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TreeShrink: Efficient Detection of Outlier Tree Leaves

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Comparative Genomics (RECOMB-CG 2017)

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Abstract

Phylogenetic trees include errors for a variety of reasons. We argue that one way to detect errors is to build a phylogeny with all the data then detect taxa that artificially inflate the tree diameter. We formulate an optimization problem that seeks to find k leaves that can be removed to reduce the tree diameter maximally. We present a polynomial time solution to this “k-shrink” problem. Given this solution, we then use non-parametric statistics to find an outlier set of taxa that have an unexpectedly high impact on the tree diameter. We test our method, TreeShrink, on five biological datasets, and show that it is more conservative than rogue taxon removal using RogueNaRok. When the amount of filtering is controlled, TreeShrink outperforms RogueNaRok in three out of the five datasets, and they tie in another dataset.

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References

  1. Braun, M.J., Clements, J.E., Gonda, M.A.: The visna virus genome: evidence for a hypervariable site in the env gene and sequence homology among lentivirus envelope proteins. J. Virol. 61(12), 4046–4054 (1987)

    Google Scholar 

  2. Hugenholtz, P., Huber, T.: Chimeric 16S rDNA sequences of diverse origin are accumulating in the public databases. Int. J. Syst. Evol. Microbio. 53(1), 289–293 (2003)

    Article  Google Scholar 

  3. Zwickl, D.J., Stein, J.C., Wing, R.A., Ware, D., Sanderson, M.J.: Disentangling methodological and biological sources of gene tree discordance on Oryza (Poaceae) chromosome 3. Syst. Biol. 63(5), 645–659 (2014)

    Article  Google Scholar 

  4. Leaché, A.D., Rannala, B.: The accuracy of species tree estimation under simulation: a comparison of methods. Syst. Biol. 60(2), 126–137 (2011)

    Article  Google Scholar 

  5. Mirarab, S., Bayzid, M.S., Boussau, B., Warnow, T.: Statistical binning enables an accurate coalescent-based estimation of the avian tree. Science 346(6215), 1250463 (2014)

    Article  Google Scholar 

  6. Gatesy, J., Springer, M.S.: PhyloGenet. Anal. at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum. Mol. Phylogenet. Evol. 80, 231–266 (2014)

    Article  Google Scholar 

  7. Arvestad, L., Berglund, A.C., Lagergren, J., Sennblad, B.: Gene tree reconstruction and orthology analysis based on an integrated model for duplications and sequence evolution. In: RECOMB, pp. 326–335. ACM Press, New York (2004)

    Google Scholar 

  8. Akerborg, O., Sennblad, B., Arvestad, L., Lagergren, J.: Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. PNAS 106(14), 5714–5719 (2009)

    Article  Google Scholar 

  9. Szöllősi, G.J., Tannier, E., Daubin, V., Boussau, B.: The inference of gene trees with species trees. Syst. Biol. 64(1), e42–e62 (2014)

    Article  Google Scholar 

  10. Stolzer, M., Lai, H., Xu, M., et al.: Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees. Bioinformatics 28(18), i409–i415 (2012)

    Article  Google Scholar 

  11. Chauve, C., El-Mabrouk, N., Guéguen, L., Semeria, M., Tannier, E.: Duplication, rearrangement and reconciliation: a follow-up 13 years later. In: Chauve, C., El-Mabrouk, N., Tannier, E. (eds.) Models and Algorithms for Genome Evolution. Computational Biology, vol. 19, pp. 47–62. Springer, London (2013). doi:10.1007/978-1-4471-5298-9_4

    Chapter  Google Scholar 

  12. Wu, Y.C., Rasmussen, M.D., Bansal, M.S., Kellis, M.: TreeFix: statistically informed gene tree error correction using species trees. Syst. Biol. 62(1), 110–120 (2013)

    Article  Google Scholar 

  13. Lafond, M., Chauve, C., Dondi, R., El-Mabrouk, N.: Polytomy refinement for the correction of dubious duplications in gene trees. Bioinformatics 30(17), i519–i526 (2014)

    Article  Google Scholar 

  14. Bansal, M.S., Wu, Y.C., Alm, E.J., Kellis, M.: Improved gene tree error correction in the presence of horizontal gene transfer. Bioinformatics 31(8), 1211–1218 (2015)

    Article  Google Scholar 

  15. Tan, G., Muffato, M., Ledergerber, C., et al.: Current methods for automated filtering of multiple sequence alignments frequently worsen single-gene phylogenetic inference. Syst. Biol. 64(5), 778–791 (2015)

    Article  Google Scholar 

  16. Castresana, J.: Selection of conserved blocks from multiple alignments for their use in PhyloGenet. Anal. Mol. Biol. Evol. 17(4), 540–552 (2000)

    Article  Google Scholar 

  17. Capella-Gutiérrez, S., Silla-Martínez, J.M., Gabaldón, T.: trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25(15), 1972–1973 (2009)

    Article  Google Scholar 

  18. Shen, X.X., Hittinger, C.T., Rokas, A.: Studies can be driven by a handful of genes. Nature 1(April), 1–10 (2017)

    Google Scholar 

  19. Krüger, D., Gargas, A.: New measures of topological stability in phylogenetic trees - taking taxon composition into account. Bioinformation 1(8), 327–330 (2006)

    Article  Google Scholar 

  20. Westover, K.M., Rusinko, J.P., Hoin, J., Neal, M.: Rogue taxa phenomenon: a biological companion to simulation analysis. Mol. Phylogenet. Evol. 69(1), 1–3 (2013)

    Article  Google Scholar 

  21. Pattengale, N.D., Swenson, K.M., Moret, B.M.E.: Uncovering hidden phylogenetic consensus. In: Borodovsky, M., Gogarten, J.P., Przytycka, T.M., Rajasekaran, S. (eds.) ISBRA 2010. LNCS, vol. 6053, pp. 128–139. Springer, Heidelberg (2010). doi:10.1007/978-3-642-13078-6_16

    Chapter  Google Scholar 

  22. Aberer, A.J., Krompass, D., Stamatakis, A.: Pruning rogue taxa improves phylogenetic accuracy: an efficient algorithm and webservice. Syst. Biol. 62(1), 162–166 (2013)

    Article  Google Scholar 

  23. Goloboff, P.A., Szumik, C.A.: Identifying unstable taxa: efficient implementation of triplet-based measures of stability, and comparison with Phyutility and RogueNaRok. Mol. Phylogenet. Evol. 88, 93–104 (2015)

    Article  Google Scholar 

  24. Hosner, P.A., Braun, E.L., Kimball, R.T.: Land connectivity changes and global cooling shaped the colonization history and diversification of New World quail (Aves: Galliformes: Odontophoridae). J. Biogeogr. 42, 1883–1895 (2015)

    Article  Google Scholar 

  25. Streicher, J.W., Schulte, J.A., Wiens, J.J.: How should genes and taxa be sampled for phylogenomic analyses with missing data? An empirical study in iguanian lizards. Syst. Biol. 65(1), 128–145 (2016)

    Article  Google Scholar 

  26. Salichos, L., Rokas, A.: Inferring ancient divergences requires genes with strong phylogenetic signals. Nature 497(7449), 327–331 (2013)

    Article  Google Scholar 

  27. Wickett, N.J., Mirarab, S., Nguyen, N., et al.: Phylotranscriptomic analysis of the origin and early diversification of land plants. PNAS 111(45), 4859–4868 (2014)

    Article  Google Scholar 

  28. Bergsten, J.: A review of long-branch attraction. Cladistics 21(2), 163–193 (2005)

    Article  Google Scholar 

  29. Hampl, V., Hug, L., Leigh, J.W., et al.: Phylogenomic analyses support the monophyly of Excavata and resolve relationships among eukaryotic “supergroups”. PNAS 106(10), 3859–3864 (2009)

    Article  Google Scholar 

  30. Song, S., Liu, L., Edwards, S.V., Wu, S.: Resolving conflict in eutherian mammal phylogeny using phylogenomics and the multispecies coalescent model. PNAS 109(37), 14942–14947 (2012)

    Article  Google Scholar 

  31. Silverman, B.: Density estimation for statistics and data analysis. In: Monographs on Statistics and Applied Probability. Chapman & Hall (1986)

    Google Scholar 

  32. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2016)

    Google Scholar 

  33. Mirarab, S., Reaz, R., Bayzid, M.S., et al.: ASTRAL: genome-scale coalescent-based species tree estimation. Bioinformatics 30(17), i541–i548 (2014)

    Article  Google Scholar 

  34. Misof, B., Liu, S., Meusemann, K., et al.: Phylogenomics resolves the timing and pattern of insect evolution. Science 346(6210), 763–767 (2014)

    Article  Google Scholar 

  35. Cannon, J.T., Vellutini, B.C., Smith, J., et al.: Xenacoelomorpha is the sister group to Nephrozoa. Nature 530(7588), 89–93 (2016)

    Article  Google Scholar 

  36. Rouse, G.W., Wilson, N.G., Carvajal, J.I., Vrijenhoek, R.C.: New deep-sea species of Xenoturbella and the position of Xenacoelomorpha. Nature 530(7588), 94–97 (2016)

    Article  Google Scholar 

  37. Philippe, H., Brinkmann, H., Copley, R.R., et al.: Acoelomorph flatworms are deuterostomes related to Xenoturbella. Nature 470(7333), 255–258 (2011)

    Article  Google Scholar 

  38. Mirarab, S., Warnow, T.: ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes. Bioinformatics 31(12), i44–i52 (2015)

    Article  Google Scholar 

  39. Springer, M.S., Gatesy, J.: The gene tree delusion. Mol. Phylogenet. Evol. 94(Part A), 1–33 (2016)

    Article  Google Scholar 

  40. Sukumaran, J., Holder, M.T.: DendroPy: a Python library for phylogenetic computing. Bioinformatics 26(12), 1569–1571 (2010)

    Article  Google Scholar 

  41. Bogdanowicz, D., Giaro, K.: Matching split distance for unrooted binary phylogenetic trees. IEEE/ACM Trans. Comput. Biol. Bioinform. 9(1), 150–160 (2012)

    Article  Google Scholar 

  42. Bogdanowicz, D., Giaro, K., Wróbel, B.: TreeCmp: comparison of trees in polynomial time. Evol. Bioinform. 2012(8), 475–487 (2012)

    Google Scholar 

  43. DeSantis, T.Z., Hugenholtz, P., Larsen, N., et al.: Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72(7), 5069–5072 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the NSF grant IIS-1565862 to SM and UM. Computations were performed on the San Diego Supercomputer Center (SDSC) through XSEDE allocations, which is supported by the NSF grant ACI-1053575.

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Appendices

A Proofs

1.1 A.1 Proof of Proposition 1

We start with a Lemma:

Lemma 1

If (ab) is a diameter pair of t, then for any \(c,d \in L(t)-\{a\}\),

$$ max({\delta }({c},{b}), {\delta }({d},{b})) \ge {\delta }({c},{d}). $$
Fig. 6.
figure 6

Example quartet trees

Proof

Consider the quartet formed by the 4 leaves abcd in t.

Case 1: (Fig. 6a) a and b are on the same side of the quartet:

$${\delta }({a},{b}) \ge {\delta }({a},{d}) \implies {\delta }({m},{b}) \ge {\delta }({m},{d}) \implies {\delta }({c},{m}) + {\delta }({m},{b}) \ge {\delta }({c},{m}) + {\delta }({m},{d})$$
$$ \implies {\delta }({c},{b}) \ge {\delta }({c},{d}) $$

Case 2: (Fig. 6b) Without loss of generality, we assume \({\delta }({n},{c}) \ge {\delta }({n},{d})\). We will prove that \({\delta }({b},{c}) \ge {\delta }({c},{d})\).

We have:

$$ {\delta }({a},{b}) \ge {\delta }({a},{c}) \implies {\delta }({b},{m}) \ge {\delta }({c},{m})$$
$$\implies {\delta }({b},{m}) + {\delta }({n},{c}) \ge {\delta }({c},{m}) + {\delta }({n},{c}) $$
$$\implies {\delta }({b},{m}) + {\delta }({n},{c}) \ge 2{\delta }({n},{c}) $$
$$\implies {\delta }({b},{c}) = {\delta }({b},{m}) + {\delta }({n},{c}) + {\delta }({m},{n}) \ge {\delta }({n},{c}) + {\delta }({n},{d}) = {\delta }({c},{d}) $$

   \(\square \)

We now provide the proof of Proposition 1.

Proof

Consider an arbitrary leaf \(b \in \mathcal {D}(t)-\{a\}\). We prove that \(b \in \mathcal {D}(t\backslash _{a})\).

Case 1: \((a,b) \notin \mathcal {P}(t)\). Because \(b \in \mathcal {D}(t)\), there exists \(c \in \mathcal {D}(t)-\{a\}\) such that (cb) is a diameter pair of \(t\backslash _{a}\). Therefore, \(b \in \mathcal {D}(t\backslash _{a})\).

Case 2: \((a,b) \in \mathcal {P}(t)\). Let (cd) be a diameter-pair of \(t\backslash _{a}\). According to Lemma 1, \(max({\delta }({c},{b}), {\delta }({d},{b})) \ge {\delta }({c},{d})\). Therefore, either (cb) or (db) is a diameter-pair of \(t\backslash _{a}\). Thus, \(b \in \mathcal {D}(t\backslash _{a})\).    \(\square \)

1.2 A.2 Proof of Theorem 1

Proof

We need to prove that a \(\mathcal {R}_k(t)\) is either a reasonable removing set or it is not an optimal removing set. We proceed by contradiction. Assume \(\mathcal {R}_k(t)\) is optimal but not a reasonable removing set. Let \(\mathcal {R}_m(t)\) be the largest reasonable removing set that is a subset of \(\mathcal {R}_k(t)\) (note \(0\le m\le k\)). If \(m = k\), then \(\mathcal {R}_k(t)\) is a reasonable set, contradicting the assumption. For \(m < k\), consider the tree and let \(a_m,b_m\) be its diameter pair. if \(a_m \in \mathcal {R}_k(t)\) or \(b_m \in \mathcal {R}_k(t)\), adding them to \(\mathcal {R}_m(t)\) would generate a reasonable chain of size \(m+1\), contradicting our assumption. If \(a_m \notin \mathcal {R}_k(t)\) and \(b_m \notin \mathcal {R}_k(t)\), all removals after m in \(\mathcal {R}_k(t)\) fail to reduce the diameter, but removing either \(a_m\) or \(b_m\) would reduce the diameter. Thus, \(\mathcal {R}_k(t)\) cannot be optimal, contradicting our assumption.    \(\square \)

1.3 A.3 Proof of Theorem 2

Proof

To remove k leaves from a singly paired tree t that has (ab) as a diameter pair, at least one of a or b has to be removed (or else the diameter never decreases). Thus, three types of reasonable chains exist: those that contain only a, those that contain only b, and those that contain both a and b. Note that after removing a, by Proposition 1, removing b is a reasonable removal (and vice versa), and thus, removing both a and b is always reasonable (in either order).

  • Case 1: \(a\in \mathcal {R}_{k-2}, b\notin \mathcal {R}_{k-2}\): If a reasonable chain has a but not b, by Proposition 1, b is in the diameter set at each step of the chain. Since b by definition is never removed and recalling that the tree is singly paired, at each step, there is only one reasonable removal (whatever taxon is on-diameter in addition to b). Therefore, only one reasonable chain does not include b.

  • Case 2: \(a\notin \mathcal {R}_{k-2}, b\in \mathcal {R}_{k-2}\): Similar to Case 1, one such chain exists.

  • Case 3: \(a\in \mathcal {R}_{k-2}, b\in \mathcal {R}_{k-2}\): In this case, the reasonable removing chain must start with ab or ba. In either ordering, we are left with the same induced tree, and need to remove \(k-2\) more leaves. Therefore, the set of all reasonable removing sets in this case is: .

Combining the three cases together, we have:

Let \(s_{k} = |\mathcal {S}_{k}(t)|\). We have the following recursion:

$$\begin{aligned} s_{k} = {\left\{ \begin{array}{ll} 1, &{} k = 0 \\ 2, &{} k = 1 \\ s_{k-2} + 2 &{} k \ge 2 \end{array}\right. } \end{aligned}$$
(1)

Thus, \(s_{k} = k+1\)    \(\square \)

1.4 A.4 Proof of Proposition 2

Proof

Recall that the record of each internal node keeps track of the most distant leaves below two children of the node. When we remove a, only those nodes on the path from a to the root can have a change in the their record. The first traversal of Algorithm 1 updates the records for those nodes, using simple recursive functions that can be computed in O(1) per node.

According to Proposition 1, \(b \in \mathcal {D}(t\backslash _a)\). Therefore, one of the longest paths in \(t\backslash _a\) must include b; let c be the other taxon. The record of the LCA of c and b, after the update in the first round, will have the value of this longest value. Thus, by checking the updated record for all nodes in the path from b to the root we will find the maximum value. Moreover, when updating the records in the first traversal from a to the root, we have already checked all the nodes from the LCA(ab) to the root. In the second traversal, we check the nodes from b to LCA(ab), completing the search. Each of the two traversals of Algorithm 1 visits at most h nodes and only need constant time operations in each visit. Therefore, the overall time complexity of Algorithm 1 is O(h).    \(\square \)

1.5 A.5 Proof of Theorem 3

First, we prove the following lemmas:

Lemma 2

All the longest paths in any tree have the same midpoint.

Proof

If t has only one diameter pair, then Lemma 2 is trivially correct.

If t has more than one diameter pair, let (ab) and (cd) be two distinct diameter pairs of t and let m be the midpoint of the path between a and b. We prove that m is also the midpoint of the path between c and d, that is m lies on that path between c and d and \({\delta }({m},{c}) = {\delta }({m},{d})\). w.l.o.g, we suppose \({\delta }({m},{c}) \ge {\delta }({m},{d})\).

  • We prove that the path between c and d must pass m; that is, c and d belong to two different subsets in the partition defined by m on \(\mathcal {L}\) (we call elements of the partition a “side”). We prove by contradiction, assuming c and d belong to the same side of m. Then \({\delta }({m},{c}) + {\delta }({m},{d}) > {\delta }({c},{d})\). Also, either a or b must be on a different side from c and d to m (by definition, a and b cannot be on the same side to m). Suppose a is in a different side from c and d to m. Then: \({\delta }({a},{b}) \ge {\delta }({a},{c}) \implies {\delta }({a},{m}) + {\delta }({m},{b}) \ge {\delta }({a},{m}) + {\delta }({m},{c}) \implies {\delta }({m},{b}) \ge {\delta }({m},{c}) \implies {\delta }({m},{a}) \ge {\delta }({m},{c})\). So we have, \({\delta }({a},{c}) = {\delta }({m},{a}) + {\delta }({m},{c}) \ge 2{\delta }({m},{c}) \ge {\delta }({m},{c}) + {\delta }({m},{d}) > {\delta }({c},{d})\); this leads to a contradiction because (cd) is a diameter pair.

  • Prove that \(mc = md\). Suppose \({\delta }({m},{c}) > {\delta }({m},{d})\).

    We have: \(2{\delta }({m},{a}) = 2{\delta }({m},{b}) = {\delta }({a},{b}) = {\delta }({c},{d}) \le {\delta }({m},{c}) + {\delta }({m},{d}) < 2{\delta }({m},{c})\). Therefore: \({\delta }({m},{a}) < {\delta }({m},{c})\) and \({\delta }({m},{b}) < {\delta }({m},{c})\).

    Case 1: c belongs to a different side of a to m. Then, \({\delta }({m},{a}) + {\delta }({m},{c}) = {\delta }({a},{c}) \implies {\delta }({m},{a}) + {\delta }({m},{b})< {\delta }({a},{c}) \implies {\delta }({a},{b}) < {\delta }({a},{c})\). This is a contradiction because (ab) is a diameter pair of t.

    Case 2: c belongs to the same side of a to m. Then c belongs to a different side of b to m. Similar to case 1, in this case we can prove that \({\delta }({a},{b}) < {\delta }({b},{c})\) which also leads to a contradiction.

    Thus, m is the midpoint of the path between c and d.   \(\square \)

This lemma allows us to define some new concepts that are useful in the rest of the proof.

New Definitions: The single midpoint of any tree t partitions the diameter set into disjoint subsets; we call each of those subsets a diameter group of t (if the midpoint is in the middle of the branch, we have two diameter groups; a midpoint coinciding on an internal node would give three or more groups). We call any restriction of t with k leaves removed a k-optimal restricted tree if no other restriction removing k leaves has a lower diameter. We call a tree t k-shrinkable if there exists a k-removing set that strictly reduces its diameter. We call any induced tree on t that has a smaller diameter than t a shrunk tree of t. Note that unless all but one of the diameter groups of a tree t are removed, the tree cannot shrink in diameter. When all but one of the diameter groups of a tree t is removed, we refer to the resulting tree as a minimum shrunk tree of t.

It is easy to see the following lemma.

Lemma 3

For all a and b, \((a,b)\in \mathcal {P}(t)\) if and only if a and b belong to two distinct diameter groups.   \(\square \)

Now we prove a less obvious Lemma.

Lemma 4

If tree t is k-shrinkable, any k-optimal restricted tree \(t^*\) can be induced from one of the minimum shrunk trees of t.

Proof

Because t is k-shrinkable, the diameter of \(t^*\) must be strictly smaller than the diameter of t. Suppose \(t^*\) is not an induced tree of any minimum shrink tree of t; then, t* has at least two leaves from two different diameter groups of t. Based on Lemma 3, \(t^*\) shares with t at least one diameter pair and therefore, has the same diameter as t, which is a contradiction.   \(\square \)

We now turn to the proof of Theorem 3. Recall:

Theorem 3. For any k, any arbitrary pair-restricted k-removing space includes at least one optimal k-removing set.

Proof

If t is not k-shrinkable, any k-removing set is optimal and the result trivially follows. We now focus on a case where t is k-shrinkable.

Suppose t has m diameter groups:

$$D^1=\{d_{1}^{1},d_{2}^{1},\ldots ,d_{p_1}^{1}\},D^2= \{d_{1}^{2},d_{2}^{2},\ldots ,d_{p_2}^{2}\},\ldots ,D^m=\{d_{1}^{m},d_{2}^{m},\ldots ,d_{p_m}^{m}\}.$$

For \(i=1\ldots m\), let \(k^i = |\bigcup _{j\ne i} D_j|\) be the size of all groups except group i, and let \(t^i\) denote the minimum shrunk tree of t that excludes all groups \(D^j, j\ne i\). Let \(k^{p} = \max _i(k^i)\). For the tree t to be k-shrinkable, we need that \(k^i \le k\); thus, \(k \ge k^p\).

To produce any minimum shrunk tree \(t^i\) with \(k^i \le k^p\), we can start from any removal (ab) such that \(a\in D^x\) and \(b\in D^y\) (for \(x\ne y\)), and continue to produce \(t^i\). To see this, note that if \(x \ne y \ne i\), any chain that starts with either a or b and continues to select from any groups other than \(D^i\) will produce the minimum shrunk tree \(t^i\) after \(k^i\) removals. Now, w.l.o.g, consider \(x= i\) and \(y \ne i\). Then, consider the chain that starts by removing y and continues by removals from any group other than \(D^i\). This chain will also produce \(t^i\) after \(k^i\) removals. In other words, each pair-restricted k-removing space of t can produce all the minimum shrunk trees \(t^i\) that have \(k^i \le k\).

Based on Lemma 4, when t is k-shrinkable, at least one of the minimum shrunk trees (say \(t^*_i\)) can induce any k-optimal restricted tree \(t^*\). We also just proved that any pair-restricted space can produce all minimum shrunk trees. Therefore, any arbitrary pair-restricted removing space will include a chain that induces \(t^*_i\) from t and another chain that produces \(t^*\) starting from \(t^*_i\). Thus, the union of the removing sets corresponding to these two chains will produce \(t^*\) and will be part of any arbitrary pair-restricted k-removing space.

B Supplementary Figures

Fig. 7.
figure 7

Alternative implementations of TreeShrink. Using \(\varDelta \) values instead of \(\log \varDelta \) values had no discernible impact on the trajectory, though it did slightly change the results. Fitting kernels on individual genes instead of fitting it on the full set of genes reduced the accuracy, but still was much better than the control random.

Fig. 8.
figure 8

Impact of taxon removal on gene tree discordance. For each of the four biological dataset, we show the reduction in the distance between the species tree and gene trees measured by the MS metric (y-axis) versus the total proportion of the taxa retained in the gene trees after filtering (x-axis). Average delta MS values and standard error bars are shown over all genes for each dataset. A line is drawn between all five points corresponding to each method.

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Mai, U., Mirarab, S. (2017). TreeShrink: Efficient Detection of Outlier Tree Leaves. In: Meidanis, J., Nakhleh, L. (eds) Comparative Genomics. RECOMB-CG 2017. Lecture Notes in Computer Science(), vol 10562. Springer, Cham. https://doi.org/10.1007/978-3-319-67979-2_7

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