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Immunoglobulin rearrangement identification software tools | Immune system data analysis

B cells express immunoglobulin (Ig) molecules on their outer surface and secrete them into the extracellular space. Secreted Ig is known as antibody. The genes that encode for antibodies are generated by many diversifying mechanisms including combinatorial rearrangement of gene segments, addition of non-templated (n) nucleotides at the junctions, and somatic hypermutation. This circumstance presents the important challenge of inferring the components of the original rearrangement for any observed Ig gene.

Source text:
(Munshaw and Kepler, 2010) SoDA2: a Hidden Markov Model approach for identification of immunoglobulin rearrangements. Bioinformatics.

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Identifies and delimits the variable (V), diversity (D) and joining (J) genes and alleles within immunoglobulin (Ig) or T-cell receptor (TR) nucleotide rearranged sequences. IMGT/V-QUEST delimits framework and complementarity determining regions. It then displays a graphical 2D representation of the variable region. It can also interact with additional IMGT tools for more detailed analysis via an option on the Search page for a detailed analysis, and via a link on the result page for the phylogenetic analysis of the variable region of input sequence.
Allows modelling of processes implicated in human immunoglobulin heavy chain (IGH) gene rearrangement and maturation. iHMMune-align incorporates an explicit model of V-D-J recombination and somatic mutation processes in the form of a hidden Markov model (HMM). The software generates an alignment of the rearranged sequence with its most likely component germline genes. It includes an initial Smith–Waterman alignment step for identifying the IGHV gene. Two version are available: one for full-length or near full-length sequences and the other for short sequences.
SoDA / Somatic Diversification Analysis
Permits the identification of immunoglobulin rearrangements. SoDA is a Hidden Markov Model (HMM) approach used to compute the posterior probabilities of candidate rearrangements and to find those with the highest values among them. The software has been validated on a set of simulated data, a set of clonally related sequences, and a group of randomly selected immunoglobulin (Ig) heavy chains from Genbank. Furthermore, the output format has been redesigned, in part, to facilitate comparison of multiple solutions.
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