MOTIVATION: How individuals with conditions, disabilities or abnormalities were treated gives us valuable insights into past societies. Chromosomal aneuploidies, the presence of an abnormal number of copies of the chromosomes, represent the most common large-scale chromosomal abnormalities in human populations. Chromosomal aneuploidies can affect autosomal chromosomes (e.g. Down syndrome) as well as the sex chromosomes (e.g. Klinefelter syndrome), with physical manifestations ranging from mild to severe. While simple to identify genetically, chromosomal aneuploidies are difficult to diagnose from skeletal remains alone, as they present skeletal pathologies consistent with many other conditions. RESULTS: Here we present ChASM (Chromosomal Aneuploidy Screening Methodology), a statistically rigorous Bayesian method for detecting full autosomal and sex chromosomal aneuploidies. The method leverages chromosome-wise read counts and takes into account differences in sequencing methodology, genetic coverage and condition rarity to produce posterior probability estimates for the screening of small and large databases of sequence data. AVAILABILITY AND IMPLEMENTATION: To facilitate the ease of use, ChASM has been implemented in R as the package RChASM. RChASM is available under MIT license on the Comprehensive R Archive Network.

Motivation: The study of ancient genomes can elucidate the evolutionary past. However, analyses are complicated by base-modifications in ancient DNA molecules that result in errors in DNA sequences. These errors are particularly common near the ends of sequences and pose a challenge for genotype calling. Results: I describe an iterative method that estimates genotype frequencies and errors along sequences to allow for accurate genotype calling from ancient sequences. The implementation of this method, called snpAD, performs well on high-coverage ancient data, as shown by simulations and by subsampling the data of a high-coverage Neandertal genome. Although estimates for low-coverage genomes are less accurate, I am able to derive approximate estimates of heterozygosity from several low-coverage Neandertals. These estimates show that low heterozygosity, compared to modern humans, was common among Neandertals. Availability and implementation: The C++ code of snpAD is freely available at http://bioinf.eva.mpg.de/snpAD/. Supplementary information: Supplementary data are available at Bioinformatics online.

We present ABAEnrichment, an R package that tests for expression enrichment in specific brain regions at different developmental stages using expression information gathered from multiple regions of the adult and developing human brain, together with ontologically organized structural information about the brain, both provided by the Allen Brain Atlas. We validate ABAEnrichment by successfully recovering the origin of gene sets identified in specific brain cell-types and developmental stages. AVAILABILITY AND IMPLEMENTATION: ABAEnrichment was implemented as an R package and is available under GPL (≥ 2) from the Bioconductor website (http://bioconductor.org/packages/3.3/bioc/html/ABAEnrichment.html). CONTACTS: [email protected], [email protected] or [email protected] information: Supplementary data are available at Bioinformatics online.

MOTIVATION: Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes. RESULTS: Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.

MOTIVATION: Ontology development and the annotation of biological data using ontologies are time-consuming exercises that currently require input from expert curators. Open, collaborative platforms for biological data annotation enable the wider scientific community to become involved in developing and maintaining such resources. However, this openness raises concerns regarding the quality and correctness of the information added to these knowledge bases. The combination of a collaborative web-based platform with logic-based approaches and Semantic Web technology can be used to address some of these challenges and concerns. RESULTS: We have developed the BOWiki, a web-based system that includes a biological core ontology. The core ontology provides background knowledge about biological types and relations. Against this background, an automated reasoner assesses the consistency of new information added to the knowledge base. The system provides a platform for research communities to integrate information and annotate data collaboratively. AVAILABILITY: The BOWiki and supplementary material is available at http://www.bowiki.net/. The source code is available under the GNU GPL from http://onto.eva.mpg.de/trac/BoWiki.

UNLABELLED: We present a tool suited for searching for many short nucleotide sequences in large databases, allowing for a predefined number of gaps and mismatches. The commandline-driven program implements a non-deterministic automata matching algorithm on a keyword tree of the search strings. Both queries with and without ambiguity codes can be searched. Search time is short for perfect matches, and retrieval time rises exponentially with the number of edits allowed. AVAILABILITY: The C++ source code for PatMaN is distributed under the GNU General Public License and has been tested on the GNU/Linux operating system. It is available from http://bioinf.eva.mpg.de/patman. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Information about these genes is increasingly being captured and organized in ontologies, such as the Gene Ontology. Relationships between the gene sets identified by experimental methods and biological knowledge can be made explicit and used in the interpretation of results. However, it is often difficult to assess the statistical significance of such analyses since many inter-dependent categories are tested simultaneously. RESULTS: We developed the program package FUNC that includes and expands on currently available methods to identify significant associations between gene sets and ontological annotations. Implemented are several tests in particular well suited for genome wide sequence comparisons, estimates of the family-wise error rate, the false discovery rate, a sensitive estimator of the global significance of the results and an algorithm to reduce the complexity of the results. CONCLUSION: FUNC is a versatile and useful tool for the analysis of genome-wide data. It is freely available under the GPL license and also accessible via a web service.