Wednesday, November 28, 2012

Phylogenetic Tree Mega Table

Introduction

Here we present the summary of our work related with phylogenetic tree creation and visualization of Fungi data. The experiments were carried out primarily on two data sets, which we name as Fungi 200 and Fungi 2133. Details of these data sets are as follows.

Fungi 200

Fungi 2133

Note on 126 centers:
Originally we had 7 mega-regions in million sequence clustering project and they had a total of 140 clusters. Each cluster was represented by three center sequences of which were 126 is picked as the best.

Links

Following are links to previous posts on listed topics.
  1. The 200 sequence set without tree can be found here. The 2133 sequence set without tree can be found here.
  2. A description on tree generation methods is available here. 
  3. Tree quality comparisons of edge sum and correlation are available here.
  4. Heatmap comparisons,
    • pairwise edge sum distance versus other distance measures for leaf nodes is available here.
    • pairwise 10D, 3D, and SWG PID distances for leaf nodes is available here.
    • pairwise normalized score distance measures versus SWG PID is available here.
    • pairwise distance from multiple sequence alignment versus pairwise local alignment is available here.
  5. Robinson-Foulds metric for trees is available here. (summary of this given below as well)

Column Name Explanation

  1. Sequence Set: The two sequence sets as given above.
  2. Tree Generation Method: Multiple Sequence Alignment includes Clustal Omega, Clustal W2 and Muscle; Tree Generation includes FastTree, Raxml, Ninja and Neighbor Joining. Neighbor Joining is our implementation of method used in Ninja.
  3. Euclidean Mapping (Interpolation Method): Define leaf nodes as the sample set and internal nodes as out-of-sample set. Use leaf node positions in 3D or 10D from MDS. Calculate internal node positions in 3D or 10D respectively by "neighbor joining" formulae in wikipedia. However, tree itself is NOT defined necessarily by neighborhood joining but rather using the Tree Generation Method in previous column. Note that either Internal Node Interpolation and Full 3D map are used in Spherical Phylogram in following column.
    • Internal Node Interpolation (MI-MDS) was from Majorizing Iterative MDS method: The leaf nodes are fixed from basic MDS on them. Each node position has position calculated iteratively as it is added to the sample.
    • Full 3D map uses a full MDS for whole sample but fixes the leaf nodes at positions from their MDS (i.e. in same positions as Internal Node Interpolation). This gives improved results as all internal node mapped positions are varied simultaneously subject to distance matrix.
  4. Edge Sum: edge sum is the sum of all the edges' lengths, as in 3D, 10D using Euclidean mapping mentioned above.
    • Calculate tree by method defined in "Tree Generation Method" column and then calculate edge sum by one of three methods defined below. Note each method projects tree to a Euclidean space and uses Neighborhood Joining formulae for distances
      • 3D (3D) means instantiate tree in 3D and calculate edge sum in 3D, too;
      • 10D (10D) means instantiate tree in 10D and calculate edge sum in 10D, too;
      • 10D (3D) means instantiate tree in 10D and calculate edge sum in 3D after mapping 10D tree into 3D by MDS as described above.
  5. Stress: same definition as in dimension reduction techniques, calculate the error between target dimension Euclidean pairwise distance matrix to original dimension Eculidean pairwise distance matrix. In our particular calculation, it's the error from 10D to 3D dimension reduction, that error between target 3D and original 10D.
  6. Correlation: Simple correlation between leaf sum from newick file (each nodes' contains the distance from it to its direct parent) and original pid distance matrix / 3D plot distance matrix.
  7. Plots: Spherical is short for Spherical Phylogram, where it's similar to Circular Phylogram but also consider preserving the correlations among original sequences, the internal nodes are calculated using interpolation; Cuboid is short for Cuboid Cladogram, it's same as for Rectangular Cladogram, but in 3D. The internal nodes are NOT calculated by interpolation, but rather the middle of each pair of it's direct children; Rectangle is short for Rectangular Cladogram, where is generated using Dendroscope.
  8. Heatmap
    • Edgesum (newick) Vs Original PID compares the correlation of edge sum values versus original PID distance. More information is available at http://salsafungiphy.blogspot.com/2012/11/tree-distance-heatmaps.html
    • MI-MDS Vs Full MDS Mapping compares the correlation of pairwise node distances in trees built from internal node interpolation versus full 3D map.
    • MSA Strict PIDNG Vs SWG PID compares the computed percent identity excluding gaps from multiple sequence alignment versus pairwise Smith-Waterman percent identity distance. Only A, C, T, G characters are considered as the alphabet when computing PIDNG. See more information in http://salsafungiphy.blogspot.com/2012/10/pairwise-distances-from-multiple.html
    • MSA Full PIDNG Vs SWG PID similar to the previous column except A, C, M, G, R, S, V, T, W, Y, H, K, D, B, N characters are considered as the alphabet for PIDNG calculation. See more in http://salsafungiphy.blogspot.com/2012/10/pairwise-distances-from-multiple.html
  9. 2D View: It's selected screen shot from the 3D plots (in previous column) of Spherical Phylogram or Cuboid Cladogram (made using screen shot feature of 3D viewer Plotviz running on 3D plots in previous column) plus 2D rectangular cladogram in pdf format.

    10. Mega Information Table for PhyloTree Project
    Sequence Set Tree Generation Method Euclidean Mapping Edge Sum Stress
    10D (3D)    		 Correlation
    Regular Tree    		 Heat Map Plots 2D View
    3D (3D) 10D (10D) 10D (3D) With Original Pid With 3D MDS Map Edge Sum (Newick) vs Origin PID MI-MDS vs
    Full MDS Mapping    		 MSA Strict PIDNG vs
    SWG PID    		 MSA Full PIDNG vs
    SWG PID    		 Rectangular Cladogram Cuboid Cladogram Spherical Phylogram
    126 + 74 (200) sequences
    Edge Sum Comparison Figure    		 1. Clustal Omega FastTree Internal Node Interpolation 10.02 13.26 15.01 0.0264 -- -- Spherical
    Cuboid    		 Rectangle
    Full 3D Map -- 11.29 0.0204
    2. Clustal Omega Raxml Internal Node Interpolation 11.33 14.62 16.15 0.0247 0.79 0.749 Spherical
    Cuboid    		 Rectangle  
    Full 3D Map -- 13.05 0.02
    3. Clustal W2 FastTree Internal Node Interpolation 11.16 14.68 16.67 0.0277 -- -- Spherical 
    Cuboid    		 Rectangle  
    Full 3D Map -- 13.4 0.0205
    4. Clustal W2 Raxml Internal Node Interpolation 11.99 15.08 16.17 0.025 0.825 0.78 Spherical 
    Cuboid    		 Rectangle  
    Full 3D Map -- 13.69 0.0201
    5. Muscle FastTree Internal Node Interpolation 10.61 13.8 15.79 0.0274 -- --  Spherical 
    Cuboid    		 Rectangle  
    Full 3D Map -- 12.31 0.0202
    6. Muscle Raxml Internal Node Interpolation 10.90 14.67 16.44 0.027 0.823 0.775 Spherical 
    Cuboid    		 Rectangle  
    Full 3D Map
    		-- 12.95 0.0202
    7. Neighbor Joining 3D Internal Node Interpolation 7.32 13.35 -- -- -- -- n/a n/a Spherical --
    Full 3D Map 7.33 -- -- --
    8. Ninja 3D plot Internal Node Interpolation 7.36 12.92 14.51 0.0268 0.787 0.774 n/a n/a Spherical
    Cuboid    		 Rectangle  
    Full 3D Map -- 10.04 0.0198
    9. Neighbor Joining 10D Internal Node Interpolation 9.40 11.42 13.98 0.0285 -- -- n/a n/a Spherical --
    Full 3D Map -- 9.9 0.0202
    10. Ninja 10D plot Internal Node Interpolation 8.65 12.13 14.99 0.0283 0.906 0.834 n/a n/a  Spherical 
    Cuboid    		 Rectangle  
    Full 3D Map -- 10.47 0.0207
    11. Ninja Original Pid Internal Node Interpolation 9.74 13.03 15.11 0.0273 0.925 0.855 n/a n/a  Spherical
    Cuboid    		 Rectangle  

    Full 3D Map    		 -- 11.67 0.0203
    126 + 74 + 988 + 945 (2133) sequences
    Edge Sum Comparison Figure    		 A. Clustal Omega 1 iter Raxml Internal Node Interpolation 67.95 91.31 99.9 0.025 0.138 0.145
    		Spherical 
    Cuboid

    Full 3D Map -- 90.76 0.0229
    B. Clustal Omega 1 iter FastTree Internal Node Interpolation 71.11
    		104.65 -- -- Same as A Same as A Spherical
    Cuboid
    Full 3D Map --
    C. Clustal Omega Anna Raxml Internal Node Interpolation 68.34 93.91 102.23 0.025 0.679 0.714  Spherical 
    Cuboid
    Full 3D Map -- 93.18 0.0226
    D. Clustal Omega 10 iter Raxml Internal Node Interpolation 63.51 82.1 96.95 0.0262 0.272 0.284
    		Spherical 
    Cuboid    		 Rectangle
    Full 3D Map -- 82.25 0.0232
    E. Clustal Omega 20 iter Raxml Internal Node Interpolation 58.84 81.09 93.64 0.0252 0.275 0.288
    		Spherical 
    Cuboid    		 Rectangle
    Full 3D Map -- 80.88 0.0229
    F. Muscle 2 iter Raxml Internal Node Interpolation 84.23 105.52 113.82 0.0255 0.422 0.451
    		Spherical 
    Cuboid    		 Rectangle
    Full 3D Map -- 103.03 0.0229
    G. Neighbor Joining 3D Internal Node Interpolation 26.59 71.89 -- -- -- -- n/a n/a Spherical --
    Full 3D Map -- -- --
    H. Ninja 3D plot Internal Node Interpolation 27.59 72.12 86.45 0.0268 0.519 0.575 n/a n/a Spherical
    Cuboid    		 Rectangle
    Full 3D Map -- 66.61 0.023
    I. Neighbor Joining 10D Internal Node Interpolation 39.85 52.56 81.68 0.028 -- -- n/a n/a Spherical --
    Full 3D Map -- 61.16 0.0233
    J. Ninja 10D transform Internal Node Interpolation 40.33 58.52 82.23 0.0264 0.728 0.781 n/a n/a Spherical
    Cuboid    		 Rectangle
    Full 3D Map -- 63.41 0.0233
    K. Ninja Original Pid Internal Node Interpolation 84.21 108.51 114.85 0.0247 0.614 0.605 n/a n/a Spherical
    Cuboid    		 Rectangle
    Full 3D Map -- 106.83 0.0224

    Distance Correlation with Original PID
    3D mapping 10D mapping
    200 Sequences 0.907 0.982
    2133 Sequences 0.804 0.885

    Robinson-Foulds Metric

  • Fungi 2133
    • Note. We have made the Ninja 10D transform tree (J) based on data from two MDS programs to verify they agree with each other. The one mentioned in the above table uses the 10 dimensional coordinates generated for each leaf node of the tree using a deterministic annealed (DA) SMACOF MDS program. We have also produced 10 dimensional coordinates for the leaf nodes using a Chisquared MDS program. The tree J is created using Ninja by giving the 10 dimensional Euclidean pairwise distances of leaf nodes. The tree based on former MDS is named as J SMACOF MDS and the other as J Chisq MDS in the below Robinson-Foulds metric.

Reference:
  • Yang Ruan, Geoffrey House, Saliya Ekanayake, Ursel Schütte, James D. Bever, Haixu Tang, Geoffrey Fox. Integration of Clustering and Multidimensional Scaling to Determine Phylogenetic Trees as Spherical Phylograms Visualized in 3 Dimensions. Proceedings of C4Bio 2014 of IEEE/ACM CCGrid 2014, Chicago, USA, May 26-29, 2014.
  • Yang Ruan, Geoffrey Fox. A Robust and Scalable Solution for Interpolative Multidimensional Scaling with Weighting. Proceedings of IEEE eScience 2013, Beijing, China, Oct. 22-Oct. 25, 2013. (Best Student Innovation Award)
  • Yang Ruan, Saliya Ekanayake, Mina Rho, Haixu Tang, Seung-Hee Bae, Judy Qiu, Geoffrey Fox. DACIDR: Deterministic Annealed Clustering with Interpolative Dimension Reduction using a Large Collection of 16S rRNA Sequences. Proceedings of ACM-BCB 2012, Orlando, Florida, ACM, Oct. 7-Oct. 10, 2012.
  • Yang Ruan, Zhenhua Guo, Yuduo Zhou, Judy Qiu, Geoffrey Fox. HyMR: a Hybrid MapReduce Workflow System. Proceedings of ECMLS’12 of ACM HPDC 2012, Delft, Netherlands, ACM, Jun. 18-Jun. 22, 2012
  • Adam Hughes, Yang Ruan, Saliya Ekanayake, Seung-Hee Bae, Qunfeng Dong, Mina Rho, Judy Qiu, Geoffrey Fox. Interpolative Multidimensional Scaling Techniques for the Identification of Clusters in Very Large Sequence Sets, BMC Bioinformatics 2012, 13(Suppl 2):S9.
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