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Introduction

In silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. CAVES (Comparative Analysis of Variant Epitope Sequences) is an novel tool created to automate comparative epitope analyses.

CAVES utilizes two levels of comparisons to organize putative epitopes from two closely related sequences (sequence A and B) into multiple informative categories. Level-one (L1) shows the extent to which the two epitope profiles match by directly comparing files of epitope predictions, while Level-two (L2) compares each sorted category from L1 against files of database search results to determine if the putative epitopes have been experimentally confirmed in published literature.
In both levels, epitopes are sorted into categories of exact matches, partial matches, or novel epitopes.

Resources

Installation

CAVES runs through a graphical user interface on Windows operating systems. The software is downloadable as a zipped file containing the standalone executable program with all required dependencies precompiled.

Running CAVES

Level-one input files

In Level-one (L1), CAVES takes epitope prediction results directly from tools hosted by the Immune Epitope Database-Analysis Resource (IEDB-AR, http://tools.iedb.org/main/) and looks for all possible match combinations.

IEDB-AR compatible tools:

 

Epitopes should be predicted for sequence A and B using the same tool and parameters for fair comparison.
Results from TepiTool can be downloaded as a CSV file and uploaded directly into CAVES.
Results from the B cell tool must be copied and pasted into a spreadsheet software (download option not available), and saved as a CSV file for upload to CAVES.

Level-two input files

In Level-two (L2), CAVES incorporates search results from the IEDB database of experimentally confirmed epitopes (https://www.iedb.org/) to determine which of the predicted epitopes have experimental validity in literature.

A search on the IEDB website should be performed for each of the two sequences used for epitope predictions (sequence A and B).

Requirements:

  • Amino acid sequence pasted into the Linear peptide box
  • Substring option selected from the dropdown menu  

 

Each search should use the same parameters for fair comparison, and match the type of epitopes predicted earlier (ie. T cell, B cell, MHC class, etc). Results can be downloaded as a CSV file and uploaded directly into CAVES.

Multiple sequence alignment file

CAVES uses a multiple sequence alignment (MSA) file to perform an insertions/deletions (indel) search, as CAVES uses sequence positional data during its comparative process.

MSA files can be generated with any alignment program that uses the standard dash (-) gap character.

Results can be downloaded as a FASTA file and uploaded directly into CAVES.  

 

Sequence order MUST be:

  1. Sequence A
  2. Sequence B
  3. IEDB database parent protein(s)

Hint: Set MAFFT Output order parameter to Same as input.  

 

To get the IEDB parent protein sequence:

  • Within each downloaded IEDB database search results file, navigate to the Parent Protein Accession column
  • Copy the NCBI accession number
  • Go to the NCBI website ( https://www.ncbi.nlm.nih.gov/) and search the accession to find the corresponding database entry
  • Copy/download sequence in FASTA format

Hint: If sequence A and B IEDB queries produce the same parent protein, this only needs to be included in the MSA once.
If sequence A and B produce different parent proteins, list as Sequence A parent protein before Sequence B parent protein.

CAVES optional parameters

Minimum peptide length

Expects a numeric value indicating the minimum length of amino acids that should be included in CAVES comparisons. Any epitopes that fall below this threshold will be ignored by CAVES.

The IEDB-AR TepiTool sets the epitope length as part of its own parameters.
The B cell linear epitope prediction tool does not allow users to set prediction length, in which case the CAVES threshold may be applicable.

Default threshold is three amino acids.

Level selection

Choice of running only L1 or L2 rather than the full CAVES comparison.

L1 only: compares two files of epitope predictions (no comparison to database search results)

  • MSA requires sequence A and sequence B

L2 only: compares a single file of epitope predictions to a file of database search results

  • MSA requires sequence A and database parent protein

Default setting will run CAVES full analysis (L1 and L2).

Results file

Option to name the CAVES results file and choose the directory in which to save it.

If left blank, a default name will be assigned and the file will be written in the same directory as the CAVES executable.

CAVES output

Results are written as a multi-sheet .xlsx file, labelled with the following short-hand naming convention:

L1 = Level-one results
L2 = Level-two results
E = Exact matches
P = Partial matches
N = Novel epitopes

L2 names will combine the L1 category used for comparison against the database epitopes, along with the L2 category produced as a result.

  • Ex. L1E_L2E will contain epitopes that found an exact match between sequence A and B in L1, and then found an exact match with a database epitope in L2

For details on matching criteria, please refer to our publication and the associated supplementary materials: https://www.mdpi.com/1999-4915/14/6/1152

Legal

Copyright 2021 Connor Lowey
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this work except in compliance with the License. You may obtain a copy of the License at:
https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Contact

Katherine Li: lik3456@myumanitoba.ca
Connor Lowey: connor.lowey@gmail.com