Haiti Cholera Dataset
The data for this lab is a set of whole genome sequencing data from a number of V. Cholerae strains from the outbreak of cholera in Haiti beginning in 2010 as well as a number of other V. cholerae strains included for comparison. This data was previously published in http://mbio.asm.org/content/4/4/e00398-13.abstract and http://mbio.asm.org/content/2/4/e00157-11.abstract and is available on NCBI’s Sequence Read Archive. You can view a table of the data at metadata.tsv.
Please use the SNVPhyl phylogenomics pipeline to construct a whole genome phylogeny of this data. You may find the input data under
~/CourseData/IDGE_data/module2/VCholerae_SNVPhyl. The reference file should be
reference/2010EL-1786-Haiti-2010.fasta and the fastq files should be in
fastq/. This data was reduced to an average coverage of 12X to speed up execution, so please use a minimum coverage of 4X. The pipeline can be run with the command
/usr/local/snvphyl-galaxy-cli/bin/snvphyl.py. This should take ~20 minutes to complete.
python /usr/local/snvphyl-galaxy-cli/bin/snvphyl.py --deploy-docker --fastq-dir ~/CourseData/IDGE_data/module2/VCholerae_SNVPhyl/fastq/ --reference-file ~/CourseData/IDGE_data/module2/VCholerae_SNVPhyl/reference/2010EL-1786-Haiti-2010.fasta --min-coverage 4 --output-dir ~/workspace/VCholerae_SNVPhyl_output
--deploy-dockerlaunch a Docker container containing the SNVPhyl software
--fastq-dirthe directory to the sequence reads (in fastq format)
--reference-filethe reference genome file the reads will be aligned to (in fasta format)
--min-coveragethe minimum coverage (number of overlapping reads) needed to identify a variant in the genome
--output-dirthe directory to store the output files
When finished, the output files should all be in
Note: Precomputed results are in
~/CourseData/IDGE_data/module2/VCholerae_SNVPhyl/example-output if needed.
Examine the produced phylogenetic tree in
~/workspace/VCholerae_SNVPhyl_output/phylogeneticTree.newick. To visualize this tree, you can upload the file to http://phylo.io/. You will first need to rename the file to end in nwk with the command
mv phylogeneticTree.newick phylogeneticTree.nwk. You can then download the file by opening a web browser and navigating to http://XX.oicrcbw.ca, where XX is your student ID. You can then navigate to
Given how the genomes group together along with the geographic information and dates, what can you infer about the most likely origin of the introduction of cholera into Haiti?
For your information, you can find a larger phylogenetic tree in Figure 1 from “Population Genetics of Vibrio cholerae from Nepal in 2010: Evidence on the Origin of the Haitian Outbreak”.
Salmonella Heidelberg Dataset
The data for this exercise is a set of whole genome sequencing data from a number of Salmonella heidelberg strains.
We will be using the SNVPhyl phylogenomics pipeline to construct a whole genome phylogeny from the read data and we will examine more closely some of the output files SNVPhyl produces. The files required for this exercise are:
- Reads Directory:
These read files have been reduced to an average coverage of 10X to speed up execution. As a result, please set the
--min-coverage parameter to
4 for the SNVPhyl run. Once SNVPhyl has finished running, please answer the following questions.
Note: Precomputed results are in
~/CourseData/IDGE_data/module2/SHeidelberg_SNVPhyl/example-output if needed.
Examine the output file
filterStats.txtto see a summary of the number of SNVs identified, and the number removed due to the SNV filtering steps in SNVPhyl. How many SNV sites were used to generate the phylogeny? How many were removed?
Examine the table of identified SNVs (
snvTable.tsv) and take a look at the positions and identified bases which have a status of filtered-invalid. Can you think of reasons why these positions were filtered by SNVPhyl?
Examine the summary of positions examined by SNVPhyl (
vcf2core.tsv). Definitions of each column are given here. What is the the reference genome length (hint: run
cut -f 1,2 vcf2core.tsv | column -s $'\t' -t? What is the Percentage of all positions that are valid, included, and part of the core genome for all contigs (that is, the percent of the reference genome passing all of SNVPhyl’s filters, try running
cut -f 1,7 vcf2core.tsv | column -s $'\t' -t)? Can you think of reasons why this number is not 100%?