front 1 Consensus approach | back 1 where they all agree - meta analyses topology composed of different formal analyses with or without some sort of formal analysis. allow us to combine results from incompatible data sets supertree methods are all consensus tree methods |
front 2 Total evidence approach | back 2 take all the data and make a tree |
front 3 Why did people first start creating super trees? | back 3 1 - the unwieldiness of analyses, gets harder to work with bigger data sets 2- like to summarize what has already been done, more formal way to summarize analyses |
front 4 Supertree approach | back 4 divide and conquer |
front 5 priori super tree approach | back 5 no data |
front 6 Posteriori -ad hoc approach | back 6 after the fact |
front 7 - | back 7 representative of major groups |
front 8 supertrees | back 8 Tree we put together with seperate analyses and reach a consensus, what is the most likely arrangement of species. |
front 9 Informal supertree | back 9 "cut and paste" kind of know from other studies how some species are related, paste it with what is know from other species and groups. no objective analysis that occurs can be an issue if conflicting subtrees |
front 10 Formal supetree | back 10 secondary analysis to make connected tree. allow us to combine results from incompatible data sets meta analysis - take raw data and synthesize into distance data, analysis done on secondary data set. rather than relying on primary data set, uses secondary data. confounded (?) |
front 11 Two processes used to make formal supertrees | back 11 AGREEMENT AND OPTIMIZATION via matrix representation |
front 12 Agreement | back 12 making a consensus tree, put a number on what % of trees define those relationships |
front 13 Optimization | back 13 make secondary matrix, separate analyses that uses the data in a secondary matrix that summarizes all of the trees (1) matrix representation - make a second data set that synthesizes our - one. |
front 14 Criticisms of supertree methods | back 14 no primary data, no signal enhancement - reducing noise and enhancing signal prescende of clades (novel clades) in a super tree that weren't present in previous. sticks two things together that weren't related before inadvertent replication of source data. its a meta analysis- an analysis of previous analyses without collecting data. (reusing our data, replicate source data, giving extra weight to relationship ?) |
front 15 Two methodologies taken with this newer approach | back 15 Disk covering method biclique method |
front 16 Disk covering method | back 16 use an estimate of rough relationships to create separate analyses and use a supertree to put it together. collect new data. if we have a rough estimate of relationships, we come up with areas that have some overlap, better fit when putting back together. priori supertree approach (?) |
front 17 Biclique method | back 17 find large data sets and put them together in sequence analyses that is based on the data. "divide and conquer" approach. uses old data put together a matrix that represents different groups, identify areas with large overlaps, represents one analysis we could do, separate analyses can be done, allow us to identify good data sets that could be put together and ones that identify diversity (?) posteriori (ad hoc) (?) |