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I have 2 fastq files and I generated BAM file (indexed and sorted) of some reads. I aligned them to a reference genome (hg19).

I am working with different primers.

FORWARD
1. TTGCCAGTTAACGTCTTCCTTCTCTCTCTG
2. CCCTTGTCTCTGTGTTCTTGTCCCCCCCA
3. TGATCTGTCCCTCACAGCAGGGTCTTCTCT
4. CACACTGACGTGCCTCTCCCTCCCTCCA

REVERSE
1. GAGAAAAGGTGGGCCTGAGGTTCAGAGCCA
2. CCCCACCAGACCATGAGAGGCCCTGCGGCC
3. TGACCTAAAGCCACCTCCTTA
4. CCGTATCTCCCTTCCCTGATTA

Therefore I have different amplicons. How can I plot the coverage of these different amplicons. And what could explain big difference between them?

Thank you very much for your help.

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Well, to plot the coverage I would use something like Python Matplotlib. Take a look at this example:

import matplotlib.pyplot as plt
import matplotlib

amplicons =  ('TTGCCAGTTAACGTCTTCCTTCTCTCTCTG', 
      'CCCTTGTCTCTGTGTTCTTGTCCCCCCCA', 
      'TGATCTGTCCCTCACAGCAGGGTCTTCTCT', 
      'CACACTGACGTGCCTCTCCCTCCCTCCA')
countAmpl = (1635, 4734, 2156, 3085)

fig = plt.figure(figsize=(10,8.5))

subplt = fig.add_subplot(111)
subplt.set_ylabel('Count')
subplt.set_xlabel('Amplicons')
subplt.plot(amplicons, countAmpl,  linestyle='-', marker='o', color='blue')
for tl in subplt.get_yticklabels():
    tl.set_color('blue')

plt.savefig("amplicons.eps")

Check other types of charts in Matplotlib if you think you need something else.

You can also try to open and visualize the BAM in IGV from the Broad Institute.

Regarding the difference in coverage, I would say that some are from a repetitive region. Or the amplification depth of a region is greater than for the others. Or maybe the aligner found similar regions and decided that the amplicon aligns well in all those regions.

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  • $\begingroup$ These amplicons are all of coding exons, so repetitiveness is not likely to be a problem. Unless the read is quite short, it won't align to the wrong place. $\endgroup$ – swbarnes2 Oct 4 '16 at 18:10
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BEDTools, among other software suites, will give you a coverage histogram. Biggest source of bias in PCR efficiency is just that some primers work better than others, there is sequence bias in the PCR amplification stage of the library prep too. GC content contributes to this.

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