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Michael S Rosenberg

Publications and source records attributed to Michael S Rosenberg.

12 recordsLinked to original sources
PubMed2006

How should gaps be treated in parsimony? A comparison of approaches using simulation.

Simulation with indels was used to produce alignments where true site homologies in DNA sequences were known; the gaps from these datasets were removed and the sequences were then aligned to produce hypothesized alignments. Both alignments were then analyzed under three widely used methods of treating gaps during tree reconstruction under the maximum parsimony principle. With the true alignments, for many cases (82%), there was no difference in topological accuracy for the different methods of gap coding. However, in cases where a difference was present, coding gaps as a fifth state character or as separate presence/absence characters outperformed treating gaps as unknown/missing data nearly 90% of the time. For the hypothesized alignments, on average, all gap treatment approaches performed equally well. Data sets with higher sequence divergence and more pectinate tree shapes with variable branch lengths are more affected by gap coding than datasets associated with shallower non-pectinate tree shapes.

Computer Simulation↗
PubMed2006

Intraoperative fragment detection during percutaneous nephrolithotomy: evaluation of high magnification rotational fluoroscopy combined with aggressive nephroscopy.

PURPOSE: Percutaneous nephrolithotomy effectively treats large volume renal calculi but relies on postoperative imaging to judge success. We evaluated the effectiveness of maximizing intraoperative imaging through combined high resolution fluoroscopy and flexible nephroscopy. MATERIALS AND METHODS: Percutaneous nephrolithotomy was performed cooperatively with a radiologist in an interventional radiology suite equipped with a ceiling mounted, high resolution C-arm. Aggressive rigid and flexible nephroscopy was performed. At the conclusion patients were prospectively classified as radiologically and/or endoscopically stone-free. Postoperative noncontrast CT allowed fragment classification as stone-free, 2 mm or less, 2 to 4 mm and greater than 4 mm. RESULTS: The average stone dimension +/- SEM was 579 +/- 77 mm(2) in 25 consecutive renal units. CT demonstrated that 15 renal units (60%) were stone-free after the primary procedure, while 2 (8%), 5 (20%) and 3 (12%) had fragments 2 or less, 2 to 4 and greater than 4 mm, respectively. Of 21 renal units considered endoscopically and fluoroscopically stone-free postoperative CT demonstrated that 6 had residual fragments, of which all were less than 4 mm. All 4 renal units not considered radiologically and endoscopically stone-free had fragments on CT. Intraoperative fluoroscopy after nephroscopy demonstrated fragments in 36% of renal units, of which after further nephroscopy 78% were stone-free on CT. The sensitivity of intraoperative imaging with reference to the gold standard of postoperative CT was 40%, 38% and 100% at thresholds of 0, 2 and 4 mm, respectively. Specificity was 100%, 94% and 95%, respectively. CONCLUSIONS: Flexible nephroscopy combined with high magnification rotational fluoroscopy allows sensitive and specific intraoperative detection of residual fragments, enabling immediate removal or the planning of necessary second look nephroscopy.

Endoscopy↗
PubMed2006

Multiple sequence alignment accuracy and phylogenetic inference.

Phylogenies are often thought to be more dependent upon the specifics of the sequence alignment rather than on the method of reconstruction. Simulation of sequences containing insertion and deletion events was performed in order to determine the role that alignment accuracy plays during phylogenetic inference. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (ultrametric equal branch length, ultrametric random branch length, nonultrametric random branch length). Comparisons between hypothesized alignments and true alignments enabled determination of two measures of alignment accuracy, that of the total data set and that of individual branches. In general, our results indicate that as alignment error increases, topological accuracy decreases. This trend was much more pronounced for data sets derived from more pectinate topologies. In contrast, for balanced, ultrametric, equal branch length tree shapes, alignment inaccuracy had little average effect on tree reconstruction. These conclusions are based on average trends of many analyses under different conditions, and any one specific analysis, independent of the alignment accuracy, may recover very accurate or inaccurate topologies. Maximum likelihood and Bayesian, in general, outperformed neighbor joining and maximum parsimony in terms of tree reconstruction accuracy. Results also indicated that as the length of the branch and of the neighboring branches increase, alignment accuracy decreases, and the length of the neighboring branches is the major factor in topological accuracy. Thus, multiple-sequence alignment can be an important factor in downstream effects on topological reconstruction.

Base Sequence↗
PubMed2005

Multiple sequence alignment accuracy and evolutionary distance estimation.

BACKGROUND: Sequence alignment is a common tool in bioinformatics and comparative genomics. It is generally assumed that multiple sequence alignment yields better results than pair wise sequence alignment, but this assumption has rarely been tested, and never with the control provided by simulation analysis. This study used sequence simulation to examine the gain in accuracy of adding a third sequence to a pair wise alignment, particularly concentrating on how the phylogenetic position of the additional sequence relative to the first pair changes the accuracy of the initial pair's alignment as well as their estimated evolutionary distance. RESULTS: The maximal gain in alignment accuracy was found not when the third sequence is directly intermediate between the initial two sequences, but rather when it perfectly subdivides the branch leading from the root of the tree to one of the original sequences (making it half as close to one sequence as the other). Evolutionary distance estimation in the multiple alignment framework, however, is largely unrelated to alignment accuracy and rather is dependent on the position of the third sequence; the closer the branch leading to the third sequence is to the root of the tree, the larger the estimated distance between the first two sequences. CONCLUSION: The bias in distance estimation appears to be a direct result of the standard greedy progressive algorithm used by many multiple alignment methods. These results have implications for choosing new taxa and genomes to sequence when resources are limited.

Algorithms↗
PubMed2005

Evolutionary distance estimation and fidelity of pair wise sequence alignment.

BACKGROUND: Evolutionary distances are a critical measure in comparative genomics and molecular evolutionary biology. A simulation study was used to examine the effect of alignment accuracy of DNA sequences on evolutionary distance estimation. RESULTS: Under the studied conditions, distance estimation was relatively unaffected by alignment error (50% or more of the sites incorrectly aligned) as long as 50% or more of the sites were identical among the sequences (observed P-distance < 0.5). Beyond this threshold, the alignment procedure artificially inflates the apparent sequence identity, skewing distance estimates, and creating alignments that are essentially indistinguishable from random data. This general result was independent of substitution model, sequence length, and insertion and deletion size and rate. CONCLUSION: Examination of the estimated sequence identity may yield some guidance as to the accuracy of the alignment. Inaccurate alignments are expected to have large effects on analyses dependent on site specificity, but analyses that depend on evolutionary distance may be somewhat robust to alignment error as long as fewer than half of the sites have diverged.

Algorithms↗
PubMed2005

Inferring species phylogenies from multiple genes: concatenated sequence tree versus consensus gene tree.

Phylogenetic trees from multiple genes can be obtained in two fundamentally different ways. In one, gene sequences are concatenated into a super-gene alignment, which is then analyzed to generate the species tree. In the other, phylogenies are inferred separately from each gene, and a consensus of these gene phylogenies is used to represent the species tree. Here, we have compared these two approaches by means of computer simulation, using 448 parameter sets, including evolutionary rate, sequence length, base composition, and transition/transversion rate bias. In these simulations, we emphasized a worst-case scenario analysis in which 100 replicate datasets for each evolutionary parameter set (gene) were generated, and the replicate dataset that produced a tree topology showing the largest number of phylogenetic errors was selected to represent that parameter set. Both randomly selected and worst-case replicates were utilized to compare the consensus and concatenation approaches primarily using the neighbor-joining (NJ) method. We find that the concatenation approach yields more accurate trees, even when the sequences concatenated have evolved with very different substitution patterns and no attempts are made to accommodate these differences while inferring phylogenies. These results appear to hold true for parsimony and likelihood methods as well. The concatenation approach shows >95% accuracy with only 10 genes. However, this gain in accuracy is sometimes accompanied by reinforcement of certain systematic biases, resulting in spuriously high bootstrap support for incorrect partitions, whether we employ site, gene, or a combined bootstrap resampling approach. Therefore, it will be prudent to report the number of individual genes supporting an inferred clade in the concatenated sequence tree, in addition to the bootstrap support.

Animals↗
PubMed2005

The file-drawer problem revisited: a general weighted method for calculating fail-safe numbers in meta-analysis.

Quantitative literature reviews such as meta-analysis are becoming common in evolutionary biology but may be strongly affected by publication biases. Using fail-safe numbers is a quick way to estimate whether publication bias is likely to be a problem for a specific study. However, previously suggested fail-safe calculations are unweighted and are not based on the framework in which most meta-analyses are performed. A general, weighted fail-safe calculation, grounded in the meta-analysis framework, applicable to both fixed- and random-effects models, is proposed. Recent meta-analyses published in Evolution are used for illustration.

Meta-Analysis as Topic↗
PubMed2003

Patterns of transitional mutation biases within and among mammalian genomes.

Significant transition/transversion mutation bias is a well-appreciated aspect of mammalian nuclear genomes; however, patterns of bias among genes within a genome and among species remain largely uncharacterized. Understanding these patterns is important for understanding similarities and differences in mutational patterns among genomes and genomic regions. Therefore, we have conducted an analysis of 7,587 pairs of sequences of 4,347 mammalian protein-coding genes from seven species (human, mouse, rat, cow, sheep, pig, and macaque) and from the introns of 51 gene pairs and multiple intergenic regions (37 kbp, 52 kbp and 65 kbp) from the human, chimpanzee, and baboon genomes. Our analyses show that genes and regions with widely varying base composition exhibit uniformity of transition mutation rate both within and among mammalian lineages, as long as the transitional mutations caused by CpG hypermutability are excluded. The estimates show no relationship to potential intrachromosomal or interchromosomal effects. This uniformity points to similarity in point mutation processes in genomic regions with substantially different GC-content biases.

Animals↗
PubMed2003

Heterogeneity of nucleotide frequencies among evolutionary lineages and phylogenetic inference.

A major assumption of many molecular phylogenetic methods is the homogeneity of nucleotide frequencies among taxa, which refers to the equality of the nucleotide frequency bias among species. Changes in nucleotide frequency among different lineages in a data set are thought to lead to erroneous phylogenetic inference because unrelated clades may appear similar because of evolutionarily unrelated similarities in nucleotide frequencies. We tested the effects of the heterogeneity of nucleotide frequency bias on phylogenetic inference, along with the interaction between this heterogeneity and stratified taxon sampling, by means of computer simulations using evolutionary parameters derived from genomic databases. We found that the phylogenetic trees inferred from data sets simulated under realistic, observed levels of heterogeneity for mammalian genes were reconstructed with accuracy comparable to those simulated with homogeneous nucleotide frequencies; the results hold for Neighbor-Joining, minimum evolution, maximum parsimony, and maximum-likelihood methods. The LogDet distance method, specifically designed to deal with heterogeneous nucleotide frequencies, does not perform better than distance methods that assume substitution pattern homogeneity among sequences. In these specific simulation conditions, we did not find a significant interaction between phylogenetic accuracy and substitution pattern heterogeneity among lineages, even when the taxon sampling is increased.

Algorithms↗
PubMed2002

Using a dopamine type 1A receptor agonist in high-risk patients to ameliorate contrast-associated nephropathy.

OBJECTIVE: The objective of our study was to evaluate the effects of fenoldopam mesylate, a dopamine type 1A receptor agonist and a potent renal vasodilator that markedly increases renal blood flow, on kidney function of patients who were receiving iodinated contrast material for an interventional procedure and thought to be at high risk of contrast-associated nephropathy. MATERIALS AND METHODS: We retrospectively reviewed the records of all patients who received fenoldopam mesylate to determine the acute and, when possible, the longer term effects on kidney function. RESULTS: Twenty-nine cases were reviewed. The average serum creatinine value before contrast administration was 2.55 mg/dL (range, 1.3-5.8 mg/dL) [corrected]. Twenty-four hours after contrast administration, serum creatinine was measured in 28 of the 29 patients. The serum creatinine values had decreased in 16 of the 28 patients by an average of 0.55 mg/dL [corrected]. In nine patients, the serum creatinine value had not changed. Two of the three increases in the serum creatinine value appear to have been caused primarily by problems that did not involve the contrast material. CONCLUSION: The use of fenoldopam mesylate at appropriate doses offers patients at high risk for contrast-associated nephropathy a chance to avoid this complication. To learn the extent and true nature of the effect of fenoldopam mesylate in this patient population requires a rigorous scientific trial, which is currently underway.

Adult↗
PubMedDate not supplied

A new protocol for evaluating putative causes for multiple variables in a spatial setting, illustrated by its application to European cancer rates.

We introduce a statistical protocol for analyzing spatially varying data, including putative explanatory variables. The procedures comprise preliminary spatial autocorrelation analysis (from an earlier study), path analysis, clustering of the resulting set of path diagrams, ordination of these diagrams, and confirmatory tests against extrinsic information. To illustrate the application of these methods, we present incidence and mortality rates of 31 organ- and sex-specific cancers in Europe; these rates vary markedly with geography and type of cancer. Additionally, we investigated three factors (ethnohistory, genetics, and geography) putatively affecting these rates. The five variables were correlated separately for the 31 cancers over European reporting stations. We analyzed the correlations by path analysis, k-means clustering, and nonmetric multidimensional scaling; coefficients of the 31 path diagrams modeling the correlations vary substantially. To simplify interpretation, we grouped the diagrams into five clusters, for which we describe the differential effects of the three putative causes on incidence and mortality. When scaled, the path coefficients intergrade without marked gaps between clusters. Ethnic differences make for differences in cancer rates, even when the populations tested are ancient and complex mixtures. Path analysis usefully decomposes a structural model involving effects and putative causes, and estimates the magnitude of the model's components. Smooth intergradation of the path coefficients suggests the putative causes are the results of multiple forces. Despite this continuity of the path diagrams of the 31 cancers, clustering offers a useful segmentation of the continuum. Etiological and other extrinsic information on the cancers map significantly into the five clusters, demonstrating their epidemiological relevance.

Biometry↗