EEB BootCamp 2020

Bioinformatics Boot Camp for Ecology & Evolution: Genomic Epidemiology Thursday, Aug 6, 2020, 2 - 3:30pm Instructors: Dr Weigang Qiu & Ms Saymon Akther Email: weigang@genectr.hunter.cuny.edu Lab Website: http://diverge.hunter.cuny.edu/labwiki/

CoV Genome Tracker	Coronavirus evolutuon	Lyme Disease (Borreliella)
Haplotype network	Spike protein alignment	Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)

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Case studies

• Covid-19 Genome Tracker
• Comparative genomics of worldwide Lyme disease pathogens

1. Is it necessary to mention nextstrain?

• Next Strain

Bioinformatics tools for genomic epidemiology

Required for the tutorial

• bcftools: Reading/writing BCF2/VCF/gVCF files and calling/filtering/summarising SNP and short indel sequence variants Installation link
• vcftools: To work with genetic variation data in the form of VCF files Github link
• Sequence format converter Web tool
• TCS: To infer Haplotype network, TCS.jar file is provided, Required Java. PubMed link
• Web-interactive visualization of Haplotype Network with tcsBU Web tool; Paper
• ggplot (R)

Not required for the tutorial. Recommended

• BpWrapper: command-line tools for manipulation of sequences, alignment, and tree (based on BioPerl). Github Link; Flowchart from publication
• Pairwise genome alignment with MUMMER: Github link
• Samtools: Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format Installation link

CoV genome data set

• N=100 SARS-CoV-2 genomes collected during January, February & March 2020. Data source & acknowledgement GIDAID (Warning: You need to acknowledge GISAID if you reuse the data in any publication)
• Download the folder "bootcamp_august_6th_2020": data file
• unzip the folder

unzip bootcamp_august_6th_2020.zip

• View files

ls -lrt # long list, in reverse timeline

ls cov_data # a folder of 100 CoV2 genomes in FASTA format, pairwise genome alignment sam and indexed sorted bam files generated by bwa (or nucmer) and samtools 

# We skipped bwa (or nucmer) and samtools part of the tutorial for time constrain. The bash script used to generate these files is available on request 

ls cov_data/*sorted.bam | wc # 100 sorted.bam files correspond to 100 sequence files

less ref.fas # NC_045512 as reference sequence, "q" to quit

less metadata_cov.txt # a tsv file that contains collection dates and geographic information of 100 CoV2 genomes
wc metadata_cov.txt

file TCS.jar # Java application

less bcf-snp-call.sh # a file contain all the bash commands required to call SNPs and generate vcf file of 100 CoV2 genomes
less ploidy.txt # to specify the ploidy=1 during vcf SNP call

less rgb.txt #rgb color code to color the phylogenetic network

• Additional files

Tutorial

• 2-2:30: Introduction on pathogen phylogenomics
• 2:30-2:55: Part 1: Calling SNPs and creating VCF file

## Create alignment pileup and call variants using plodity file(plodity 1), multiallelic, first output is bam then piped to bcf ##

bcftools mpileup -Ou -f ref.fas cov_data/*sorted.bam | bcftools call -mv --ploidy-file ploidy.txt  -Ob -o calls.bcf

## Get Stats, check # of records (SNPs), # of indels, TS/TV ratio 
##( expeced more transitions than transversions) #for cov2 should be around more or less 2.5

bcftools stats calls.bcf | less

#remove indels and save into vcf format 

bcftools view --exclude-types indels calls.bcf > snps.vcf

## filter sites by allele counts: only keep informative sites

vcftools --vcf snps.vcf --mac 2 --recode --recode-INFO-all --out snps2.vcf

## rename the snp2 recode file

mv snps2.vcf.recode.vcf snps2.vcf

#Get stats, check # of records (informative SNPs) and TS/TV ratio (the ratio will increase)

bcftools stats snps2.vcf | less 

## Rename the samples

bcftools query -l snps2.vcf > samples
wc samples 
less samples 

# make sure you don't have exsiting rename_ids.txt file since we are going to append on the file

if [ -e rename_ids.txt ];then rm rename_ids.txt ; fi
cat  samples | while read line; do basename $line .sorted.bam >> rename_ids.txt ; done;
wc rename_ids.txt

#change the name of the samples 

bcftools reheader -s rename_ids.txt snps2.vcf > snps3.vcf
less snps3.vcf

#create fasta file of snps

cat rename_ids.txt | while read line; do echo ">$line"; bcftools query -s "$line" -f '[%TGT]' snps3.vcf; echo; done > cov_haplotypes.fas
grep ">" cov_haplotypes.fas | wc

• 2:55-3:10: Part 2: Build and interactive visualize haplotype network with TCS and tcsBU

# Preparing files for haplotype network visualization by parsing the cov metadata
# create file for geographic information

cut -f1,3 metadata_cov.txt | tr '\t' ';' > haplotype.csv
wc haplotype.csv

# Create file to color the network by geography

cut -f3 metadata_cov.txt | sort | uniq > continent.txt
wc continent.txt 

paste continent.txt rgb.txt | tr '\t' ';' > groups.csv
less groups.csv

#covert the SNPs fasta file to nexus sequential format 
#go to this website 
[https://www.hiv.lanl.gov/content/sequence/FORMAT_CONVERSION/form.html Web tool]

mv result.nexuss cov_haplotypes.nexus
less cov_haplotypes.nexus 

#if by any chance you are unable to complete part 1 then please use backup "cov_haplotypes.nexus" file for rest of the steps
# Build haplotype network for the cov dataset 

java -jar -Xmx1g TCS.jar

## This part is not command line. 
** A java window will pop-up
** Click on "Start New TCS Analysis"
** Fix connection limit at 10 steps
** File -> Select Nexus/Phylip Sequence file -> upload "cov_haplotypes.nexus" file -> Run

# check the output files
ls -lrt 

# Interactive visualization of haplotype network with tcsBU
# go to this website 
** Load graph file -> cov_haplotypes.nexus.graph
** Load group file -> groups.csv
** Load haplotype file -> haplotype.csv
** Show Legend 
** Save SVG

• 3:10-3:25: Part 3: Visualization of SNPs frequency with vcftools and ggplot2
  • Load graph file
  • Load group file
  • Load haplotype file
• 3:25-3:30: Q & A