01.1-methylation-explore

library(tidyverse)

Bismark + was done on Hyak.

Genmome stats

kt <- read.csv("../data/Pver-karytotype.tab", header = FALSE, sep = "\t")

knitr::kable(head(kt))

V1	V2
JAAVTL010000001.1	2095917
JAAVTL010000002.1	2081954
JAAVTL010000003.1	1617595
JAAVTL010000004.1	1576134
JAAVTL010000005.1	1560107
JAAVTL010000006.1	1451149

There are 18268 scaffolds

nrow(kt)

[1] 18268

ggplot(kt, aes(x = V2)) +
  geom_histogram(bins = 100) +
  scale_x_log10()

ggplot(kt, aes(x = V2)) +
  geom_histogram(bins = 100) +
  xlim(0, 5000)

knitr::kable(kt %>% filter(V2 < 1000) %>% count())

n
6544

First thing I want to do is do a simple histogram showing distribution of methylation levels. This will likely be done by taking 10 bedgraphs and concatenating then, making a histogram.

After that I would want to look at distribution across features..