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Allows pairwise comparison of sets of gene structure annotations. ParsEval is able to analyze annotations for large eukaryotic genomes. It calculates several statistics that highlight the similarities and differences between the two sets of annotations provided. In comparison to existing methods, ParsEval exhibits a considerable performance improvement, both in terms of runtime and memory consumption. Reports from ParsEval can provide relevant biological insights into the gene structure annotations being compared.

CGL / Comparitive Genomics Library

A suite of measures for annotation management to characterize change to a genome's annotations between releases. CGL provides an easy means to explore, compare, and characterize genome annotations, allowing users to ask and answer significant biological questions about genome-annotations without becoming bogged down in tangential programming issues. CGL simplifies the task of writing scripts to compare genome annotations to one another. Genome annotations comprise an invaluable resource for such studies because they describe the essential parts of a gene and their relationships to one another.

Annotation issues

An inference system to check for violations of constraints in gene ontology (GO) annotations. Annotation issues automatically finds inconsistencies between the implicit taxon specificity of GO classes and the species of origin of the annotated gene products. It includes an engine to calculate the link between any given class in the GO and a taxonomic group. Using this system, inconsistencies are automatically detected and passed on to curators for correction. Annotation issues also indicates that there is no restriction on using the GO class for annotation of gene products from any taxonomic group outside of the one mentioned. The feedback generated from the described taxon checking system has benefited both ontology development and annotation in the GO Consortium.


Analyzes the performance of gene annotation systems. Eval provides summaries and graphical distributions for many descriptive statistics about any set of annotations, regardless of their source. It also compares sets of predictions to standard annotations and to one another. Eval can generate a wide range of statistics showing the similarities and differences between a standard annotation set and a prediction set. Eval can also determine the similarities and differences among multiple annotation sets and extract subsets of genes that meet specific criteria for further analysis.

ACS / Annotation Confidence Score

An annotation quality scoring scheme to reduce the cost for microbial genomes annotation. ACS is computed by combining sequence and textual annotation similarity using a modified version of a logistic curve. Extensive experiments with many different reference genome sets demonstrated that ACS was effective to denote the annotation quality for reference genomes of various phylogeny and for varying number of genomes. ACS also can handle many issues in textual annotations such as use of abbreviations and synonyms.