IGV's translation row gets frameshifted when scrolling

The Integrated Genomics Viewer (IGV) can show the translation of the DNA if the "show translation" option is checked in the context menu of the sequence band at the bottom. It shows three different possible translations, one for each reading frame. I have noticed, though, that which band is which reading frame can get jumbled when moving the viewport, especially when clicking the top navigation band to jump. Therefore, figuring out which band is the helpful one has to be redone after scrolling around. In most cases, there should be at least one nearby stop codon in the frame of the wrong bands, making it clear that they're probably not the ones to look at.

1000 Genomes Phase 1 data has some SNPs that Phase 3 doesn't

Yesterday I noticed that the 1000 Genomes Phase 3 data set is missing some common SNPs. Today I checked whether the SNP I was looking for was in the Phase 1 data set, and it is. The Phase 1 VCF lists it as the same high quality as the rest of the SNPs that I could find in the Phase 3 VCF, so I'm not sure why it was dropped. It's almost certainly real - I've been working with a different set of sequences with many reads that contain the mutation. The proportion of non-co-occurrence from the Phase 1 VCF is an order of magnitude higher than that from the Phase 3 VCF, whether or not the lost-and-found SNP is included in the Phase 1 calculation. This suggests that there is a bit more error in the Phase 1 reads than Phase 3.

1000 Genomes VCF files might not have all SNPs

I've been trying to determine the co-occurrence of a handful of SNPs using a 1000 Genomes VCF file, but one of the SNPs seems to be absent. Its rsID doesn't appear in the VCF, nor can I find it by position. It's a pretty common SNP if I'm reading its NCBI page right; I expect that it should co-occur with the others that I can find in the VCF.

Per the IGSR site, a couple million variations were culled in the production of the Phase 3 data set (that I'm using) for a handful of reasons including quality control. It's possible that this SNP didn't quite make the cut due to uncertainty.

Use VCF files to get SNP information from large data sets

Recently I needed to find information on the co-occurrence of some single-nucleotide polymorphisms in a human gene. For a small data set covering only the gene of interest, manipulating the information in SAM format worked well. But then I wanted to look at the data generated by the 1000 Genomes project, which is comprised of thousands of full genomes - a ton of data. My scripts probably wouldn't be able to handle files that large, and even extracting the relevant SNPs using my current tools from a single genome could take ages. Fortunately, the 1000 Genomes project also offers VCF files, which are catalogs of variations with each individual's type at that site right there on the same line. That's extremely convenient. The rsID is the third tab-delimited field, and filtering for rsIDs I needed was pretty easy with a bit of PowerShell.