Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants

Predictive algorithms are important tools for translating genomic data into meaningful functional annotations. In this work, we benchmarked the performance of eight prediction methods using a set of strictly pharmacogenetic variants. We first compiled a set of damaging or neutral variants that affec...

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Main Authors:	Chua, Eng Wee, Goh, Chian Siang
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2019
Online Access:	http://journalarticle.ukm.my/14378/ http://journalarticle.ukm.my/14378/ http://journalarticle.ukm.my/14378/1/10%20Eng%20Wee%20Chua.pdf

id	ukm-14378
recordtype	eprints
spelling	ukm-143782020-03-10T02:27:09Z http://journalarticle.ukm.my/14378/ Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants Chua, Eng Wee Goh, Chian Siang Predictive algorithms are important tools for translating genomic data into meaningful functional annotations. In this work, we benchmarked the performance of eight prediction methods using a set of strictly pharmacogenetic variants. We first compiled a set of damaging or neutral variants that affected pharmacogenes from two online databases. We then cross-checked their functional impacts against the predictions given by the chosen tools. Of the eight methods, SIFT (Sorting Intolerant From Tolerant), Mutation Assessor, and CADD (Combined Annotation Dependent Depletion) were the top performers in predicting the functional relevance of a variant. The performance of SIFT surpassed that of CADD despite its much simpler algorithm, correctly identifying 66.91% of the damaging variants and 84.38% of the neutral variants. SIFT assumes that important DNA bases within a gene are conserved and not amenable to substitution. Overall, none of the prediction methods struck a balance between sensitivity and specificity. For instance, we noted that CADD was very sensitive in detecting the damaging variants (89.21%); however, it also mispredicted a large fraction of the neutral variants (43.75%). We then trialled a consensus approach whereby the functional significance of a variant is defined by agreement between at least three prediction methods. The approach performed better than all the tools deployed alone, detecting 84.17% of the deleterious variants and 70.97% of the neutral variants. A prediction method that integrates an assortment of algorithms, each assigned an empirically optimised weighting, may be established in the future for the functional assessment of pharmacogenetic variants. Penerbit Universiti Kebangsaan Malaysia 2019-10 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/14378/1/10%20Eng%20Wee%20Chua.pdf Chua, Eng Wee and Goh, Chian Siang (2019) Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants. Sains Malaysiana, 48 (10). pp. 2151-2159. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid48bil10_2019/KandunganJilid48Bil10_2019.htm
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Predictive algorithms are important tools for translating genomic data into meaningful functional annotations. In this work, we benchmarked the performance of eight prediction methods using a set of strictly pharmacogenetic variants. We first compiled a set of damaging or neutral variants that affected pharmacogenes from two online databases. We then cross-checked their functional impacts against the predictions given by the chosen tools. Of the eight methods, SIFT (Sorting Intolerant From Tolerant), Mutation Assessor, and CADD (Combined Annotation Dependent Depletion) were the top performers in predicting the functional relevance of a variant. The performance of SIFT surpassed that of CADD despite its much simpler algorithm, correctly identifying 66.91% of the damaging variants and 84.38% of the neutral variants. SIFT assumes that important DNA bases within a gene are conserved and not amenable to substitution. Overall, none of the prediction methods struck a balance between sensitivity and specificity. For instance, we noted that CADD was very sensitive in detecting the damaging variants (89.21%); however, it also mispredicted a large fraction of the neutral variants (43.75%). We then trialled a consensus approach whereby the functional significance of a variant is defined by agreement between at least three prediction methods. The approach performed better than all the tools deployed alone, detecting 84.17% of the deleterious variants and 70.97% of the neutral variants. A prediction method that integrates an assortment of algorithms, each assigned an empirically optimised weighting, may be established in the future for the functional assessment of pharmacogenetic variants.
format	Article
author	Chua, Eng Wee Goh, Chian Siang
spellingShingle	Chua, Eng Wee Goh, Chian Siang Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
author_facet	Chua, Eng Wee Goh, Chian Siang
author_sort	Chua, Eng Wee
title	Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
title_short	Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
title_full	Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
title_fullStr	Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
title_full_unstemmed	Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
title_sort	benchmarking in silico tools for the functional assessment of dna variants using a set of strictly pharmacogenetic variants
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2019
url	http://journalarticle.ukm.my/14378/ http://journalarticle.ukm.my/14378/ http://journalarticle.ukm.my/14378/1/10%20Eng%20Wee%20Chua.pdf
first_indexed	2023-09-18T20:06:57Z
last_indexed	2023-09-18T20:06:57Z
_version_	1777407221938782208

Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants

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