinformatics - November 12, 2009 Category: Bioinformatics Source Type: journals

Analysis of High-Throughput Flow Cytometry Data Using plateCoreEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Flow cytometry (FCM) software packages from R/Bioconductor, such as flowCore and flowViz, serve as an open platform for development of new analysis tools and methods. We created plateCore, a new package that extends the functionality in these core packages to enable automated negative control-based gating and make the processing and analysis of plate-based data sets from high-throughput FCM screening experiments easier. plateCore was used to analyze data from a BD FACS CAP screening experiment where five Peripheral Blood Mononucleocyte Cell (PBMC) samples were assayed for 189 different human cell surface markers. This same...
Source: Advances in Bioinformatics - October 11, 2009 Category: Bioinformatics Source Type: journals

Bridging the Divide between Manual Gating and Bioinformatics with the Bioconductor Package flowFlowJoEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
We present this package and illustrate some of the ways in which it can be used. (Source: Advances in Bioinformatics)
Source: Advances in Bioinformatics - October 7, 2009 Category: Bioinformatics Source Type: journals

The KM-Algorithm Identifies Regulated Genes in Time Series Expression DataEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
We present a statistical method to rank observed genes in gene expression time series experiments according to their degree of regulation in a biological process. The ranking may be used to focus on specific genes or to select meaningful subsets of genes from which gene regulatory networks can be built. Our approach is based on a state space model that incorporates hidden regulators of gene expression. Kalman (K) smoothing and maximum (M) likelihood estimation techniques are used to derive optimal estimates of the model parameters upon which a proposed regulation criterion is based. The statistical power of the proposed al...
Source: Advances in Bioinformatics - October 7, 2009 Category: Bioinformatics Source Type: journals

FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric DataEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
A new software package called flowFP for the analysis of flow cytometry data is introduced. The package, which is tightly integrated with other Bioconductor software for analysis of flow cytometry, provides tools to transform raw flow cytometry data into a form suitable for direct input into conventional statistical analysis and empirical modeling software tools. The approach of flowFP is to generate a description of the multivariate probability distribution function of flow cytometry data in the form of a “fingerprint.” As such, it is independent of a presumptive functional form for the distribution, in contra...
Source: Advances in Bioinformatics - September 24, 2009 Category: Bioinformatics Source Type: journals

A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour SurvivalsEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expres...
Source: Advances in Bioinformatics - July 30, 2009 Category: Bioinformatics Source Type: journals

Tumor Classification Using High-Order Gene Expression Profiles Based on Multilinear ICAEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Motivation. Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training gene expression profiles (GEP) ensemble, but it cannot distinguish relations between the different factors, or different modes, and it is not available to high-order GEP Data Mining. In order to generalize ICA, we introduce Multilinear-ICA and apply it to tumor classification using high order GEP. Firstly, we introduce the basis conceptions and operations of tensor and recommend Support Vector Machine (SVM) classifier and Multilinear-ICA. Secondly, the higher score genes of original high...
Source: Advances in Bioinformatics - July 20, 2009 Category: Bioinformatics Source Type: journals

The FAST-AIMS Clinical Mass Spectrometry Analysis SystemEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Within clinical proteomics, mass spectrometry analysis of biological samples is emerging as an important high-throughput technology, capable of producing powerful diagnostic and prognostic models and identifying important disease biomarkers. As interest in this area grows, and the number of such proteomics datasets continues to increase, the need has developed for efficient, comprehensive, reproducible methods of mass spectrometry data analysis by both experts and nonexperts. We have designed and implemented a stand-alone software system, FAST-AIMS, which seeks to meet this need through automation of data preprocessing, fe...
Source: Advances in Bioinformatics - July 9, 2009 Category: Bioinformatics Source Type: journals

Automated Quantitative Assessment of Proteins' Biological Function in Protein Knowledge BasesEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Sw...
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

A Tutorial of the Poisson Random Field Model in Population GeneticsEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Population genetics is the study of allele frequency changes driven by various evolutionary forces such as mutation, natural selection, and random genetic drift. Although natural selection is widely recognized as a bona-fide phenomenon, the extent to which it drives evolution continues to remain unclear and controversial. Various qualitative techniques, or so-called “tests of neutrality”, have been introduced to detect signatures of natural selection. A decade and a half ago, Stanley Sawyer and Daniel Hartl provided a mathematical framework, referred to as the Poisson random field (PRF), with which to determine...
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

Genevestigator V3: A Reference Expression Database for the Meta-Analysis of TranscriptomesEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
The Web-based software tool Genevestigator provides powerful tools for biologists to explore gene expression across a wide variety of biological contexts. Its first releases, however, were limited by the scaling ability of the system architecture, multiorganism data storage and analysis capability, and availability of computationally intensive analysis methods. Genevestigator V3 is a novel meta-analysis system resulting from new algorithmic and software development using a client/server architecture, large-scale manual curation and quality control of microarray data for several organisms, and curation of pathway data for m...
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

Comparing Quantitative Trait Loci and Gene Expression DataEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
We develop methods to compare the positions of quantitative trait loci (QTL) with a set of genes selected by other methods, such as microarray experiments, from a sequenced genome. We apply our methods to QTL for addictive behavior in mouse, and a set of genes upregulated in a region of the brain associated with addictive behavior, the nucleus accumbens (NA). The association between the QTL and NA genes is not significantly stronger than expected by chance. However, chromosomes 2 and 16 do show strong associations suggesting that genes on these chromosomes might be associated with addictive behavior. The statistical method...
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

Genomic Promoter Analysis Predicts Functional Transcription Factor BindingEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo. (Source: Advances in Bioinformatics)
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

Metagenome Fragment Classification Using N-Mer Frequency ProfilesEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
A vast amount of microbial sequencing data is being generated through large-scale projects in ecology, agriculture, and human health. Efficient high-throughput methods are needed to analyze the mass amounts of metagenomic data, all DNA present in an environmental sample. A major obstacle in metagenomics is the inability to obtain accuracy using technology that yields short reads. We construct the unique N-mer frequency profiles of 635 microbial genomes publicly available as of February 2008. These profiles are used to train a naive Bayes classifier (NBC) that can be used to identify the genome of any fragment. We show that...
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

NCR-PCOPGene: An Exploratory Tool for Analysis of Sample-Classes Effect on Gene-Expression RelationshipsEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Conclusions. The PCOPGene tools are especially suitable for microarrays with large sample series. This application helps to identify cellular states and the genes involved in it in a flexible way. The application takes advantage of the ability of our system to relate gene expressions; even when these relationships are noncontinuous and cannot be found using linear or nonlinear analytical methods. (Source: Advances in Bioinformatics)
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological InformationEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1) Add synonyms of gene names by searching the Gene Ontology (GO) database. (2) Sea...
Source: Advances in Bioinformatics - June 10, 2009 Category: Bioinformatics Source Type: journals

NCR-PCOPGene: An Exploratory Tool for Analysis of Sample-Classes Effect on Gene-Expression RelationshipsEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Conclusions. The PCOPGene tools are especially suitable for microarrays with large sample series. This application helps to identify cellular states and the genes involved in it in a flexible way. The application takes advantage of the ability of our system to relate gene expressions; even when these relationships are noncontinuous and cannot be found using linear or nonlinear analytical methods. (Source: Advances in Bioinformatics)
Source: Advances in Bioinformatics - December 11, 2008 Category: Bioinformatics Source Type: journals

Metagenome Fragment Classification Using N-Mer Frequency ProfilesEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
A vast amount of microbial sequencing data is being generated through large-scale projects in ecology, agriculture, and human health. Efficient high-throughput methods are needed to analyze the mass amounts of metagenomic data, all DNA present in an environmental sample. A major obstacle in metagenomics is the inability to obtain accuracy using technology that yields short reads. We construct the unique N-mer frequency profiles of 635 microbial genomes publicly available as of February 2008. These profiles are used to train a naive Bayes classifier (NBC) that can be used to identify the genome of any fragment. We show that...
Source: Advances in Bioinformatics - November 17, 2008 Category: Bioinformatics Source Type: journals

Genomic Promoter Analysis Predicts Functional Transcription Factor BindingEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo. (Source: Advances in Bioinformatics)
Source: Advances in Bioinformatics - October 30, 2008 Category: Bioinformatics Source Type: journals

Comparing Quantitative Trait Loci and Gene Expression DataEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
We develop methods to compare the positions of quantitative trait loci (QTL) with a set of genes selected by other methods, such as microarray experiments, from a sequenced genome. We apply our methods to QTL for addictive behavior in mouse, and a set of genes upregulated in a region of the brain associated with addictive behavior, the nucleus accumbens (NA). The association between the QTL and NA genes is not significantly stronger than expected by chance. However, chromosomes 2 and 16 do show strong associations suggesting that genes on these chromosomes might be associated with addictive behavior. The statistical method...
Source: Advances in Bioinformatics - September 16, 2008 Category: Bioinformatics Source Type: journals

Genevestigator V3: A Reference Expression Database for the Meta-Analysis of TranscriptomesEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
The Web-based software tool Genevestigator provides powerful tools for biologists to explore gene expression across a wide variety of biological contexts. Its first releases, however, were limited by the scaling ability of the system architecture, multiorganism data storage and analysis capability, and availability of computationally intensive analysis methods. Genevestigator V3 is a novel meta-analysis system resulting from new algorithmic and software development using a client/server architecture, large-scale manual curation and quality control of microarray data for several organisms, and curation of pathway data for m...
Source: Advances in Bioinformatics - July 8, 2008 Category: Bioinformatics Source Type: journals

A Tutorial of the Poisson Random Field Model in Population GeneticsEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Population genetics is the study of allele frequency changes driven by various evolutionary forces such as mutation, natural selection, and random genetic drift. Although natural selection is widely recognized as a bona-fide phenomenon, the extent to which it drives evolution continues to remain unclear and controversial. Various qualitative techniques, or so-called “tests of neutrality”, have been introduced to detect signatures of natural selection. A decade and a half ago, Stanley Sawyer and Daniel Hartl provided a mathematical framework, referred to as the Poisson random field (PRF), with which to determine...
Source: Advances in Bioinformatics - July 2, 2008 Category: Bioinformatics Source Type: journals

Automated Quantitative Assessment of Proteins' Biological Function in Protein Knowledge BasesEmail this article to a colleague. Save this article to My Clippings. Discuss or comment on this article.
Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Sw...
Source: Advances in Bioinformatics - June 30, 2008 Category: Bioinformatics Source Type: journals