Hi all,
I've always wanted to try harvesting and analysing data from NCBI, but I've just never really known the best way forward. I know that I can easily download a whole bunch of data from NCBI by just searching for a group on the website, Geneious, or any other number of programs/scripts. But, I end up with a big mess of data that seems difficult to sort through and actually use.
So, for those who routinely download NCBI sequences — particularly using R — can you point me in the right direction of packages or tutorials to make it easier to:
- Summarise the available data (say by species within a particular genus) on the online databases. Perhaps with an output table showing the number of sequences available for genes X, Y, and Z by taxon A, B, and C.
- Choose the genes (i.e., several commonly used phylogenetics genes) and the species you want and download them into an alignment.
- Follow up question — It doesn't look like these databases store a specimen identifiers. So, do I need to trawl through each paper's tables to then link different genes from a single specimen together. Or, do people usually just link genes together from the same species to get a full compliment (this seems dodgy and prone to author error in identification).
Perhaps there is already a document or paper that really summarises these issues and the best-practice nicely, but my search queries haven't found it yet.
Many thanks in advance!
James
Hi James, depending on the complexity of the search could try this:
https://cran.r-project.org/web/packages/biomartr/vignettes/Database_Retrieval.html
Some people will use Python and Linux to write code that will pull data from online databases but it requires fairly detailed coding. If you were generating your own data the following link is a great resource for the Phyloseq package: https://bioconductor.org/help/course-materials/2017/BioC2017/Day1/Workshops/Microbiome/MicrobiomeWorkflowII.html#using_phyloseq
Thanks for the helpful replies! That R package looks promising.
I have also been looking at this article.packageArticle BarcodingR: an integrated R package for species identificati...
But, I haven't had a chance to give it a go yet.
My Python skills are very rusty and were not extensive to begin with, but that is another possibility.
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