Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data.
Triplet ordering preferences are used to perform Monte Carlo sampling of the posterior causal orderings originating from the analysis of gene-expression experiments involving observation as well as, usually few, interventions, like knock-outs. The performance of this sampling approach is compared to...
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0170514&type=printable |
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| author | Alexander K Hartmann Grégory Nuel |
| author_facet | Alexander K Hartmann Grégory Nuel |
| author_sort | Alexander K Hartmann |
| collection | DOAJ |
| description | Triplet ordering preferences are used to perform Monte Carlo sampling of the posterior causal orderings originating from the analysis of gene-expression experiments involving observation as well as, usually few, interventions, like knock-outs. The performance of this sampling approach is compared to a previously used sampling via pairwise ordering preference as well as to the sampling of the full posterior distribution. For a fair comparison, the latter approach is restricted to twice the numerical effort of the triplet-based approach. This is done for artificially generated causal, i.e., directed acyclic graphs (DAGs) and for actual experimental data taken from the ROSETTA challenge. The sampling using the triplets ordering turns out to be superior to both other approaches. |
| format | Article |
| id | doaj-art-fd5561514fbe404abc41bcfb08ceb268 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-fd5561514fbe404abc41bcfb08ceb2682025-08-20T02:03:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01121e017051410.1371/journal.pone.0170514Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data.Alexander K HartmannGrégory NuelTriplet ordering preferences are used to perform Monte Carlo sampling of the posterior causal orderings originating from the analysis of gene-expression experiments involving observation as well as, usually few, interventions, like knock-outs. The performance of this sampling approach is compared to a previously used sampling via pairwise ordering preference as well as to the sampling of the full posterior distribution. For a fair comparison, the latter approach is restricted to twice the numerical effort of the triplet-based approach. This is done for artificially generated causal, i.e., directed acyclic graphs (DAGs) and for actual experimental data taken from the ROSETTA challenge. The sampling using the triplets ordering turns out to be superior to both other approaches.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0170514&type=printable |
| spellingShingle | Alexander K Hartmann Grégory Nuel Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data. PLoS ONE |
| title | Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data. |
| title_full | Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data. |
| title_fullStr | Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data. |
| title_full_unstemmed | Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data. |
| title_short | Using Triplet Ordering Preferences for Estimating Causal Effects in the Analysis of Gene Expression Data. |
| title_sort | using triplet ordering preferences for estimating causal effects in the analysis of gene expression data |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0170514&type=printable |
| work_keys_str_mv | AT alexanderkhartmann usingtripletorderingpreferencesforestimatingcausaleffectsintheanalysisofgeneexpressiondata AT gregorynuel usingtripletorderingpreferencesforestimatingcausaleffectsintheanalysisofgeneexpressiondata |