...
Additionally, the files in the data directory can be loaded in IGV if you copy them back to your desktop.
Optional
...
The phage lambda data set you examined is actually a mixed population of many different phage lambda genotypes descended from a clonal ancestor. You ran breseq in a mode where it predicted consensus mutations in what it thinks is one uniform haploid genome. Actually, some individuals in the population have certain mutations and others do not, so you might have noticed when you looked at some of the alignments that there was a mixture of bases at a position.
We will talk more about analyzing mixed population data to predict rare variants in a later lesson. However, if you're curious you can now experimental with running breseq in a mode where it estimates the frequencies of different mutations in the population. This process is most accurate for single nucleotide variants. Mutations at intermediate frequencies are not (yet) predicted for all classes of mutations like large structural variants.
| Code Block |
|---|
login1$ breseq --polymorphism-prediction --polymorphism-no-indels -r lambda.gbk lambda_mixed_population.fastq |
The option --polymorphism-prediction turns on these mixed population predictions. The option --polymorphism-no-indels turns off predictions of small insertions and deletions (which don't work as well for reasons too complicated to explain here). You're welcome to also try it without this option.
Copy the resulting output directory back to your computer and examine the HTML output in a web browser. Compare it to the output from before.
Optional: Install breseq
We have already installed breseq in $BI/bin for the purpose of this tutorial. You are welcome to continue using it for your own work, or use the installation options we present here to install or update to newer versions as needed.
...