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LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00003425naa a2200361 4500
001oai:DiVA.org:uu-240011
003SwePub
008150105s2014 | |||||||||||000 ||eng|
024a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-2400112 URI
024a https://doi.org/10.1371/journal.pone.01111122 DOI
040 a (SwePub)uu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
100a Akhtar, Malik N.4 aut
2451 0a Accurate Assignment of Significance to Neuropeptide Identifications Using Monte Carlo K-Permuted Decoy Databases
264 c 2014-10-17
264 1b Public Library of Science (PLoS),c 2014
338 a electronic2 rdacarrier
520 a In support of accurate neuropeptide identification in mass spectrometry experiments, novel Monte Carlo permutation testing was used to compute significance values. Testing was based on k-permuted decoy databases, where k denotes the number of permutations. These databases were integrated with a range of peptide identification indicators from three popular open-source database search software (OMSSA, Crux, and X! Tandem) to assess the statistical significance of neuropeptide spectra matches. Significance p-values were computed as the fraction of the sequences in the database with match indicator value better than or equal to the true target spectra. When applied to a test-bed of all known manually annotated mouse neuropeptides, permutation tests with k-permuted decoy databases identified up to 100% of the neuropeptides at p-value < 10(-5). The permutation test p-values using hyperscore (X! Tandem), E-value (OMSSA) and Sp score (Crux) match indicators outperformed all other match indicators. The robust performance to detect peptides of the intuitive indicator "number of matched ions between the experimental and theoretical spectra" highlights the importance of considering this indicator when the p-value was borderline significant. Our findings suggest permutation decoy databases of size 1x10(5) are adequate to accurately detect neuropeptides and this can be exploited to increase the speed of the search. The straightforward Monte Carlo permutation testing (comparable to a zero order Markov model) can be easily combined with existing peptide identification software to enable accurate and effective neuropeptide detection. The source code is available at http://stagbeetle.animal.uiuc.edu/pepshop/MSMSpermutationtesting.
650 7a NATURVETENSKAPx Kemi0 (SwePub)1042 hsv//swe
650 7a NATURAL SCIENCESx Chemical Sciences0 (SwePub)1042 hsv//eng
700a Southey, Bruce R.4 aut
700a Andrén, Per E.u Uppsala universitet,Institutionen för farmaceutisk biovetenskap4 aut0 (Swepub:uu)perandre
700a Sweedler, Jonathan V.4 aut
700a Rodriguez-Zas, Sandra L.4 aut
710a Uppsala universitetb Institutionen för farmaceutisk biovetenskap4 org
773t PLOS ONEd : Public Library of Science (PLoS)g 9:10, s. e111112-q 9:10<e111112-x 1932-6203
856u https://uu.diva-portal.org/smash/get/diva2:775892/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
856u https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0111112&type=printable
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-240011
8564 8u https://doi.org/10.1371/journal.pone.0111112

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Akhtar, Malik N.
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