Manual d’eines estadístiques bàsiques per a usuaris

“Manual d’eines estadístiques bàsiques per a usuaris”, pretén com el seu nom indica ser una guia d’estadística bàsica per als usuaris. En aquest sentit és una publicació activa on es van incloent i/o ampliant tots aquells temes d’interès. De cada eina estadística es dona una idea clara i fonamental de perquè serveix i de sota quines condicions és correcte aplicar-la. Alguns capítols inclouen un petit exemple amb les corresponents instruccions en llenguatge R per tal de mostrar com realitzar els càlculs mitjançant aquesta eina informàtica

Identification of differentially expressed genes by means of outlier detection

BACKGROUND: An important issue in microarray data is to select, from thousands of genes, a small number of informative differentially expressed (DE) genes which may be key elements for a disease. If each gene is analyzed individually, there is a big number of hypotheses to test and a multiple comparison correction method must be used. Consequently, the resulting cut-off value may be too small. Moreover, an important issue is the selection's replicability of the DE genes. We present a new method, called ORdensity, to obtain a reproducible selection of DE genes. It takes into account the relation between all genes and it is not a gene-by-gene approach, unlike the usually applied techniques to DE gene selection. RESULTS: The proposed method returns three measures, related to the concepts of outlier and density of false positives in a neighbourhood, which allow us to identify the DE genes with high classification accuracy. To assess the performance of ORdensity, we used simulated microarray data and four real microarray cancer data sets. The results indicated that the method correctly detects the DE genes; it is competitive with other well accepted methods; the list of DE genes that it obtains is useful for the correct classification or diagnosis of new future samples and, in general, it is more stable than other procedures. CONCLUSIONS: ORdensity is a new method for identifying DE genes that avoids some of the shortcomings of the individual gene identification and it is stable when the original sample is changed by subsamples

Reliable software

In biomedicine, biodiversity and other fields of research, large databases are used. Assuming that a proper statistical procedure has been chosen, a crucial point is the selection of the right software to compute the data. The available software has to be sufficiently proven and having the guarantee that it is reliable. Currently, it is easy to obtain free software for most statistical procedures. We agree that a free software is especially useful because as a large number of researchers can take benefit of it. However, in several repositories, software has not been sufficiently proven, and could yield to erroneous results. This situation could lead to dreadful consequences, for instance, when studying cancer or complex genetic diseases. We propose that researchers should be especially accurate in their software selection, and also the control levels should be improved in order to upload new software in a public repository

Study of linkage between miniature and singed genes in Drosophila melanogaster

We have developed a practical exercise for undergraduate students whose main aim is to identify, using genetic crosses, a pair of D. melanogaster mutations (miniature and singed). Each student receives a vial with the problem strain containing two unknown mutations. The first step is to observe and describe both mutations. Then, the students carry out genetic crosses between mutant and normal strains: (P) ♀ mutant strain × ♂ normal strain (P) ♀ normal strain × ♂ mutant strain A different offspring is expected in these crosses: in the first one we will obtain normal females and m sn males, whereas in the second all individuals will present normal phenotype. It is possible to deduce that both are sex linked mutations. With this information and to simplify the amount of work, only F1 individuals from the first cross will be used (m+sn+ / m sn × m sn / Y chrom.) to obtain the F2 generation. By counting the number of miniature (recombinant type), singed (recombinant type), miniature-singed (parental type) and normal (parental type) flies it is possible to estimate the recombination frequency between both genes. Knowing the phenotype, their chromosomal location (X chromosome) and the genetic distance between both mutations, it is possible to identify them by finding all this information in a Drosophila melanogaster genetic map. Additionally, a statistical analysis can be carried out to compare the number of expected F2 individuals with those observed in the experiment. As the distance between both genes is 15.1 m.u., then the expected percentages for each phenotype would be: normal (42.45%), miniature-signed (42.45%), miniature (7.55%) and singed (7.55%). Multiplying the frequency of each class by the total number of individuals obtained in the F2 it is possible to estimate the expected number of flies for each class. Finally, a χ2 test can be computed to ascertain whether there are significant differences between expected and observed number of individuals

Why Mathematics is essential in Biomedical Sciences degree?

Improvement of mathematical education and motivation of students in the mathematics" area is needed. What can be done? We introduce some ideas to generate the student"s interest for mathematics, because they often present difficulties in appreciating the relevance of mathematics and its role in the health sciences. We consider that a cornerstone in the strategy to attract the students" interest is linking the mathematics with real biomedical situations. We proceed in the following manner: We first present a real biomedical situation to produce interest and to generate curiosity. Second, we ask thought-provoking questions to students as: Which is the biomedical problem presented? Which is my knowledge on this situation? What could I do to solve this biomedical situation? Do I need some new mathematical concepts and procedures? Thereupon, the teacher explains the mathematical concepts necessary to solve the case presented, providing definitions, properties and tools for graphical display and/or mathematical calculations. In this learning methodology, ICTs were cornerstones for reaching the proposed competences. Furthermore, ICTs can also be used in the evaluative task in its two possible aspects: formative and for obtaining a qualification. Comments from students about this new mathematics teaching method indicate that the use of real biomedical case studies kept the lessons in mathematics interesting

Com s'adapten els organismes al canvi climàtic? Les inversions cromosòmiques de Drosophila subobscura: el cas de les poblacions de Sèrbia

És conegut el fet que les inversions cromosòmiques de les poblacions naturals de l'espècie Drosophila subobscura són adaptatives respecte a les variacions de l'ambient. S'ha observat que les inversions canvien en freqüència al llarg del temps segons la predicció de l'escalfament global del nostre planeta. Aquests resultats es posen de manifest en els nostres estudis realitzats a poblacions sèrbies de D. subobscura. Així, el polimorfisme cromosòmic per inversions canvia segons les estacions de l'any i també a llarg termini (períodes de 10-15 anys) d'acord amb el que s'esperaria segons l'escalfament global. Per tant, les inversions cromosòmiques d'aquesta espècie són uns bons indicadors del canvi climàtic i també són útils per estudiar com els organismes s'hi poden adaptar

Medium-term changes in Drosophila subobscura chromosomal inversion polymorphism: a possible relation with global warming?

Drosophila subobscura is a species with a rich chromosomal polymorphism for inversions. Evidence demonstrates that it is adaptive. In the present research, we studied whether it is possible to detect changes in the inversion chromosomal polymorphism of D. subobscura in a medium-term period of time. The Serbian population of Avala was selected and its inversion composition in 2004 and 2011 (a seven year period) was compared. Significant variation was found in the U chromosome. This result was due to a significant increase of U1+2 (warm) and a decrease of Ust (cold) and U1+2+6. Further, minimum, maximum and mean temperatures increased (although not significantly). Thus, U chromosome seems to be able to react in a medium-term to temperature changes in the way expected by the global warming

Inbreeding and thermal adaptation in Drosophila subobscura

Using a well-adapted Drosophila subobscura population (Avala, Serbia), a drastic experiment of inbreeding was carried out to assess whether the expected level of homozygosity could be reached or if other evolutionary forces affected the process. In general, no significant changes of inversion (or arrangement) frequencies were detected after 12 brother sister mating generations. Furthermore, no significant differences were obtained between observed and expected (under the inbreeding model) karyotypic frequencies. Thus, these results seemed to indicate that the main evolutionary factor in the experiment was inbreeding. However, in the G12 generation, complete chromosomal fixation was reached only in two out of the eight final inbred lines. In these lines, the chromosomal compositions were difficult to interpret, but they could be likely a consequence of adaptation to particular laboratory conditions (constant 18 °C, food, light period, etc.). Finally, in a second experiment, the inbred lines presented higher fertility at 18 °C than at 13 °C. Also, there was a significant line effect on fertility: inbred line number 6 (A1, J1, U1+2; U1+2+6, E8, and O3+4+7) presented the highest values, which maybe the result of an adaptation to laboratory conditions. Thus, the results obtained in our experiments reflect the adaptive potential of D. subobscura inversions

Chromosomal Thermal Index: a comprehensive way to integrate the thermal adaptation of Drosophila subobscura whole karyotype

Drosophila has demonstrated to be an excellent model to study the adaptation of organisms to global warming, with inversion chromosomal polymorphism having a key role in this adaptation. Here, we introduce a new index (Chromosomal Thermal Index or CTI) to quantify the thermal adaptation of a population according to its composition of 'warm' and 'cold' adapted inversions. This index is intuitive, has good statistical properties, and can be used to hypothesis on the effect of global warming on natural populations. We show the usefulness of CTI using data from European populations of D. subobscura, sampled in different years. Out of 15 comparisons over time, nine showed significant increase of CTI, in accordance with global warming expectations. Although large regions of the genome outside inversions contain thermal adaptation genes, our results show that the total amount of warm or cold inversions in populations seems to be directly involved in thermal adaptation, whereas the interactions between the inversions content of homologous and non-homologous chromosomes are not relevant

Fuzzy classification with distance-based depth prototypes: High-dimensional unsupervised and/or supervised problems

Supervised and unsupervised classification is crucial in many areas where different types of data sets are common, such as biology, medicine, or industry, among others. A key consideration is that some units are more typical of the group they belong to than others. For this reason, fuzzy classification approaches are necessary. In this paper, a fuzzy supervised classification method, which is based on the construction of prototypes, is proposed. The method obtains the prototypes from an objective function that includes label information and a distance-based depth function. It works with any distance and it can deal with data sets of a wide nature variety. It can further be applied to data sets where the use of Euclidean distance is not suitable and to high-dimensional data (data sets in which the number of features is larger than the number of observations , often written as >> ). In addition, the model can also cope with unsupervised classification, thus becoming an interesting alternative to other fuzzy clustering methods. With synthetic data sets along with high-dimensional real biomedical and industrial data sets, we demonstrate the good performance of the supervised and unsupervised fuzzy proposed procedures