Services

MHCMotifDecon - 1.1

Motif deconvolution of Multi-allele immunopetidomics data

MHCMotifDecon-1.1 is a supervised method for motif deconvolution of MHC peptidome data. The method uses MHC binding predictions from NetMHCpan-4.1 (for MHC class I) and NetMHCIIpan-4.2 (for MHC class II) to deconvolute and assign likely MHC restriction elements to MHC peptidome data.

In the deconvolution, MS co-immunoprecipitated contaminants are identified and placed in a trash bin.

SUBMISSION

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

INPUT TYPE:

Paste an input into the field below:

... or upload a file in format "Ligand [Cell_line_ID]" directly from your local disk:

... or load some sample data (currently only available for class II):

If input data is for multiple cell lines:

paste an input into the field below:


... or load a file with the allele information for each cell line in the format [Cell_line_ID HLA1,HLA2,...] directly from your local disk:


else if input data is for a single cell line:

select species/loci:



Select Allele(s)


... or type a list of molecules names (i.e. DRB1_0101) separated by commas without spaces


For a list of available molecule names click here

ADDITIONAL CONFIGURATION:

Define allowed peptide length to include (default 12-21) 

Include peptide count histogram

Include length histogram

Include consistency matrix plot

Threshold to discard as trash: % Rank 

Minimum quantity of sequences allowed for logo plotting 



Restrictions:

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

CITATIONS

For publication of results, please cite:

  • Accurate MHC Motif Deconvolution of immunopeptidomics data reveals high relevant contribution of DRB3, 4 and 5 to the total DR Immunopeptidome.
    Saghar Kaabinejadian, Carolina Barra, Bruno Alvarez, Hooman Yari, William Hildebrand, Morten Nielsen
    Frontiers in Immunology 26 January 2022. Sec. Antigen Presenting Cell Biology, DOI: 10.3389/fimmu.2022.835454

DATA RESOURCES

INSTRUCTIONS

INPUT DATA

In this section, the user must define the input for the prediction server following these steps:

1) Specify the desired type of input data (Class II or Class I) using the drop down menu.

2) Provide the input data by means of pasting the data into the blank field, uploading it using the "Choose File" button or by loading sample data using the "Load Data" button. The input must be in the format "Ligand [Cell_line_ID]", where ligand is an MS identified peptide, and Cell_line_ID the ID for the corresponding cell line. This ID is optional if analysing single MS data sets. All the input peptide sequences must be in one-letter amino acid code. The alphabet is as follows (case sensitive):

A C D E F G H I K L M N P Q R S T V W Y and X (unknown)

Any other symbol will be converted to X before processing.

MHC SELECTION

Here, the user must define which MHC(s) molecule(s) the input MS data is going to be deconvoluted against:

1)If the input data is for a single cell line, the alleles can be selected from a Dropdown list. Here, first, select the "species/loci.

2)After selecting the "species/loci, the user will be able to select a single or multiple MHC molecules from the updated "Select Allele(s)" list. On the other hand, the user may opt to directly type the MHC names in the provided blank field (separated by commas and without blank spaces); if this is the case, there will be no need to select an MHC supertype familiy from the drop-down menu. Click here for a list of MHC molecule names (use the names in the first column). Please note that a maximum of 20 MHC types is allowed per submission.

3)If the input data is covering MS data from multiple cell lines, the user must paste oin, upload or load sample data describing the MHC molecules expressed in each cell line. The input must be in the format "Cell_line_ID HLA1,HLA2,HLA3", where each Cell_line_ID must match the cell-line ID given in the MS peptide input data. Please note that steps 1-2) and 3) are mutually exclusive, and are only labeled thi