CLUM: a cluster program for analyzing microarray data.

Microarray technology is increasingly being applied in biological and medical research to address a wide range of problems. Cluster analysis has proven to be a very useful tool for investigating the structure of microarray data. This paper presents a program for clustering microarray data, which is based on the so call path-distance. The algorithm gives in each step a partition in two clusters and no prior assumptions on the structure of clusters are required. It assigns each object (gene or sample) to only one cluster and gives the global optimum for the function that quantifies the adequacy of a given partition of the sample into k clusters. The program was tested on experimental data sets, showing the robustness of the algorithm.

INCA: new statistic for estimating the number of clusters and identifying atypical units.

This paper presents a solution to two problems that arise in the classification of data such as types of tumor, samples of gene expression profiles or general biomedical data. First, to estimate the real number of clusters in a data set and second to decide whether a new unit belongs to one of these previously identified clusters or it is an outlier or atypical unit. We propose a new statistic which allows us to solve these problems. As our approach is based on a measure of distance or dissimilarity between any pair of units, it can be applied to any kind of multivariate data (continuous, binary or multi-attribute data) and it has applications in many biomedical fields. We validated the approach in simulated examples and applied it to the diagnosis of dermal diseases and to the analysis of lymphatic cancer data, showing the good performance of our approach.

Very-long-chain omega-3 fatty acids as markers for habitual fish intake in a population consuming mainly lean fish: the EPIC cohort of Gipuzkoa. European Prospective Investigation into Cancer and Nutrition.

OBJECTIVE: To assess the relationship between habitual fish intake and fatty acid levels in serum as well as in the LDL fractions of serum phospholipids and cholesteryl esters. DESIGN: Cross-sectional study. SETTING: Cohort of Gipuzkoa (Basque Country, northern Spain) included in the European Prospective Investigation into Cancer and Nutrition (EPIC) project. SUBJECTS: Random sample of 120 healthy volunteers of both sexes aged 35-65 y, divided into various consumption groups according to daily fish intake. METHODS: Data on habitual intake over the previous year was collected by trained interviewers by means of a computerized questionnaire based on the diet history method. Fasting venous blood samples were drawn and fatty acids were measured by gas-liquid chromatography. RESULTS: Lean fish accounted for 78% of all fish consumption in the highest consumption group (>115 g/day) and for 60% in the lowest (<31 g/day). The mean concentrations of omega-3 polyunsaturated fatty acids (PUFA), eicosapentaenoic acid (EPA, C20:5, omega-3), and docosahexaenoic acid (DHA, C22:6, omega-3) in serum and in the LDL fractions of serum phospholipids and cholesteryl esters increased significantly from the lowest to the highest fish consumption categories. Fish intake showed a statistically significant relationship with omega-3 PUFA, EPA and DHA in serum and in the LDL fractions of serum phospholipids and cholesteryl esters both in the simple linear regression analysis and in a multiple regression model adjusted by age, body mass index (BMI) and vegetable intake. CONCLUSIONS: Habitual fish intake is reflected in the content of EPA and DHA in serum and in the LDL phospholipid and cholesteryl esters fractions. The concentrations of very-long-chain omega-3 fatty acids are useful biomarkers for dietary fish intake, mainly lean fish. SPONSORSHIP: Europe Against Cancer Programme of the European Union (agreement SOC 97 200302 05F02); 'Fondo de Investigaciones Sanitarias', Spanish Ministry of Health (FIS grant 99/0024-05); Government of the Basque Country; and 'Fundación Científica de la Asociación Española contra el Cáncer'.