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GibbsCluster-2.0 Server

Simultaneous alignment and clustering of peptide data

View the version history of this server. All previous versions are available online, for comparison and reference.

GibbsCluster is a server for unsupervised alignment and clustering of peptide sequences. The program takes as input a list of peptide sequences and attempts to cluster them into meaningful groups, using the algorithm described in this paper.
Visit the links on the pink bar below to read instructions and guidelines, see output formats, or download the code.

Update (Nov 2016): Implements deletions and insertions in the sequence alignment.

For very large data sets, you are encouraged to download a stand-alone version of the program, with full functionality and no parameter limitations.

Instructions Output format Abstract Downloads

DATA SUBMISSION

Paste peptides in the box:

or submit a file directly from your local disk:



To load some SAMPLE DATA click here:

More sample data: Sample 1 - Sample 2 - Fibroblast (Bassani, MCP 2016)

SUBMIT job



Optionally set some of the parameters before starting your job, or load one of the recommended configurations:

MHC class I ligands of same length:
MHC class I ligands of length 8-13:
MHC class II ligands:

BASIC options

Hover the mouse cursor over the symbol for a short description of the options

Job name

Number of clusters

Motif length


ADVANCED options

Make clustering moves at each iteration

Max deletion length

Max insertion length

Number of seeds for initial conditions

Penalty factor for inter-cluster similarity (λ)

Weigth on small clusters (σ)

Use trash cluster to remove outliers


VERY ADVANCED options

Number of iterations per sequence per temperature step

Initial Monte Carlo temperature

Number of temperature steps

Interval between Indel moves

Interval between Single Peptide moves

Interval between Phase Shift moves

Background amino acid frequencies

Preference for hydrophobic AAs at P1

Sequence weighting type



SUBMIT job



Confidentiality:
The sequences are kept confidential and will be deleted after processing.


CITATIONS

  • GibbsCluster: unsupervised clustering and alignment of peptide sequences
    Andreatta M, Alvarez B, Nielsen M
    Nucleic Acids Research (2017) doi: 10.1093/nar/gkx248
    Full text: PUBMED
  • Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach
    Andreatta M, Lund O, Nielsen M
    Bioinformatics (2012) doi: 10.1093/bioinformatics/bts621
    Full text: PUBMED

PORTABLE VERSION

Would you prefer to run GibbsCluster locally? A portable version for the most common UNIX and MAC platforms is available at this download page.


GETTING HELP

Scientific problems:        Technical problems: