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repgenHMM: a dynamic programming tool to infer the rules of immune receptor generation from sequence data.

Elhanati Y, Marcou Q, Mora T, Walczak AM - Bioinformatics (2016)

Bottom Line: To test the validity of our algorithm, we also generated synthetic sequences produced by a known model, and confirmed that its parameters could be accurately inferred back from the sequences.The inferred model can be used to generate synthetic sequences, to calculate the probability of generation of any receptor sequence, as well as the theoretical diversity of the repertoire.We estimate this diversity to be [Formula: see text] for human T cells.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire de physique théorique, CNRS, UPMC and Ecole normale supérieure, Paris, France.

No MeSH data available.


TCR beta chain rearrangement distribution inferred from sequence data previously analyzed in (Murugan et al., 2012). (a) Distribution of the number of insertions at both VD and DJ junctions, and comparison with the distribution of insertion in the alpha chain from Figure 3c. Inset: The nucleotide usage is identical for VD and DJ insertions when considered on opposite strands. (b) Distribution of the number of deletions on both the V and J genes, averaged over different genes
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btw112-F5: TCR beta chain rearrangement distribution inferred from sequence data previously analyzed in (Murugan et al., 2012). (a) Distribution of the number of insertions at both VD and DJ junctions, and comparison with the distribution of insertion in the alpha chain from Figure 3c. Inset: The nucleotide usage is identical for VD and DJ insertions when considered on opposite strands. (b) Distribution of the number of deletions on both the V and J genes, averaged over different genes

Mentions: The beta and heavy chain algorithm was applied to the human TCR beta data that was already analyzed in (Murugan et al., 2012) using brute-force methods. The inferred model parameters were all very similar to those reported in Murugan et al. (2012), confirming the validity of our algorithm. The distribution of the number of insertions and deletions are displayed in Figure 5. Remarkably, insertion profiles at the two insertion sites are very close to each other, as previously reported, but they also closely match the insertion profile of the alpha chain (Figure 5a). Nucleotide usage in each of the two inserted regions (between V and D, and between D and J) is shown in the inset. The VD insertion base usage is similar to the usage of the complementary bases (antisense) in the DJ region, suggesting that the biological mechanism is operating on the opposite strands for both insertions types, as previously noted (Murugan et al., 2012). From the computational point of view, because the algorithm enumerates both the D gene choice and its deletions, its benefit is smaller for beta chains than for alpha chains.Fig. 5.


repgenHMM: a dynamic programming tool to infer the rules of immune receptor generation from sequence data.

Elhanati Y, Marcou Q, Mora T, Walczak AM - Bioinformatics (2016)

TCR beta chain rearrangement distribution inferred from sequence data previously analyzed in (Murugan et al., 2012). (a) Distribution of the number of insertions at both VD and DJ junctions, and comparison with the distribution of insertion in the alpha chain from Figure 3c. Inset: The nucleotide usage is identical for VD and DJ insertions when considered on opposite strands. (b) Distribution of the number of deletions on both the V and J genes, averaged over different genes
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4920122&req=5

btw112-F5: TCR beta chain rearrangement distribution inferred from sequence data previously analyzed in (Murugan et al., 2012). (a) Distribution of the number of insertions at both VD and DJ junctions, and comparison with the distribution of insertion in the alpha chain from Figure 3c. Inset: The nucleotide usage is identical for VD and DJ insertions when considered on opposite strands. (b) Distribution of the number of deletions on both the V and J genes, averaged over different genes
Mentions: The beta and heavy chain algorithm was applied to the human TCR beta data that was already analyzed in (Murugan et al., 2012) using brute-force methods. The inferred model parameters were all very similar to those reported in Murugan et al. (2012), confirming the validity of our algorithm. The distribution of the number of insertions and deletions are displayed in Figure 5. Remarkably, insertion profiles at the two insertion sites are very close to each other, as previously reported, but they also closely match the insertion profile of the alpha chain (Figure 5a). Nucleotide usage in each of the two inserted regions (between V and D, and between D and J) is shown in the inset. The VD insertion base usage is similar to the usage of the complementary bases (antisense) in the DJ region, suggesting that the biological mechanism is operating on the opposite strands for both insertions types, as previously noted (Murugan et al., 2012). From the computational point of view, because the algorithm enumerates both the D gene choice and its deletions, its benefit is smaller for beta chains than for alpha chains.Fig. 5.

Bottom Line: To test the validity of our algorithm, we also generated synthetic sequences produced by a known model, and confirmed that its parameters could be accurately inferred back from the sequences.The inferred model can be used to generate synthetic sequences, to calculate the probability of generation of any receptor sequence, as well as the theoretical diversity of the repertoire.We estimate this diversity to be [Formula: see text] for human T cells.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire de physique théorique, CNRS, UPMC and Ecole normale supérieure, Paris, France.

No MeSH data available.