Yaamini’s Notebook: DML Analysis Part 24

Some information I’ve missed

I met with Steven on Tuesday, and he suggested I do a few things:

  1. Figure out if the mRNA genome feature file overlaps with introns and exons
  2. Count the number of unique genes the gene background overlapped with and get Uniprot codes

Feature file overlaps

TL;DR: Yes, the mRNA feature file includes introns and exons.

screen shot 2019-02-27 at 2 33 18 pm

Figure 1. Various genome feature files in IGV.

I opened the tracks in IGV and found they overlapped. I have to consider this as I think about what the overlaps between DML and DMR and exon, intron, or mRNA coding regions actually mean. My guess is that I need to consider exon and intron overlaps as a subset of the mRNA overlaps. Unless the mRNA coding region file has information that isn’t an intron or exon, I could just compare exon and intron overlaps instead of using mRNA overlaps.

Unique genes from gene background-mRNA overlaps

I went back to my R Markdown file and subsetted unique Genbank IDs from the file with gene background-mRNA overlaps and Uniprot codes. I used the following code:

 uniqueBackgroundmRNAblast <- subset(backgroundmRNAblast, !duplicated(backgroundmRNAblast$Genbank)) #Subset the unique Genbank IDs from backgroundmRNAUniprot and save as a new dataframe. nrow(uniqueBackgroundmRNAblast$Genbank) #Count the number of unique genes  

The gene background overlapped with 14,943 unique genes. I saved the subsetted information in this file.

Going forward

  1. Describe gene products for all remaining DML and DMR overlaps
  2. Compare genes with hypermethylated vs. hypomethylated loci and regions

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