Common framework?

[privefl]

Hi, it seems you are making a very useful and interesting R package here.

You may know my packages {bigstatsr} and {bigsnpr}.
I think your package could make use of those.

It would be also beneficial if we could agree on some common framework so that people don't see your package as just another tool, but rather as something that fits well in the existing ecosystem and comes as a complementary tool.

What do you think?

[YinLiLin]

Hi, sorry that I just came across your comments here. And many thanks for your suggestions.

Yes, I definitely know the wonderful package bigstatsr and some related packages that you developed. Actually i had tried it last year and compared it with bigmemory, and I found that there are no big difference between those two kinds of packages in terms of efficiency of accessing values from the local file. As bigstatsr has achieved more robust and enrich functions for genomic analysis, sometimes it maybe more likely to cause installation problems, so I eventually choose to use big memory. Moreover, the bigmemory is only used to store the genotype in my package hibayes, it will be transformed to R standard matrix to fit Bayesian model, as you may known, there are millions even billions of iterations on loading SNPs in MCMC process, as loading SNP from memory-map file is slower than from RAM directly, so it's not a good choice to code the MCMC process on the basis of memory-map file.

Anyway, I really thank you for providing so many user-friendly tools, I will constantly follow your updates and integrate it in my future projects.

[privefl]

Thanks for your answer.

Memory-mapping basically access data in RAM, as long as you have enough RAM.
So, the first access is from disk, but the other accesses are made from RAM, which is what makes it so nice to use.