Pseudogenes are segments of DNA that have been duplicated and mutated to lost some functionality relative to a complete gene. Pseudogenes can usually be characterized by a combination of homology to a known gene and loss of some functionality. High-throughput sequencing has led to identification of many pseudogenes using gene prediction techniques. Pseudogene detection software tools are used to identify and annotate pseudogenes sequences from genomes.
Allows users to identify pseudogenes sequences from genomes. PseudoPipe principally focuses on pseudogenes unable to be translated into proteins and can provide a complete annotation of the pseudogenes detected in the studied genome including chromosomal location, nucleotide sequences, name and sequence of the parent gene and alignment of the pseudogene with the functional gene.
Makes the annotation of novel plant genomes tractable for small groups with limited bioinformatics experience and resources, and faster and more transparent for large groups with more experience and resources. The MAKER-P pipeline generates species-specific repeat libraries, as well as structural annotations of protein coding genes, non-coding RNAs, and pseudogenes.
Permits pseudogene annotation and orthologous assignments between reference genomes. DFAST follows two main steps: structural annotation for predicting biological features such as coding data sequences (CDSs), RNAs, and clustered regularly interspaced short palindromic repeats (CRISPRs); and functional annotation for inferring protein functions of predicted CDSs. It can be customized by users in the standalone version.
Intends to identify processed pseudogenes that have been incorporated into gene models in any mammalian genome annotation. PPFINDER combines two different approaches: intron location method and conserved synteny method. The software also permits to improve gene prediction by masking genome sequence.
Predicts pattern-based human gene structure. FGENES is a web application running on the Softberry platform and exploits pattern recognition of diverse types of promoter, exons and polyA signals. Dynamic programming can be found by the combination of these features and a set of gene models is built along given sequence.
Performs searches for pseudogenes among any pair of genome sequences. Psi-Fi can improve gene recognition and annotation by identifying annotated genes, by detecting pseudogenes in unannotated regions, and by discovering potentially functional open reading frames (ORFs). This solution was utilized for recovering pseudogene inventories in sequenced members of the Escherichia coli or Shigella clade.
Identifies non-reference processed pseudogene insertions from discordant read pair mappings. GRIPper manages to find these insertions via paired-end whole-genome sequence data. This software is suitable with data set for Illumina reads. It allows users to analyze human genome but can be adapted to another species with some configuration.