Presenter: Tobin Groth

Here we demonstrate the utility of ClaretBio’s SRSLY in cfDNA fragmetnomics for prostate cancer detection. Using a combined random forest and K-fold approach we show that 3’ of cfDNA are the most informative in differentiating between low grade prostate cancer and healthy individuals. The signal is captured at low depth of sequencing and is spread across the genome.

Presenter: Varsha Rao

Here we demonstrate the utility of SRSLY in cfDNA fragmentomics using a cohort of Myelodysplastic Syndrome (MDS) Patients and show that the method can differentiate a sub-group that shows abnormality in erythropoiesis - MDS-RS (Ring sideroblast)

Presenter: Camille Schwartz

This work demonstrates the utility of cfDNA fragmentomics in low-depth sequencing based diagnosis in Myelodysplastic Syndrome

Rootless hair - an under-appreciated, non-invasive sample type for genomic analyses in animal husbandry contexts.