Abstract Summary: GeneANOVA is an ANOVA-based software devoted to the analysis of gene expression data. Availability: GeneANOVA is freely available on request for non-commercial use. Contact: [email protected]

MOTIVATION: Compression algorithms can be used to analyse genetic sequences. A compression algorithm tests a given property on the sequence and uses it to encode the sequence: if the property is true, it reveals some structure of the sequence which can be described briefly, this yields a description of the sequence which is shorter than the sequence of nucleotides given in extenso. The more a sequence is compressed by the algorithm, the more significant is the property for that sequence. RESULTS: We present a compression algorithm that tests the presence of a particular type of dosDNA (defined ordered sequence-DNA): approximate tandem repeats of small motifs (i.e. of lengths < 4). This algorithm has been experimented with on four yeast chromosomes. The presence of approximate tandem repeats seems to be a uniform structural property of yeast chromosomes.

A program for assembling sequences by using a global approach has been developed. By successive steps, a more and more precise classification of DNA fragments permits the positioning of the sequences on the contig; after having detected the pairs of overlapping sequences, groups are formed such that all sequences in a group overlap. Sequences common to several groups enable the groups to be ordered in a series. Ambiguities in the order of groups can arise at this stage, due to the presence of repeated fragments; different solutions are then proposed. Putting the groups into order leads to a preclassification of sequences. The fragments are then aligned by group, by searching for words common to all sequences in the group, and using an algorithm of dynamic programming. A detailed example on a set of nine sequences accompanies the description of the method.

A method aimed at classifying protein sequences without resorting to pairwise alignment is presented. Called DOCMA (DOt-plot Comparisons by Multivariate Analysis), it is based on a multivariate analysis of the pairwise dot-plots between all the sequences in the set. The dot-plots are first simplified by considering only the projections of the 'diagonal' segments of similarity onto the axes. From these projections a data matrix is built, in which each column is representative of the comparisons of one given sequence with all the other ones. This data matrix is then transformed into a distance matrix by a chi-squared analysis, from which the coordinates of the sequences in an orthonormal Euclidean space are obtained. The sequences are finally classified by a dynamic clustering procedure followed by a search for strong clusters. Application of this method to protein families such as the globins, the cytochromes c and the aminoacyl-tRNA synthetases shows that it is quite effective in delineating subgroups that contain even distantly related sequences.

The table of 'biochemical pathways' published by Boehringer is considered as the most exhaustive document dealing with intermediary metabolism. The present work consisted of constructing a database in which is collected everything known to date about intermediary metabolism: metabolic pathways, bioreactions, metabolites, enzymatic activities, genes and regulation. Data on genes make it possible to establish a link with existing computer structures specialized for genomic sequences. The present structure of the database presented here consists of three environments. The first environment is graphic; it is modeled upon the Boehringer table, but is more convenient to use. The second environment provides the user with all kinds of manipulations of data (entries, corrections, deletions, consistency, limiting redundancy, etc.). These operations either are automatic or depend on a user-friendly interface (menus selected with the mouse) and so allow biologists at all levels to use the database and to develop it for their own particular needs. Finally, the third environment offers various procedures that make it possible to carry out multicriteria research on all the data in the database at once. This database can thus be substituted for the Boehringer table as a standard reference. It is also a tool that can be used to develop information systems not only in the domain of metabolism but also in the study of genomes (modeling, analysis of data, predictions, etc.).

The graphical representation of distance matrices in a Euclidean space allows the merging of two distance matrices since the two matrices have shared elements. The graphical representation of the merging of the two distance matrices is associated with a robust method of classification that allows one to distinguish species for which membership to a cluster cannot be established with certainty. These possibilities are exploited to test the consistency of phylogenetic trees, and to establish exact relations between species for which one possesses different independent distance measurements (distance matrices established from several types of sequences for instance). The whole set of programs is written in BASIC and runs on microcomputers.