C. elegans strains.

Assignment #6
The goal of this project is to analyze next generation sequencing data taken from two C. elegans strains. Unlike previous
projects/assignments, we will not only design scripts, but we will also use these scripts to analyze and understand
common issues that arise from next-generation sequencing.
On canvas is a template file that you should rename as Assignment_6_yourlastname.py.
I have also uploaded a reference fasta file, as well as 4 sets of bam/index files:
 LSJ2_II.bam and N2_II.bam contain sorted indexed bam files that map to CHROMOSOME_II.
 LSJ2_II_reduced.bam and N2_II_reduced.bam are smaller files that you can use for debugging purposes (i.e.,
you don’t want to debug code on huge files that might take a long time to analyze).
The example images and output are run on the reduced/smaller bam files, but you will be graded on your output from
the large files! You will turn in (1) your script as a .py file, (2) a pdf of your write-up to the analysis questions, including
figures supporting your arguments.
1. Script requirements:
A. Follow the template code to take in the following positional arguments: <reference file> <bam file LSJ2> <bam
file N2>
B. Open these files using the appropriate methods from pysam [to install, use install -c bioconda pysam]
C. For each bam file, identify:
1. number of reads
2. number of reads with mapping quality zero
3. number of reads that contain a mismatch to the reference
Store and print this information back to the user.
2. Data analysis: [include all answers in a separate pdf file]
A. Calculate the coverage of LSJ2 and N2 on CHROMOSOME_II in 50,000 bp bins. Use matplotlib to plot a scatter
plot of these coverages comparing LSJ2 and N2. The x-axis should show coverage in LSJ2 and the y-axis should
show cover from N2. Also plot a normalizing line that accounts for the different sequencing depth these strains
were sequenced to. Save this as figure1_yourlastname.png.
B. You will notice a set of unusual bins (circled in first graphical output example). What might cause these reads fall
off the axis so? Confirm this hypothesis by identifying the location of these unusual bins and plot the average
coverage of LSJ2 and N2 in this region at 5000 bp resolution. Save this as figure2_yourlastname.png
C. Identify all the positions in LSJ2 with 2 or more reads that mismatch the reference. For these positions calculate
the percent of reads that are mutant vs. total in LSJ2. Also calculate the percent of reads that are mutant vs.
total in N2 at these same positions. Create a scatter plot that show the LSJ2 mutant frequency on the x-axis and
the N2 mutant frequency on the y-axis. Save this as figure3_yourlastname.png
D. Using your outputted figure 3, identify the regions on the graph that represent actual differences in DNA
sequences between LSJ2 and N2, errors in the C. elegans reference genome, errors due to misaligned reads, and
errors due to mistakes in the sequencing run. What percentage of all of these are bona fide mutations?
Graphical Outputs:
The following examples below show the expected output figures your script should also produce. Your script should
output these as separate .png files. In total, there should be at least three figures.
Ex. Fig1: N2 and LSJ2 reads. Circle is option here I’m simply showing you which bins are ‘unusual’):
Ex. Fig2: Coverage of an unusual region. This example doesn’t show the actual correct region (it’s up to you to figure that
out!) but this is the general format of your figure.
Ex. Fig3: Mismatch frequencies.
Note that all of these examples are run on the reduced bam files. I have done this to help you debug. However, your
write-up (including figures) should be based on the full bam files.
Example Usage:
$ python3 Assignment6_Solution.py -h
$ python3 Assignment6_Solution.py C_elegans_genome_WS220.fa LSJ2_reduced_II.bam N2_reduced_II.bam