non weighted histogram of read lengths

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A non-weighted histogram of read lengths is a graphical representation of the distribution of read lengths in a set of sequencing data. In this type of histogram, each read length is represented by a single count, regardless of the number of times that length occurs in the dataset.

To create a non-weighted histogram of read lengths, you can follow these steps:
1. Collect the read length data from your sequencing dataset.
2. Determine the range of read lengths in your dataset.
3. Divide the range of read lengths into a series of bins, each representing a range of read lengths.
4. Count the number of reads in each bin.
5. Plot the bin counts on the y-axis and the bin ranges on the x-axis to create a histogram.

Here's an example code snippet in Python to create a non-weighted histogram of read lengths using the Matplotlib library:

import matplotlib.pyplot as plt

# Example read length data
read_lengths = [100, 200, 300, 400, 500, 200, 300, 300, 100, 100, 200, 500, 500]

# Define the bin ranges
bins = range(0, 600, 100)

# Count the number of reads in each bin
bin_counts, _, _ = plt.hist(read_lengths, bins=bins, color='blue')

# Plot the histogram
plt.xlabel('Read length')
plt.ylabel('Count')
plt.title('Non-weighted histogram of read lengths')
plt.show()

This code will create a histogram with five bins representing read lengths from 0-100, 100-200, 200-300, 300-400, and 400-500. The bin counts will be [4, 4, 3, 1, 2], respectively, and the resulting histogram will show the distribution of read lengths in the dataset.