KFlorek - CAPE

Strategies for Modernizing Public Health Genomic Data Approaches

Kelsey Florek, PhD, MPH
Senior Genomics and Data Scientist
Wisconsin State Laboratory of Hygiene
June 5, 2024

Slides live at:
www.k-florek.net/talks

Public Health Application of
Infectious Disease Genomics

Pathogen Surveillance
- trends
- prioritization and risk assessment
- early warning system

Outbreak Response
- source tracking
- containment
- risk assessment

Application of Genomic Data to Outbreaks

An applied genomic epidemiological handbook

Application of Genomic Data to Surveillance

An applied genomic epidemiological handbook

Pathogen Surveillance: SARS-CoV-2

SARS-CoV-2 Wastewater

SARS-CoV-2 Clinical

Advancing Genomics in the Cloud

What is the cloud?

Cloud Data Strategies

Genomic Data Lake

Anatomy of a Bioinformatics Workflow


              include { SAMPLESHEET_CHECK } from '../../modules/local/samplesheet_check'

              workflow INPUT_CHECK {
                  take:
                  samplesheet // file: /path/to/samplesheet.csv
              
                  main:
                  SAMPLESHEET_CHECK ( samplesheet )
                      .csv
                      .splitCsv ( header:true, sep:',' )
                      .map { create_fasta_channel(it) }
                      .set { reads }
              
                  emit:
                  // channel: [ val(meta), [ path_to_reads ] ]
                  reads
                  // channel: [ samplesheet.valid.csv ]                   
                  csv = SAMPLESHEET_CHECK.out.csv
                  // channel: [ versions.yml ]
                  versions = SAMPLESHEET_CHECK.out.versions 
              }
              
              // Function to get list of [ meta, [ fasta ] ]
              def create_fasta_channel(LinkedHashMap row) {
                  // create meta map
                  def meta = [:]
                      meta.id         = row.sample
              
                  def fasta_meta = []
              
                  if (!file(row.fasta).exists()) {
                      exit 1
                  } else {
                      fasta_meta = [ meta, [ file(row.fasta) ] ]
                  }
              
                  return fasta_meta
              }

Genomic Data Cloud Infrastructure

Monitoring Data Workflows with Nextflow Tower

WSLH Data Portal Infrastructure

AWS Glue and MapReduce

Map: input data is first split into smaller blocks, then each block is assigned to a separate worker node and processed in parallel
Shuffle: worker nodes redistribute data such that all data belonging to a group located on the same worker node
Reduce: if needed worker nodes then process each group of output data, in parallel