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At least 1,783 records · Page 99Linked to original sources
PubMed1988

Statistical analysis of DNA sequences.

Developments in the statistical analysis of DNA sequence data since 1984 are reviewed. Mathematical methods employing dynamic programming or incorporating Markov chain theory have been developed to search sequences for regions of similarity and to align sequences. When the biological forces of mutation and genetic drift are included in models, distances between aligned sequences allow the construction of evolutionary trees. Theory based on models may lead to estimates of variation of parameter estimates and so give a means of assessing the statistical significance of observed patterns and relationships. The complexity of DNA sequences, however, suggests that most statistical inferences will rest on random permutations of sequences.

Base Sequence↗
PubMed2004

A molecular genetic and statistical approach for the diagnosis of dual-site cancers.

BACKGROUND: Concurrent tumors can be synchronous, independently derived, non-metastatic tumors or metastatic tumors. The prognosis and clinical management of patients with these different concurrent tumor types are different. METHODS: DNA from normal and tumor tissues of 62 patients with synchronous endometrial and ovarian, bilateral ovarian, or endometrial and bilateral ovarian tumors was analyzed for loss of heterozygosity and microsatellite instability using eight polymorphic microsatellite markers at loci frequently deleted in ovarian and/or endometrial cancers. A statistical algorithm was designed to assess the clonal relationship between the tumors. RESULTS: The original histopathology reports classified 26 (42%) case patients with single primary tumors and related metastatic lesions and 21 (34%) with independent primary tumors; 15 (24%) were unclassified. Genetic data identified 35 (56%) case patients with single primary tumors and related metastatic lesions, 18 (29%) with independent primary tumors, and nine (15%) that could not be typed. Excluding case patients with histopathology reports for which a clonal relationship was uncertain or was not reported, there was 53% concordance between genetic and histopathology diagnoses. Increasing the stringency of the statistical analysis increased the number of uncertain diagnoses but did not affect the proportion of discordant genetic and histologic diagnoses. CONCLUSIONS: We have developed a rapid and robust combined genetic and statistical method to establish whether multiple tumors from the same patient represent distinct primary tumors or whether they are clonally related and therefore metastatic. For the majority of case patients, histopathology reports and genetic analyses were in agreement and diagnostic confidence was improved. Importantly, in approximately one-fourth of all case patients, genetic and histopathologic analyses suggested alternative diagnoses. The results suggest that genetic analysis has implications for clinical management and can be performed rapidly as a diagnostic test with paraffin-embedded tissues.

Biomarkers, Tumor↗
PubMed2007

Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting.

BACKGROUND: Both the validity and the reproducibility of microarray-based clinical research have been challenged. There is a need for critical review of the statistical analysis and reporting in published microarray studies that focus on cancer-related clinical outcomes. METHODS: Studies published through 2004 in which microarray-based gene expression profiles were analyzed for their relation to a clinical cancer outcome were identified through a Medline search followed by hand screening of abstracts and full text articles. Studies that were eligible for our analysis addressed one or more outcomes that were either an event occurring during follow-up, such as death or relapse, or a therapeutic response. We recorded descriptive characteristics for all the selected studies. A critical review of outcome-related statistical analyses was undertaken for the articles published in 2004. RESULTS: Ninety studies were identified, and their descriptive characteristics are presented. Sixty-eight (76%) were published in journals of impact factor greater than 6. A detailed account of the 42 studies (47%) published in 2004 is reported. Twenty-one (50%) of them contained at least one of the following three basic flaws: 1) in outcome-related gene finding, an unstated, unclear, or inadequate control for multiple testing; 2) in class discovery, a spurious claim of correlation between clusters and clinical outcome, made after clustering samples using a selection of outcome-related differentially expressed genes; or 3) in supervised prediction, a biased estimation of the prediction accuracy through an incorrect cross-validation procedure. CONCLUSIONS: The most common and serious mistakes and misunderstandings recorded in published studies are described and illustrated. Based on this analysis, a proposal of guidelines for statistical analysis and reporting for clinical microarray studies, presented as a checklist of "Do's and Don'ts," is provided.

Bias↗
PubMed1991

Statistical issues arising from mouse micronucleus assay experiments of Ashby and co-workers.

Data from a series of mouse micronucleus assays have been reanalysed to illustrate various statistical issues raised by Ashby and co-workers during the development of the assay. Most of the statistical points discussed in these earlier papers can be explained by the stochastic nature of the data. Reanalysis shows that the type of data collected in mammalian micronucleus assays is amenable to analysis by standard biometric methods. It is concluded that statistical analysis has an important role in the exploration and interpretation of data from the micronucleus assay.

Analysis of Variance↗
PubMed2002

Searching for RNA genes using base-composition statistics.

The hypothesis that genomic regions rich in non-protein-coding RNAs (ncRNAs) can be identified using local variations in single-base and dinucleotide statistics has been investigated. (G+C)%, (G-C)% difference, (A-T)% difference and dinucleotide-frequency statistics were compared among seven classes of ncRNAs and three genomes. Significant variations were observed in (G+C)% and, in Methanococcus jannaschii, in the frequency of the dinucleotide 'CG'. Screening programs based on these two base-composition statistics were developed. With (G+C)% screening alone, a 1% fraction of the M.jannaschii genome containing all 44 known transfer RNAs, ribosomal RNAs and signal recognition particle RNAs could be identified. When (G+C)% combined with CG dinucleotide-frequency screening was used, 43 of the 44 known M.jannaschii structural ncRNAs were again identified, while the number of presumably false hits overlapping a known or putative protein-coding gene was reduced from 15 to 6. In addition, 19 candidate ncRNAs were identified including one with significant homology to several known archaeal RNaseP RNAs.

Animals↗
PubMed2002

Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences.

The human genome encodes the transcriptional control of its genes in clusters of cis-elements that constitute enhancers, silencers and promoter signals. The sequence motifs of individual cis- elements are usually too short and degenerate for confident detection. In most cases, the requirements for organization of cis-elements within these clusters are poorly understood. Therefore, we have developed a general method to detect local concentrations of cis-element motifs, using predetermined matrix representations of the cis-elements, and calculate the statistical significance of these motif clusters. The statistical significance calculation is highly accurate not only for idealized, pseudorandom DNA, but also for real human DNA. We use our method 'cluster of motifs E-value tool' (COMET) to make novel predictions concerning the regulation of genes by transcription factors associated with muscle. COMET performs comparably with two alternative state-of-the-art techniques, which are more complex and lack E-value calculations. Our statistical method enables us to clarify the major bottleneck in the hard problem of detecting cis-regulatory regions, which is that many known enhancers do not contain very significant clusters of the motif types that we search for. Thus, discovery of additional signals that belong to these regulatory regions will be the key to future progress.

Algorithms↗
PubMed2004

GFINDer: Genome Function INtegrated Discoverer through dynamic annotation, statistical analysis, and mining.

Statistical and clustering analyses of gene expression results from high-density microarray experiments produce lists of hundreds of genes regulated differentially, or with particular expression profiles, in the conditions under study. Independent of the microarray platforms and analysis methods used, these lists must be biologically interpreted to gain a better knowledge of the patho-physiological phenomena involved. To this end, numerous biological annotations are available within heterogeneous and widely distributed databases. Although several tools have been developed for annotating lists of genes, most of them do not give methods for evaluating the relevance of the annotations provided, or for estimating the functional bias introduced by the gene set on the array used to identify the gene list considered. We developed Genome Functional INtegrated Discoverer (GFINDer), a web server able to automatically provide large-scale lists of user-classified genes with functional profiles biologically characterizing the different gene classes in the list. GFINDer automatically retrieves annotations of several functional categories from different sources, identifies the categories enriched in each class of a user-classified gene list and calculates statistical significance values for each category. Moreover, GFINDer enables the functional classification of genes according to mined functional categories and the statistical analysis is of the classifications obtained, aiding better interpretation of microarray experiment results. GFINDer is available online at http://www.medinfopoli.polimi.it/GFINDer/.

Computational Biology↗
PubMed2004

Empirical evaluation of data transformations and ranking statistics for microarray analysis.

There are many options in handling microarray data that can affect study conclusions, sometimes drastically. Working with a two-color platform, this study uses ten spike-in microarray experiments to evaluate the relative effectiveness of some of these options for the experimental goal of detecting differential expression. We consider two data transformations, background subtraction and intensity normalization, as well as six different statistics for detecting differentially expressed genes. Findings support the use of an intensity-based normalization procedure and also indicate that local background subtraction can be detrimental for effectively detecting differential expression. We also verify that robust statistics outperform t-statistics in identifying differentially expressed genes when there are few replicates. Finally, we find that choice of image analysis software can also substantially influence experimental conclusions.

Animals↗
PubMed2005

MIDAW: a web tool for statistical analysis of microarray data.

MIDAW (microarray data analysis web tool) is a web interface integrating a series of statistical algorithms that can be used for processing and interpretation of microarray data. MIDAW consists of two main sections: data normalization and data analysis. In the normalization phase the simultaneous processing of several experiments with background correction, global and local mean and variance normalization are carried out. The data analysis section allows graphical display of expression data for descriptive purposes, estimation of missing values, reduction of data dimension, discriminant analysis and identification of marker genes. The statistical results are organized in dynamic web pages and tables, where the transcript/gene probes contained in a specific microarray platform can be linked (according to user choice) to external databases (GenBank, Entrez Gene, UniGene). Tutorial files help the user throughout the statistical analysis to ensure that the forms are filled out correctly. MIDAW has been developed using Perl and PHP and it uses R/Bioconductor languages and routines. MIDAW is GPL licensed and freely accessible at http://muscle.cribi.unipd.it/midaw/. Perl and PHP source codes are available from the authors upon request.

Algorithms↗
PubMed2006

Retrieval accuracy, statistical significance and compositional similarity in protein sequence database searches.

Protein sequence database search programs may be evaluated both for their retrieval accuracy--the ability to separate meaningful from chance similarities--and for the accuracy of their statistical assessments of reported alignments. However, methods for improving statistical accuracy can degrade retrieval accuracy by discarding compositional evidence of sequence relatedness. This evidence may be preserved by combining essentially independent measures of alignment and compositional similarity into a unified measure of sequence similarity. A version of the BLAST protein database search program, modified to employ this new measure, outperforms the baseline program in both retrieval and statistical accuracy on ASTRAL, a SCOP-based test set.

Data Interpretation, Statistical↗
PubMed1979

A rank statistic for assessing the amount of variation explained by risk factors in epidemiologic studies.

A statistic, Q, based on the ranks of the estimated probabilities of disease is proposed for assessing the effectiveness of regression models used with dichotomous dependent variables in epidemiologic studies of risk factors for chronic diseases. The pitfalls of R2 are discussed, and the proposed statistic is compared with R2 utilizing 8.6-year incidence data from the national cooperative Pooling Project and 15-year mortality data from the Chicago Peoples Gas Company Study. Based on the risk factors, systolic blood pressure, serum cholesterol, and smoking status for middle-aged males, the proposed statistic, Q, attains from 27-44% of its maximum value for the endpoint, the first major coronary event, and from 35-46% of the maximum for death from the cardiovascular diseases.

Adult↗
PubMed1981

A Mantel-Haenszel statistic for testing the association between a polychotomous exposure and a rare outcome.

The Mantel-Haenszel statistic has been designed to test the association between two dichotomous variables using information from several 2 x 2 tables. This statistic is extended here for incidence data on a rare outcome arising at two or more levels of an exposure variable. When there are only two levels of exposure the statistic is reduced to the one suggested earlier by Miettinen. The relationship between degree of urbanization and female laryngeal cancer is studied as an example.

Epidemiologic Methods↗
PubMed1991

Comment on the statistical evaluation of data.

This paper represents a plea for a more professional approach to the statistical evaluation of data contained in biological research papers. On the one hand more attention needs to be given to ensuring that statistically rigorous methods are employed; the use of sophisticated methods is now a possibility due to the wide availability of statistical computer packages. Examples are presented of some interesting applications of the multivariate techniques Cluster Analysis and Principal Component Analysis, the data being drawn from early research work into in-vitro fertilization.

Statistics as Topic↗
PubMed2000

A power analysis of microsatellite-based statistics for inferring past population growth.

We present results concerning the power to detect past population growth using three microsatellite-based statistics available in the current literature: (1) that based on between-locus variability, (2) that based on the shape of allele size distribution, and (3) that based on the imbalance between variance and heterozygosity at a locus. The analysis is based on the single-step stepwise mutation model. The power of the statistics is evaluated for constant, as well as variable, mutation rates across loci. The latter case is important, since it is a standard procedure to pool data collected at a number of loci, and mutation rates at microsatellite loci are known to be different. Our analysis indicates that the statistic based on the imbalance between allele size variance and heterozygosity at a locus has the highest power for detection of population growth, particularly when mutation rates vary across loci.

Evolution, Molecular↗
PubMed1992

Statistical method for estimating the standard errors of branch lengths in a phylogenetic tree reconstructed without assuming equal rates of nucleotide substitution among different lineages.

A statistical method is developed for estimating the standard errors of branch lengths in a phylogenetic tree reconstructed without assuming equal rates of nucleotide substitution among different lineages. This method can be easily used for testing whether the length of an interior branch in a reconstructed tree is positive, i.e., whether the topology of the tree is correct. Computer simulations indicate that this method is appropriate for a statistical test. As an example, this method is applied to phylogenetic trees reconstructed for the four hominoid species: human, chimpanzee, gorilla, and orangutan. The results obtained show that the present method provides a powerful statistical test.

Animals↗
PubMed1994

Statistical methodology for the concurrent assessment of interrater and intrarater reliability: using goniometric measurements as an example.

Statistical methodology for the concurrent assessment of interrater and intrarater reliability is presented. Application of the methodology is illustrated with an example of one therapist using two goniometers repeatedly to measure knee joint angles. Methods for estimating the coefficients, testing hypotheses, constructing confidence intervals, and computing sample size requirements are provided. In addition, the calculation and clinical interpretation of the standard error of measurement (SEM) are discussed. It is recommended that (1) when both interrater and intrarater reliability are being assessed, a repeated-measures design be used to take advantage of the increased precision gained by using all observations in the statistical analysis, and (2) appropriate statistical tests, confidence intervals, and SEMs always be used in conjunction with the estimated reliability coefficients.

Bias↗
PubMed1994

Use of statistical control charts to assess outcomes of medical care: pneumonia in Medicare patients.

Detection of nonrandom variation in outcomes with statistical control charts is at the heart of quality improvement techniques. The authors examined the charts' ability to detect variations in outcome of pneumonia. They surveyed Medicare claims data for DRG 89, pneumonia with complications or co-morbidities, from November 1988 through October 1991 at 20 Illinois hospitals with the most Medicare discharges for DRG 89. Control charts were constructed on five outcomes--mean length of stay, range of length of stay, mortality, readmissions, and complications. Standard techniques from industrial statistics were used to construct the historical means and control limits derived from 2 years of data, to plot the monthly samples from the 3rd year of data and to score the control charts for nonrandom variation at less than 1% probability. The observed number of control charts with nonrandom variation was 33 of 100; the expected number was 9.18 (p < 0.0001). Nineteen hospitals had 1 to 3 control charts with nonrandom variation on the five outcomes, whereas only one hospital had none. The number of control charts with nonrandom variation per hospital did not correlate with hospital size, occupancy, teaching status, location, or payer-mix. Statistical control charts provide simple tools for identification of nonrandom variation in outcomes. To the extent that these variations can be related to quality issues, the charts will be useful for quality management.

Aged↗
PubMed2000

Antibiotics and return visits for respiratory illness: a comparison of pooled versus hierarchical statistical methods.

BACKGROUND: Antibiotic prescribing for respiratory illness has been associated with small reductions in return visits in an analysis of a large practice-based network. In this study, we apply hierarchical analytical methods that account for the clustering of patients by practices to identify whether antibiotic prescribing by primary care physicians reduces subsequent visits for 6 acute respiratory illnesses-upper respiratory infection, pharyngitis, bronchitis, otitis media, sinusitis, and cough. METHODS: The study data came from 318 family physicians and internists in 45 practices in the Practice Partner Research Network from January 1995 through December 1996, with 255,564 active patients. Patients treated with antibiotics were compared with those who were not on the frequency of revisit within the next 14 days. A simple pooling model and 3 hierarchical statistical models (fixed-effects, random-effects, and Bayesian) were used to compare the odds-ratios for return visits. RESULTS: Statistically significant results were found only for bronchitis and sinusitis by the hierarchical models, but the simple pooling model produced statistically significant results for all study conditions. CONCLUSION: We conclude that antibiotics may reduce return visits for patients with bronchitis and sinusitis, but not for patients with other respiratory illness (upper respiratory infection, pharyngitis, otitis media, or cough). Studies of large clinical databases should use methods of analysis that account for the grouping of patients by practice to avoid false positive associations (type I errors.)

Academic Medical Centers↗