Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Topological conﬂicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conﬂicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conﬂicting resolutions. When the source trees host a signiﬁcant number of topological conﬂicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees. Results: To overcome this problem,  propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly diﬀers among source trees or for which insuﬃcient information is provided.  detail a variant of the PhySIC veto method called PhySIC IST that can infer non-plenary supertrees. PhySIC IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally,  propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that signiﬁcantly conﬂict with other source trees. Combining STC with a veto method allows an explicit trade-oﬀ beten veto and liberal approaches, tuned by a single parameter. Performing large-scale simulations,  observe that STC+PhySIC IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the ll-known MRP method. Two biological case studies on animals conﬁrm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC IST provides ll-resolved supertrees agreeing with current knowledge in systematics. Conclusions: The paper introduces and tests two new methodologies, PhySIC IST and STC, that demonstrate the interest in inferring non-plenary supertrees as ll as preprocessing the source trees. An implementation of the methods is available at: http://www.atgc-montpellier.fr/physic ist/.
['Celine Scornavacca', 'Vincent Berry', 'Vincent Lefort', 'Emmanuel J. P. Douzery', 'Vincent Ranwez']
I am writing a research paper on a idea PhySIC_IST: cleaning source trees to infer more informative supertrees
[{"from": "human", "value": "I am writing a research paper on a idea PhySIC_IST: cleaning source trees to infer more informative supertrees"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Topological con\ufb02icts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological con\ufb02icts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all con\ufb02icting resolutions. When the source trees host a signi\ufb01cant number of topological con\ufb02icts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees. Results: To overcome this problem,  propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly di\ufb00ers among source trees or for which insu\ufb03cient information is provided.  detail a variant of the PhySIC veto method called PhySIC IST that can infer non-plenary supertrees. PhySIC IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally,  propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that signi\ufb01cantly con\ufb02ict with other source trees. Combining STC with a veto method allows an explicit trade-o\ufb00 beten veto and liberal approaches, tuned by a single parameter. Performing large-scale simulations,  observe that STC+PhySIC IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the ll-known MRP method. Two biological case studies on animals con\ufb01rm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC IST provides ll-resolved supertrees agreeing with current knowledge in systematics. Conclusions: The paper introduces and tests two new methodologies, PhySIC IST and STC, that demonstrate the interest in inferring non-plenary supertrees as ll as preprocessing the source trees. An implementation of the methods is available at: http://www.atgc-montpellier.fr/physic ist/."}]