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8. (0.5 pt) Rosalind Problem 27 describes read quality distribution and shows examples of good data and bad data: Quality score distribution over all sequences Quality score distribution over all sequences Average Quality per read 60000 Average Quality per read 160000 50000 140000 120000 40000 100000 30000 80000 60000 20000 40000 10000 20000 2 3 4 5 6 7 8 9 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 Mean Sequence Quality (Phred Score) Mean Sequence Quality (Phred Score) Using the same FASTQ file as problem 7, calculate the mean phred scores per read and generate a density plot like those shown above, but more legible, using the R package ggplot2 . You should make the font size larger and you do not need to include the "Average Quality per read" box. Label the x-axis 'Mean Read Quality (Phred Score)' and the y-axis 'Read Count'. Feel free to experiment with color and theme, but aim for a publication quality figure. Embed your code and plot below. 9. (0.5 pt) Comment on the quality of the sequencing reads from * fastg Is the data usable? What should you do next?

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---
title: ''
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## 1

```{r}
library(ggplot2)
library(RColorBrewer)

data("ChickWeight")

# Printing first six rows
head(ChickWeight)

# Printing summary statistics
summary(ChickWeight)...

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