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FragIdent – Automatic identification and characterisation of cDNA-fragments
BACKGROUND: Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672089/ https://www.ncbi.nlm.nih.gov/pubmed/19254371 http://dx.doi.org/10.1186/1471-2164-10-95 |
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author | Seelow, Dominik Goehler, Heike Hoffmann, Katrin |
author_facet | Seelow, Dominik Goehler, Heike Hoffmann, Katrin |
author_sort | Seelow, Dominik |
collection | PubMed |
description | BACKGROUND: Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available. RESULTS: Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs) within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones. CONCLUSION: We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at . |
format | Text |
id | pubmed-2672089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26720892009-04-23 FragIdent – Automatic identification and characterisation of cDNA-fragments Seelow, Dominik Goehler, Heike Hoffmann, Katrin BMC Genomics Software BACKGROUND: Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available. RESULTS: Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs) within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones. CONCLUSION: We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at . BioMed Central 2009-03-02 /pmc/articles/PMC2672089/ /pubmed/19254371 http://dx.doi.org/10.1186/1471-2164-10-95 Text en Copyright © 2009 Seelow et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Seelow, Dominik Goehler, Heike Hoffmann, Katrin FragIdent – Automatic identification and characterisation of cDNA-fragments |
title | FragIdent – Automatic identification and characterisation of cDNA-fragments |
title_full | FragIdent – Automatic identification and characterisation of cDNA-fragments |
title_fullStr | FragIdent – Automatic identification and characterisation of cDNA-fragments |
title_full_unstemmed | FragIdent – Automatic identification and characterisation of cDNA-fragments |
title_short | FragIdent – Automatic identification and characterisation of cDNA-fragments |
title_sort | fragident – automatic identification and characterisation of cdna-fragments |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672089/ https://www.ncbi.nlm.nih.gov/pubmed/19254371 http://dx.doi.org/10.1186/1471-2164-10-95 |
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