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Biomedical subjects

M W Perlin

Publications and source records attributed to M W Perlin.

8 recordsLinked to original sources
PubMed2001

Linear mixture analysis: a mathematical approach to resolving mixed DNA samples.

With the advent of PCR-based STR typing systems, mixed samples can be separated into their individual DNA profiles. Quantitative peak information can help in this analysis. However, despite such advances, forensic mixture analysis still remains a laborious art, with the high cost and effort often precluding timely reporting. We introduce here a new automated approach to resolving forensic DNA mixtures. Our linear mixture analysis (LMA) is a straightforward mathematical approach that can integrate all the quantitative PCR data into a single rapid computation. LMA has application to diverse mixture problems. As demonstrated here on laboratory STR data, LMA can assess the quality and utility of its solutions. Such rapid and robust methods for computer-based analysis of DNA mixtures may help in reducing crime.

Algorithms↗
PubMed1995

Rapid construction of integrated maps using inner product mapping: YAC coverage of human chromosome 11.

Inner product mapping (IPM) has been proposed as a hybridization-based method for achieving low-cost, high-throughput, high-resolution radiation hybrid (RH) mapping of clones. Using Alu-PCR products of chromosome 11-specific clones, we serially hybridized a set of RHs against gridded filters of YACs having an average size of 350 kb. We then combined these hybridization data with preexisting RH map data to build an inner product map. This binning of 865 YACs provides the first high-resolution large-scale (> twofold redundancy) clonal coverage of human chromosome 11 and is the first inner product map ever constructed. We verified the accuracy and precision of this chromosome 11 map by performing a novel likelihood analysis on independent YAC hybridization data. These results establish that IPM is a highly rapid, inexpensive, accurate, and precise large-scale long-range mapping method, particularly when preexisting RH maps are available, and that IPM can replace or complement more conventional short-range mapping methods. IPM may enable the rapid construction of sequence-ready maps and the binning of expressed sequences.

Chromosome Mapping↗
PubMed1995

Towards fully automated genotyping: use of an X linked recessive spastic paraplegia family to test alternative analysis methods.

Advances in dinucleotide-based genetic maps open possibilities for large scale genotyping at high resolution. The current rate-limiting steps in use of these dense maps is data interpretation (allele definition), data entry, and statistical calculations. We have recently reported automated allele identification methods. Here we show that a 10-cM framework map of the human X chromosome can be analyzed on two lanes of an automated sequencer per individual (10-12 loci per lane). We use this map and analysis strategy to generate allele data for an X-linked recessive spastic paraplegia family with a known PLP mutation. We analyzed 198 genotypes in a single gel and used the data to test three methods of data analysis: manual meiotic breakpoint mapping, automated concordance analysis, and whole chromosome multipoint linkage analysis. All methods pinpointed the correct location of the gene. We propose that multipoint exclusion mapping may permit valid inflation of LOD scores using the equation max LOD-(next best LOD).

Alleles↗
PubMed1995

Toward fully automated genotyping: genotyping microsatellite markers by deconvolution.

Dense genetic linkage maps have been constructed for the human and mouse genomes, with average densities of 2.9 cM and 0.35 cM, respectively. These genetic maps are crucial for mapping both Mendelian and complex traits and are useful in clinical genetic diagnosis. Current maps are largely comprised of abundant, easily assayed, and highly polymorphic PCR-based microsatellite markers, primarily dinucleotide (CA)n repeats. One key limitation of these length polymorphisms is the PCR stutter (or slippage) artifact that introduces additional stutter bands. With two (or more) closely spaced alleles, the stutter bands overlap, and it is difficult to accurately determine the correct alleles; this stutter phenomenon has all but precluded full automation, since a human must visually inspect the allele data. We describe here novel deconvolution methods for accurate genotyping that mathematically remove PCR stutter artifact from microsatellite markers. These methods overcome the manual interpretation bottleneck and thereby enable full automation of genetic map construction and use. New functionalities, including the pooling of DNAs and the pooling of markers, are described that may greatly reduce the associated experimentation requirements.

Algorithms↗
PubMed1994

Intelligent DNA-based molecular diagnostics using linked genetic markers.

This paper describes a knowledge-based system for molecular diagnostics, and its application to fully automated diagnosis of X-linked genetic disorders. Molecular diagnostic information is used in clinical practice for determining genetic risks, such as carrier determination and prenatal diagnosis. Initially, blood samples are obtained from related individuals, and PCR amplification is performed. Linkage-based molecular diagnosis then entails three data analysis steps. First, for every individual, the alleles (i.e., DNA composition) are determined at specified chromosomal locations. Second, the flow of genetic material among the individuals is established. Third, the probability that a given individual is either a carrier of the disease or affected by the disease is determined. The current practice is to perform each of these three steps manually, which is costly, time consuming, labor-intensive, and error-prone. As such, the knowledge-intensive data analysis and interpretation supersede the actual experimentation effort as the major bottleneck in molecular diagnostics. By examining the human problem solving for the task, we have designed and implemented a prototype knowledge-based system capable of fully automating linkage-based molecular diagnostics in X-linked genetic disorders, including Duchenne Muscular Dystrophy (DMD). Our system uses knowledge-based interpretation of gel electrophoresis images to determine individual DNA marker labels, a constraint satisfaction search for consistent genetic flow among individuals, and a blackboard-style problem solver for risk assessment. We describe the system's successful diagnosis of DMD carrier and affected individuals from raw clinical data.

DNA↗
PubMed1994

Toward fully automated genotyping: allele assignment, pedigree construction, phase determination, and recombination detection in Duchenne muscular dystrophy.

Human genetic maps have made quantum leaps in the past few years, because of the characterization of > 2,000 CA dinucleotide repeat loci: these PCR-based markers offer extraordinarily high PIC, and within the next year their density is expected to reach intervals of a few centimorgans per marker. These new genetic maps open new avenues for disease gene research, including large-scale genotyping for both simple and complex disease loci. However, the allele patterns of many dinucleotide repeat loci can be complex and difficult to interpret, with genotyping errors a recognized problem. Furthermore, the possibility of genotyping individuals at hundreds or thousands of polymorphic loci requires improvements in data handling and analysis. The automation of genotyping and analysis of computer-derived haplotypes would remove many of the barriers preventing optimal use of dense and informative dinucleotide genetic maps. Toward this end, we have automated the allele identification, genotyping, phase determinations, and inheritance consistency checks generated by four CA repeats within the 2.5-Mbp, 10-cM X-linked dystrophin gene, using fluorescein-labeled multiplexed PCR products analyzed on automated sequencers. The described algorithms can deconvolute and resolve closely spaced alleles, despite interfering stutter noise; set phase in females; propagate the phase through the family; and identify recombination events. We show the implementation of these algorithms for the completely automated interpretation of allele data and risk assessment for five Duchenne/Becker muscular dystrophy families. The described approach can be scaled up to perform genome-based analyses with hundreds or thousands of CA-repeat loci, using multiple fluorophors on automated sequencers.

Alleles↗
PubMedDate not supplied

Computer-based tutorial in MR imaging.

PURPOSE: To test the effectiveness of customized software as a teaching tool to help the novice understand basic physics concepts underlying the creation of MR images via various pulse sequences. METHODS: The authors have developed animating graphic and highly interactive electronic MR audiovisual software for the Macintosh computer in the C programming language, and have integrated it into the classroom setting for teaching MR imaging physics concepts such as T1, T2, T2*, proton density, RF excitation, TR, TE, TI, flip angle, static magnetic field strength, gradient magnetic fields, section thickness, number of phase-encoding gradients, number of excitations, field of view, intersection gap, receiver bandwidth, contrast agent(s), etc. The program interactively demonstrates the effects of these variables upon such imaging objectives as voxel dimensions, section quantity, total scanned volume, signal-to-noise ratio, contrast, contrast-to-noise ratios, resolving power, and scan acquisition time. Partial saturation, gradient echo, inversion recovery, and fat-saturation imaging techniques are included. Written posttests on the syllabus covered in our basic MR course were administered to three groups: 43 student professionals (technologist/physicist/radiologist) (control professional group) before, 149 student professionals (exposed professional group) after the addition of the tutorial software into the MR course as an integral part of the teaching process, and a group of 200 pharmaceutical sales staff with little to no prior MR or scientific background (exposed pharmaceutical group). The scores were then evaluated and compared among the groups. One hundred ten students exposed to this software also anonymously rated the software on a 1 to 5 scale (harmful to very helpful, respectively) as to their feeling regarding its role in their MR educational experience and the ease with which they were able to understand the material covered in the basic MR course curriculum. RESULTS: Mean test scores were statistically significantly lower in the Control Professional Group (60%, +/- 2.59 standard error of the mean (SEM)) than in either the Exposed Pharmaceutical (73% +/- 0.75 SEM) or Exposed Professional Groups (77% +/- 0.99 SEM). The mean subjective assessment score regarding the software was 4.8 (scale 1 to 5). CONCLUSION: This custom-developed interactive MR tutorial software is demonstrated to be effective in assisting even those new to MR imaging in understanding the concepts underlying MR imaging physics in a manner that is felt to be significantly more palatable than lectures, articles, and/or textbooks alone.

Computer-Assisted Instruction↗