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T-Coffee Documentation Release Version 13.45.47.Aba98c5

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T-Coffee Documentation

Release Version_13.45.47.aba98c5

Cedric Notredame

Aug 31, 2021

Contents

  • 1
  • T-Coffee Installation

3

1.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.1 Unix/Linux Binaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 MacOS Binaries - Updated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3444566677779

  • 1.1.3
  • Installation From Source/Binaries downloader (Mac OSX/Linux) . . . . . . . . . . . . . . .

1.2 Template based modes: PSI/TM-Coffee and Expresso . . . . . . . . . . . . . . . . . . . . . . . . .

1.2.1 Why do I need BLAST with T-Coffee? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Using a BLAST local version on Unix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Using the EBI BLAST client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.4 Using the NCBI BLAST client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.5 Using another client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3 Troubleshooting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3.1 Third party packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 M-Coffee parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.3 Structural modes (using PDB) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.3.4 R-Coffee associated packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

  • 2
  • Quick Start Regressive Algorithm

11

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Installation from source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3.1 Fast and accurate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3.2 Slower and more accurate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3.3 Very Fast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.4 Regressive flags . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

34
Quick Start Unistrap

15

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.2.1 3.2.2
Produce bootsrap replicates by shuffling sequences and guide tree sister nodes . . . . . . . . 16 Produce bootsrap replicates by shuffling the guide tree sister nodes . . . . . . . . . . . . . . 16

3.2.3 Get list of supported methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 unistrap flags . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Quick Start T-Coffee

19

4.1 Basic Command Lines (or modes) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.1.1 Protein sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

i

4.1.2 DNA sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.1.3 RNA sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.2 Brief Overview of T-Coffee Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2.1 Alignment methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2.1.1 T-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.2.1.2 M-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.2.1.3 Expresso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.2.1.4 R-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.2.1.5 Pro-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.2.2

Evaluation tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4.2.2.1 TCS (MSA evaluation based on consistency) . . . . . . . . . . . . . . . . . . . . . 24 4.2.2.2 iRMSD/APDB (MSA structural evaluation) . . . . . . . . . . . . . . . . . . . . . 24 4.2.2.3 STRIKE (single structure MSA evaluation) . . . . . . . . . . . . . . . . . . . . . . 24

4.2.2.4 T-RMSD (structural clustering) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.3 Tutorial (Practical Examples) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

4.3.1 4.3.2 4.3.3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

  • 5
  • T-Coffee Main Documentation

27

5.1 Before You Start. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

5.1.1 5.1.2 5.1.3

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Prerequisite for using T-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Let’s have a try. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.2 What is T-Coffee ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

5.2.1

What is T-Coffee? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.2.1.1 What does it do? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.2.1.2 What can it align? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.2.1.3 How can I use it? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.2.1.4 Is there an online webserver? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.2.1.5 Is T-Coffee different from ClustalW? . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.2.1.6 Is T-Coffee very accurate? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

5.2.2 What T-Coffee can and cannot do for you ... . . . . . . . . . . . . . . . . . . . . . . . . . 29

5.2.2.1 What T-Coffee can’t do . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.2.2.2 What T-Coffee can do . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5.2.3 How does T-Coffee alignment works? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.3 Preparing Your Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

5.3.1

The reformatting utility: seq_reformat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.3.1.1 General introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5.3.1.2 Modification options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 5.3.1.3 Using a “cache” file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

5.3.1.3.1 5.3.1.3.2 5.3.1.3.3

What is a cache in T-Coffee? . . . . . . . . . . . . . . . . . . . . . . . . 32 Preparing a sequence/alignment cache . . . . . . . . . . . . . . . . . . . 32 Preparing a library cache . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.3.2

Modifying the format of your data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.3.2.1 Keeping/Protecting your sequence names . . . . . . . . . . . . . . . . . . . . . . . 34 5.3.2.2 Changing the sequence format . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 5.3.2.3 Changing the case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

5.3.2.3.1 5.3.2.3.2 5.3.2.3.3

Changing the case of your sequences . . . . . . . . . . . . . . . . . . . . 35 Changing the case of specific residues . . . . . . . . . . . . . . . . . . . 35 Changing the case with a cache . . . . . . . . . . . . . . . . . . . . . . . 35

5.3.2.4 Coloring/Editing residues in an alignment . . . . . . . . . . . . . . . . . . . . . . 36
5.3.2.4.1 5.3.2.4.2

Changing the default colors . . . . . . . . . . . . . . . . . . . . . . . . . 36

Coloring specific types of residues/nucleic acids . . . . . . . . . . . . . . 36

ii

5.3.2.4.3 5.3.2.4.4 5.3.2.4.5
Coloring a specific residue of a specific sequence . . . . . . . . . . . . . 36

Coloring according to the conservation . . . . . . . . . . . . . . . . . . . 37 Coloring an alignment using a cache . . . . . . . . . . . . . . . . . . . . 37

5.3.3

Modifying the data itself. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.3.3.1 Modifiying sequences in your dataset . . . . . . . . . . . . . . . . . . . . . . . . . 37

5.3.3.1.1 5.3.3.1.2 5.3.3.1.3 5.3.3.1.4 5.3.3.1.5 5.3.3.1.6

Converting residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Extracting sequences according to a pattern . . . . . . . . . . . . . . . . 38 Extracting/Removing specific sequences by names . . . . . . . . . . . . 38 Extracting the most informative sequences . . . . . . . . . . . . . . . . . 39 Extracting/Removing sequences with the % identity . . . . . . . . . . . . 39

Chaining important sequences . . . . . . . . . . . . . . . . . . . . . . . 41

5.3.3.2 Modifying columns/blocks in your dataset . . . . . . . . . . . . . . . . . . . . . . 41
5.3.3.2.1 5.3.3.2.2 5.3.3.2.3 5.3.3.2.4

Removing gapped columns . . . . . . . . . . . . . . . . . . . . . . . . . 41 Extracting specific columns . . . . . . . . . . . . . . . . . . . . . . . . . 41 Extracting entire blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Concatenating blocks or MSAs . . . . . . . . . . . . . . . . . . . . . . . 43

5.3.4

Manipulating DNA sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.3.4.1 Translating DNA sequences into protein sequences . . . . . . . . . . . . . . . . . . 43 5.3.4.2 Back-translation with the bona fide DNA sequences . . . . . . . . . . . . . . . . . 43 5.3.4.3 Finding the bona fide sequences for the back-translation . . . . . . . . . . . . . . . 43

5.3.5 Manipulating RNA Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.3.5.1 Producing a Stockholm output: adding predicted secondary structures . . . . . . . 43
5.3.5.1.1 5.3.5.1.2
Producing/Adding a consensus structure . . . . . . . . . . . . . . . . . . 43 Adding a precomputed consensus structure to an alignment . . . . . . . . 44
5.3.5.2 Analyzing a RNAalifold secondary structure prediction . . . . . . . . . . . . . . . 44
5.3.5.2.1 5.3.5.2.2

Visualizing compensatory mutations . . . . . . . . . . . . . . . . . . . . 44 Analyzing matching columns . . . . . . . . . . . . . . . . . . . . . . . . 45
5.3.5.3 Comparing alternative folds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Phylogenetic Trees Manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5.3.6.1 Producing phylogenetic trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 5.3.6.2 Comparing two phylogenetic trees . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.3.6.3 Scanning phylogenetic trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.3.6.4 Pruning phylogenetic trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.3.6.5 Tree Reformatting for MAFFT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Manipulating structure files (PDB) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.3.7.1 Extracting a structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

5.3.7.2 Adapting extract_from_pdb to your own environment . . . . . . . . . . . . . . . . 48
5.3.6 5.3.7

5.4 Aligning Your Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

5.4.1

General comments on alignments and aligners . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.4.1.1 What is a good alignment? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5.4.1.2 The main methods and their scope . . . . . . . . . . . . . . . . . . . . . . . . . . 49

5.4.1.2.1 5.4.1.2.2 5.4.1.2.3

ClustalW is really everywhere... . . . . . . . . . . . . . . . . . . . . . . 49 MAFFT/MUSCLE to align big datasets . . . . . . . . . . . . . . . . . . 50 T-Coffee/ProbCons, slow but accurate !!! . . . . . . . . . . . . . . . . . . 50

5.4.1.3 Choosing the right package (without flipping a coin !) . . . . . . . . . . . . . . . . 50

Protein Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.4.2.1 General considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5.4.2.2 Computing a simple MSA (default T-Coffee) . . . . . . . . . . . . . . . . . . . . . 52 5.4.2.3 Aligning multiple datasets/Combining multiple MSAs . . . . . . . . . . . . . . . . 52 5.4.2.4 Estimating the diversity in your alignment . . . . . . . . . . . . . . . . . . . . . . 53

5.4.2.5 Comparing alternative alignments . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

5.4.2.6 Comparing subsets of alternative alignments . . . . . . . . . . . . . . . . . . . . . 54 5.4.2.7 Modifying the default parameters of T-Coffee . . . . . . . . . . . . . . . . . . . . 55
5.4.2
5.4.2.7.1

Can you guess the optimal parameters? . . . . . . . . . . . . . . . . . . . 55

iii

5.4.2.7.2 5.4.2.7.3 5.4.2.7.4

Changing the substitution matrix . . . . . . . . . . . . . . . . . . . . . . 55 Changing gap penalties . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Aligning (very) large datasets . . . . . . . . . . . . . . . . . . . . . . . . 57

  • 5.4.3
  • Protein sequences using 2D and/or 3D information . . . . . . . . . . . . . . . . . . . . . . 57

5.4.3.1 Using 3D structures: Expresso/3D-Coffee . . . . . . . . . . . . . . . . . . . . . . 57
5.4.3.1.1 5.4.3.1.2 5.4.3.1.3 5.4.3.1.4
Requirements to run Expresso/3D-Coffee . . . . . . . . . . . . . . . . . 57

How does Expresso/3D-Coffee work? . . . . . . . . . . . . . . . . . . . 57 Running Expresso/3D-Coffee . . . . . . . . . . . . . . . . . . . . . . . . 57 Template search paramaters . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.4.3.2 Aligning sequences and structures . . . . . . . . . . . . . . . . . . . . . . . . . . 58

5.4.3.2.1 5.4.3.2.2
Mixing sequence profile and structure templates . . . . . . . . . . . . . . 58 Aligning profile using structural information . . . . . . . . . . . . . . . . 59

5.4.3.3 Using secondary structure predictions . . . . . . . . . . . . . . . . . . . . . . . . . 59

5.4.3.3.1 5.4.3.3.2 5.4.3.3.3 5.4.3.3.4

Single sequence prediction . . . . . . . . . . . . . . . . . . . . . . . . . 59

Incorporation of the prediction in the alignment . . . . . . . . . . . . . . 59 Using other secondary structure predictions . . . . . . . . . . . . . . . . 60

Output of the prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.4.4

RNA sequences using 2D and 3D Structure . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.4.4.1 RNA sequences using 2D structure (R-Coffee) . . . . . . . . . . . . . . . . . . . . 60
5.4.4.1.1 5.4.4.1.2 5.4.4.1.3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

R-Coffee: aligning RNA sequences using secondary structures . . . . . . 61

Improving R-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

5.4.4.2 RNA Sequences using 2D and 3D structures (SARA-Coffee and RSAP-Coffee) . . 61
5.4.4.2.1 5.4.4.2.2 5.4.4.2.3 5.4.4.2.4

Running SARA/RSAP-Coffee . . . . . . . . . . . . . . . . . . . . . . . 61

Estimating the accuracy of an RNA structure based alignment . . . . . . . 62

Installing SARA-Coffee VM . . . . . . . . . . . . . . . . . . . . . . . . 62 Docker image for SARA-Coffee . . . . . . . . . . . . . . . . . . . . . . 63

5.4.5

Aligning DNA sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.4.5.1 Aligning DNA sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

5.4.5.2 Pro-Coffee: Aligning functional DNA regions . . . . . . . . . . . . . . . . . . . . 64

5.4.5.3 Splice variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 5.4.5.4 Noisy coding DNA sequences... . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Using many MSA methods at once . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.4.6.1 Using third party aligner via T-Coffee . . . . . . . . . . . . . . . . . . . . . . . . . 65

5.4.6.2 Using all the methods at the same time: M-Coffee . . . . . . . . . . . . . . . . . . 65 5.4.6.3 Using selected methods to compute your MSA . . . . . . . . . . . . . . . . . . . . 66

Aligning profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.4.7.1 Aligning sequence(s) to profile(s) . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

5.4.7.2 Computing very accurate (but slow) alignments with PSI/TM-Coffee . . . . . . . . 66
5.4.6 5.4.7

5.5 Evaluating Your Alignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

5.5.1

Sequence Based Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.5.1.1 The CORE index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

5.5.1.1.1 5.5.1.1.2

Computing the local CORE index . . . . . . . . . . . . . . . . . . . . . 68

Computing the CORE index of any alignment . . . . . . . . . . . . . . . 68

5.5.1.2 Transitive Consistency Score (TCS) . . . . . . . . . . . . . . . . . . . . . . . . . . 68

5.5.1.2.1 5.5.1.2.2 5.5.1.2.3 5.5.1.2.4 5.5.1.2.5 5.5.1.2.6

Evaluating an existing MSA . . . . . . . . . . . . . . . . . . . . . . . . 68 Filtering unreliable MSA positions . . . . . . . . . . . . . . . . . . . . . 69 Weighting MSA for improved trees . . . . . . . . . . . . . . . . . . . . . 69 Using different libraries for TCS . . . . . . . . . . . . . . . . . . . . . . 70 Working with coding DNA . . . . . . . . . . . . . . . . . . . . . . . . . 70 Summary of the output options . . . . . . . . . . . . . . . . . . . . . . . 71

5.5.2

Structural evaluation of MSAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.5.2.1 APDB/iRMSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

5.5.2.1.1

What is the APDB/iRMSD? . . . . . . . . . . . . . . . . . . . . . . . . 71

iv

5.5.2.1.2 5.5.2.1.3 5.5.2.1.4 5.5.2.1.5
How to efficiently use structural information? . . . . . . . . . . . . . . . 72 Evaluating an alignment with the iRMSD package . . . . . . . . . . . . . 72

Evaluating alternative alignments . . . . . . . . . . . . . . . . . . . . . . 72

DEC - Distance Evolutionnary Conservation with msa2distances . . . . . 73

5.5.2.2 STRIKE: Contact based evaluations . . . . . . . . . . . . . . . . . . . . . . . . . 73

  • Evaluating a MSA according to your own criterion . . . . . . . . . . . . . . . . . . . . . . 74
  • 5.5.3

5.6 Downstream Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

5.6.1

Contact Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
5.6.1.1 Contact Evaluation on proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Clustering/Trees based on protein 3D structures . . . . . . . . . . . . . . . . . . . . . . . . 75

5.6.2.1 Generating a tree based on 3D intramolecular distances conservation . . . . . . . . 75 5.6.2.2 Generating a tree based on contact conservation . . . . . . . . . . . . . . . . . . . 76 5.6.2.3 Visualizing contact/distance conservation . . . . . . . . . . . . . . . . . . . . . . . 77

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