From 6fc320d3bbd4cd0616546f98f96504a5dab7a9ee Mon Sep 17 00:00:00 2001 From: Tobias Olsen Date: Fri, 25 Mar 2022 18:45:30 +0000 Subject: [PATCH] Additional information --- README.md | 27 ++++++++++++++++++++++++++- 1 file changed, 26 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 077e8cb..23749a4 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,9 @@ -General protein language models have been shown to summarise the semantics of protein sequences into representations that are useful for state-of-the-art predictive methods. However, for antibody specific problems, such as restoring residues lost due to sequencing errors, a model trained solely on antibodies may be more powerful. Language models require vast numbers of sequences for training and antibodies are one of the few protein types for which such volumes of data exist, for example in the Observed Antibody Space (OAS) database. Here, we introduce AbLang, a language model trained on the antibody sequences in the OAS database. We demonstrate the power of AbLang by using it to restore missing residues in antibody sequence data, a key issue with BCR-seq data, as seen with over 40% of OAS sequences missing the first 15 amino acids. AbLang restores the missing residues of antibody sequences better than using IMGT germlines or the general protein language model ESM-1b. Further, AbLang does not require knowledge of the germline of the antibody and is seven times faster than ESM-1b. +**Motivation:** General protein language models have been shown to summarise the semantics of protein sequences into representations that are useful for state-of-the-art predictive methods. However, for antibody specific problems, such as restoring residues lost due to sequencing errors, a model trained solely on antibodies may be more powerful. Antibodies are one of the few protein types where the volume of sequence data needed for such language models is available, for example in the Observed Antibody Space (OAS) database. + +**Results:** Here, we introduce AbLang, a language model trained on the antibody sequences in the OAS database. We demonstrate the power of AbLang by using it to restore missing residues in antibody sequence data, a key issue with B-cell receptor repertoire sequencing, for example over 40% of OAS sequences are missing the first 15 amino acids. AbLang restores the missing residues of antibody sequences better than using IMGT germlines or the general protein language model ESM-1b. Further, AbLang does not require knowledge of the germline of the antibody and is seven times faster than ESM-1b. ----------- @@ -75,6 +77,29 @@ array(['EVQLVESGPGLVQPGKSLRLSCVASGFTFSGYGMHWVRQAPGKGLEWIALIIYDESNKYYADSVKGRFTISR ``` ----- +For restoration of an unknown number of missing residues at the ends of antibody sequences, the "align" parameter can be set to True. + +```{r, engine='python', count_lines} +seqs = [ + 'EV*LVESGPGLVQPGKSLRLSCVASGFTFSGYGMHWVRQAPGKGLEWIALIIYDESNKYYADSVKGRFTISRDNSKNTLYLQMSSLRAEDTAVFYCAKVKFYDPTAPNDYWGQGTLVTVSS', + 'PGKSLRLSCVASGFTFSGYGMHWVRQAPGKGLEWIALIIYDESNK*YADSVKGRFTISRDNSKNTLYLQMSSLRAEDTAVFYCAKVKFYDPTAPNDYWGQGTL', +] + +heavy_ablang(seqs, mode='restore', align=True) + +``` + +The output of the above is seen below. + +```console +array(['EVQLVESGPGLVQPGKSLRLSCVASGFTFSGYGMHWVRQAPGKGLEWIALIIYDESNKYYADSVKGRFTISRDNSKNTLYLQMSSLRAEDTAVFYCAKVKFYDPTAPNDYWGQGTLVTVSS', + 'QVQLVESGGGVVQPGKSLRLSCVASGFTFSGYGMHWVRQAPGKGLEWIALIIYDESNKYYADSVKGRFTISRDNSKNTLYLQMSSLRAEDTAVFYCAKVKFYDPTAPNDYWGQGTLVTVSS'], + dtype='