ProPhylER Dataflow and Analysis Pipeline IV
Release
ProPhylER 1.0 is live now.
News
January 5 2010
The ProPhylER paper is now published in Genome Research
March 12 2010
Searching by name is now supported on the search page
March 12 2010
Searching with hg 18 coordinates for evaluating coding SNPs is now supported
Contacts
prophyler [at] prophyler.org
arend [at] stanford.edu
Resource Links
Ensembl
Uniprot
PDB
WuBlast
Probcons
Semphy
Jmol
Java
Other Links
Sidow Lab
Stanford Pathology Dept
Stanford Genetics Dept
Stanford School of Medicine
Funded by
3. From Alignments and Trees to Profiles, Constrained
Regions, and MAPP Scores
Having obtained alignments and trees from the previous step, ProPhylER now produces physicochemical profiles as well as predictive analyses of constraint and mutation impact.
BranchManager, by a statistical procedure described in this paper, generates tree-based weights for each sequence in the alignment. These weights describe the fraction of the evolutionary information each sequence contributes to the total information in the alignment. They are used by the GreaseMonkey in merging hydropathy, hydrophobic moment, and other physicochemical calculations obtained for each sequence, into a single profile that is the summary profile for the entire alignment. Such a summary contains more information than the profile for a single sequence, and captures the physicochmical characteristics of the primary sequence of the protein throughout its evolution.
RatePlotter uses a moving windows analysis in conjunction with the tree to calculate local evolutionary rates across the length of the alignment. Evolutionarily Constrained Regions (ECRs) are then inferred from that rate profile, as described in this paper. Since its publication, we have considerably refined the algorithms and implemented these refinements in ProPhylER.
MAPP (Multivariate Analysis of Polymorphism) is the program that calculates impact scores for each possible substitution for each column in the alignment. MAPP is described in this paper.
To thoroughly understand MAPP Scores, Constraint Profiles, and Plots of Physicochemical Properties, visit the Help pages where the science behind the analyses and the ProPhylER Interface, which displays the results of the analyses, are explained in detail.
Go back to Dataflow 2: From Clusters to Alignments and Trees
Go back to Dataflow 1: From Individual Protein Sequences to Clusters of Close Homologs
Go back to Dataflow overview
Last updated 8/25/08