Part 4: Coverage plotting, chimera detection and inspection

As explained during the lectures, the genome amplification process (MDA) results in a coverage bias across the genome and induces chimera formation. Here you will have a look at the ‘best’ assembly that you managed to obtain, and try to assess the level of bias and chimera formation. In order to visualize the coverage of a normal single-cell assembly, you need to map your reads used in the assembly, back to your assembled contigs. You can then visualize the coverage in Artemis. We will also use a tool to inspect potential chimeras and check the insert size using the pairs.

4.1 Reads mapping
4.2 Assessing coverage bias
4.3 Detection and inspection of chimeric reads
4.4 Insert size

Here are the questions that these results should help you to answer:

Questions:

Q4.1: What was the highest coverage for any of your contigs?

Q4.2: Do you think that the completeness of your SC genome will improve with more sequence data? Why? Will your genome ever be ‘complete’?

Q4.3: How would you explain the coverage patterns you can see on the contigs called NODE_7 and NODE_4.

Q4.4: How many chimeric reads did you find in your original dataset? Do you think this value is a true representation of the total amount of chimeras?

Q4.5: What was the average insert size in this dataset?