Gisrecs = load_deduplicated_sequences ( 'gisaid_cov2020_sequences.fasta' ) annot = pathogenie. Next we can annotate with my own routine as follows: Here are the proteins in the NCBI RefSeq annotation: gene Annotationsįirst let’s check that our annotation works ok against the reference genome which is NC_045512. This is done by pairwise comparisons to the reference. Finally we can compare each one to the reference to see the mutation(s). From these we extract the orthologs by name (we could do it by sequence similarity too) and then collapse these to the unique set of protein sequences which will be much less. They are annotated and the function returns a pandas dataframe of all proteins from all samples. These were reduced to 6408 by removing exactly identical sequences. There were 7428 complete nucleotide sequences for SARS-CoV-2 sampled from humans present in the GISAID database at time of writing. This approach would work for more distant sequences too. However since they’re viral genomes it’s very quick and it lets us extract the sequence for any protein of interest. Notice that annotating all the genomes like this is somewhat inefficient since they are practically identical. Here I use some code from a Python package I made called pathogenie to do the annotation. Then these can all be aligned against the reference to see the amino acid substitutions. An alternate way is to annotate the genomes and extract the corresponding protein sequences across all non-redundant genomes (non-identical). Typically a phylogenetic approach is used using the nucleotide sequence. There is more than one way to do this as usual. One way of using these sequences is to calculate the number of non-synonymous mutations arising in the genome since the first identified isolate from Wuhan was sequenced. This data is available with free registration on the GISAID website. There are at present ~8000 sequences for the human virus present. These genomes are updated daily from sequencing results across the world. ![]() Some of them may be positively or negatively selected for. Groups studying the SARS-CoV-2 virus are using genomes from GISAID to keep track of variants that could have functional effects on the virus phenotype.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |