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Biomedical subjects

F R McMorris

Publications and source records attributed to F R McMorris.

10 recordsLinked to original sources
PubMed1998

Measuring the phylogenetic randomness of biological data sets.

Two qualitative taxonomic characters are potentially compatible if the states of each can be ordered into a character state tree in such a way that the two resulting character state trees are compatible. The number of potentially compatible pairs (NPCP) of qualitative characters from a data set may be considered to be a measure of its phylogenetic randomness. The value of NPCP depends on the number of evolutionary units (EUs), the number of characters, the number of states in the characters, the distributions of EUs among these states, and the amount and distribution of missing information and so does not directly indicate degree of phylogenetic randomness. Thus, for an observed data set, we used Monte Carlo methods to estimate the probability that a data set chosen equiprobably from among those identical (with respect to all the other above determining features) to the observed data set would have as high (or low) an NPCP as the observed data set. This probability, the realized significance of the observed NPCP, is attractive as an indication of phylogenetic randomness because it does not require the assumptions made by other such methods: No character state trees are assumed and consequently, only potential compatibility can be determined; no particular method of phylogenetic estimation is assumed; and no phylogenetic trees are constructed. We determined the values and significances of NPCP for analyses of 57 data sets taken from 53 published sources. All data sets from 37 of those sources exhibited realized significances of < 0.01, indicating high levels of phylogenetic nonrandomness. From each of the remaining 16 sources, at least one data set was more phylogenetically random. Inclusion of outgroups changed significance in some cases, but not always in the same direction. Data sets with significantly low NPCP may be consistent with an ancient hybrid origin (or other ancient polyphyletic gene exchange, crossing over, viral transfer, etc.) of the study group.

Monte Carlo Method↗
PubMed1994

The agreement metric for labeled binary trees.

Let S be a set of n objects. A binary tree of S is a binary tree whose leaves are labeled without repetition from S. The operation of pruning a tree T is that of removing some leaves from T and suppressing all inner vertices of degree 2 which are formed by this deletion. Given two trees T and U, an agreement tree is a tree that can be obtained from T as well as from U by pruning the fewest number of leaves from the two trees. A quadratic algorithm is presented for doing this and two metrics are defined based on agreement trees.

Algorithms↗
PubMed1993

A consensus program for molecular sequences.

Although molecular biologists often calculate consensus sequences from aligned DNA or protein sequences, relatively little is known about the properties of many of the consensus methods being used. Consequently, we wrote a program, CONSENSUS, to analyze and compare methods of calculating a consensus result (a base, an ambiguity code or a subset of codes) at a position in an aligned set of molecular sequences. The program supports alphabets of up to four symbols (e.g. [R,Y] or [A,C,G,T]). The program's output makes it suitable for exploratory data analysis or for selecting values of thresholds or confidence levels in consensus methods having such parameters.

Base Sequence↗
PubMed1992

Threshold consensus methods for molecular sequences.

We introduce a parameterized threshold consensus method (th chi) for molecular sequences which is based on a majority-rule voting principle. In contrast to other frequency-based methods, the th chi method uses a single criterion to return ambiguity codes of different lengths. We derive basic features of the method and establish that it returns at most two ambiguity codes at any position of the consensus sequence. We bound from below the size of the frequency gap that exists when the th chi method returns an ambiguity code. Using such properties, we compare the th chi method to other consensus methods for molecular sequences which are defined in terms of threshold or gap criteria.

Base Sequence↗
PubMed1992

Critical comparison of consensus methods for molecular sequences.

Consensus methods are recognized as valuable tools for data analysis, especially when some sort of data aggregation is desired. Although consensus methods for sequences play a vital role in molecular biology, researchers pay little heed to the features and limitations of such methods, and so there are risks that criteria for constructing consensus sequences will be misused or misunderstood. To understand better the issues involved, we conducted a critical comparison of nine consensus methods for sequences, of which eight were used in papers appearing in this journal. We report the results of that comparison, and we make recommendations which we hope will assist researchers when they must select particular consensus methods for particular applications.

Algorithms↗
PubMed1992

Interpreting consensus sequences based on plurality rule.

Our goal is to help researchers interpret the results of a function, based on the concept of plurality rule, that calculates a consensus of a profile of molecular bases. By expressing the plurality rule function as a composition of simpler functions, we obtain both an algorithm to calculate the consensus result and an upper bound on the number of nonequivalent results. Consequently, when used to analyze molecular sequences such as DNA or RNA, the plurality rule function yields at most 48 nonequivalent consensus results. For problems of reasonable size, we describe an algorithm to calculate the probability that each consensus result would occur if the bases were equally likely to appear at every position of the plurality rule function's input profile.

Algorithms↗
PubMed1991

Consensus weak hierarchies.

An axiomatic characterization is presented for consensus functions defined on weak hierarchies. These functions are generalizations of the majority rule consensus.

Classification↗
PubMed1977

When are two qualitative taxonomic characters compatible?

A proof is given of a procedure that has previously appeared claiming to determine when two amino acid positions on a protein could both possibly be divergent taxonomic characters. An algorithm for executing this procedure is described.

Amino Acid Sequence↗