gaqib.blogg.se - Viewer for clustal .aln files for mac

All T-Coffee commands indicated with a tag “$$:” are currently up and running just copy/paste these commands from the documentation (without the tag “$$:”) to your terminal provided you previously downloaded the example files. For now you can find all these files on our github repository for now: example files however in the future they will be included in the T-Coffee distribution (~/tcoffee/Version…/examples/). All along this documentation, we expect you to use Unix-like shell commands running on prepared example files we have created. This manual is made to help you discover (nearly) all subtleties of T-Coffee, from default applications to sophisticated ones.

Modifying the parameters of INTERNAL/EXTERNAL methods.

What are the methods already integrated in T-Coffee?.

Generating a structural tree with support values.

Evaluating clustering capacities (under maintenance…).

Visualizing contact/distance conservation.

Generating a tree based on contact conservation.

Generating a tree based on 3D intramolecular distances conservation.

Clustering/Trees based on protein 3D structures.

Evaluating a MSA according to your own criterion.

Pro-Coffee: Aligning functional DNA regions.

Using 3D structures: Expresso/3D-Coffee.

Using protein 2D/3D structural information.

Computing very accurate (but slow) alignments with PSI/TM-Coffee.

Using selected methods to compute your MSA.

Using all the methods at the same time: M-Coffee.

Aligning (very) large alignments with T-Coffee.

Aligning (very) large datasets with MAFFT.

Aligning (very) large datasets with MUSCLE.

Modifying the default parameters of T-Coffee.

Comparing subsets of alternative alignments.

Estimating the diversity in your alignment.

Aligning multiple datasets/Combining multiple MSAs.

Computing a simple MSA (default T-Coffee).

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

General comments on alignments and aligners.

Adapting extract_from_pdb to your own environment.

Analyzing a RNAalifold secondary structure prediction.

Producing a Stockholm output: adding predicted secondary structures.

Finding the bona fide sequences for the back-translation.

Back-translation with the bona fide DNA sequences.

Translating DNA sequences into protein sequences.Modifying columns/blocks in your dataset.Coloring/Editing residues in an alignment.What T-Coffee can and cannot do for you ….