Dr. Tom Conway discusses monitoring the quality of pathogen genome data used in public health and clinical settings. Typical genomics workflows involve sample preparation, sequencing, and analyzing sequence data. Sequence quality is measured by aligning to reference sequences and identifying mismatches. As more sequence fragments accumulate, the number of distinct words increases until reaching an asymptote, and word frequency distributions become more informative. Comparing true and false word counts derived from sequences can estimate genome size and true word fraction for quality control. This quantifiable, efficient, and interpretable approach is valuable for clinical and public health applications across species.

1. Monitoring the quality of
data in the clinical use of
pathogen genomes
Dr Tom Conway
IBM Research Australia

2. Uses of Microbial Genomes: Public Health
Infected Food Microbiological
Investigation
Cluster
Analysis

3. Uses of Microbial Genomes: Clinical
Antibiotic
Resistance Test
Detecting
Resistance Genes
Current Practice Genomics Methods

4. Typical Genomics Workflow
Sample Prep
Sequencing
Sequence Data
Analytics
Reporting InterventionSequence Data

5. Measuring Sequence Quality

6. Using a Reference Sequence
alignment
Reference
Sequences
that failed to
align to
reference
x
x
x
x x o
x o
xo
x
x
Sequence fragment

7. Sequence Data as Words
1: imped, and shivered, and glafed, and growled; and
2: wind was rushing was the sea; and that the smwll
3: nd broad impression of thk identity of things seem
(from Great Expectations with apologies to Charles Dickens)

8. Sequence Data as Words
GTGGGTTTTTATCGGCTGGCACATGTGTTGGG
GTGGGT TTTATC GCTGGC CATGTG
TGGGTT TTATCG CTGGCA ATGTGT
GGGTTT TATCGG TGGCAC TGTGTT
GGTTTT ATCGGC GGCACA GTGTTG
GTTTTT TCGGCT GCACAT TGTTGG
TTTTTA CGGCTG CACATG GTTGGG
TTTTAT GGCTGG ACATGT

9. Accumulating Fragments: 10,000
#differentwords
word frequency

10. Accumulating Fragments: 20,000
#differentwords
word frequency

11. Accumulating Fragments: 50,000
#differentwords
word frequency

12. Accumulating Fragments: 100,000
#differentwords
word frequency

13. Accumulating Fragments: 200,000
#differentwords
word frequency

14. Accumulating Fragments: 500,000
#differentwords
word frequency

15. Accumulating Fragments: 1,000,000
#differentwords
word frequency

16. Accumulating Fragments: 1,000,000
#differentwords
word frequency

17. Differentiating True and False Words
#differentwords
word frequency

18. Estimated Genome Size
Isolate Number
EstimatedGenomeSize(Mbp)

19. Isolate Number
TrueWordFraction
True Word Fraction

20. Why This is Valuable
Quantifiable Robust
Efficient
Species
Independent
Actionable
Interpretable

21. The Team
Tom
Conway
Jeremy
Wazny
Justin
Bedo
Mahtab
Mirmomeni
Ben
Goudey
Kelly
Wyres
Natalie
Gunn
Hannah
Huckstep