From 4019b19bf2a8a020da3a08767de4e9ab99486a9a Mon Sep 17 00:00:00 2001 From: Evelyn Greeves Date: Tue, 23 Jan 2024 15:57:00 +0000 Subject: [PATCH] test to check formatting of headers --- _episodes/02-visualising_snps.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/_episodes/02-visualising_snps.md b/_episodes/02-visualising_snps.md index 8b1e702..c6be747 100644 --- a/_episodes/02-visualising_snps.md +++ b/_episodes/02-visualising_snps.md @@ -124,6 +124,10 @@ Each sample represents a different timepoint in the *E. coli* long-term evolutio - SRR2584863 was sampled from generation 15,000 - SRR2584866 was sampled from generation 50,000 +# test +## test +### test + > ## Challenge 1 > > Look back at the [background information](https://cloud-span.github.io/02genomics/03-background/index.html) and the [metadata](https://github.com/Cloud-SPAN/04genomics/blob/gh-pages/files/Ecoli_metadata_composite.csv) for this dataset. @@ -147,6 +151,10 @@ Each sample represents a different timepoint in the *E. coli* long-term evolutio > Once you have generated your VCF files you can view these in the IGV web app alongside your existing file. Add each VCF file as a new track. You might also want to upload the aligned reads (and their index) on separate tracks too. Once you have everything uploaded, use the viewer to examine the differences between the three samples. Was your prediction correct? {: .challenge} +# test +## test +### test + ### Annotate your VCF file The VCF file we have generated tells us **where** SNPs are located, but not a lot about **what** they affect. Are they affecting coding or non-coding DNA? Do they affect protein coding? How strong are these effects?