Immunosignature Data for Distinguishing Four Bloodborne Pathogens

Immunosignature data from a study applying ImmunoSignature Technology (IST) to blood donor samples. The IST platform uses a library of over 100,000 chemically-diverse peptides to capture antibody repertoire information. It was used to train and test algorithms for distinguishing seropositivity for Trypanosoma cruzi, hepatitis B, hepatitis C, and West Nile virus.

Use Cases

• Train a multi-class classifier to distinguish seropositivity for Trypanosoma cruzi, hepatitis B, hepatitis C, and West Nile virus using immunosignature peptide binding signals.
• Analyze differential peptide binding signals between T. cruzi sero-states to identify potential cohort subclasses or novel antigens.
• Benchmark the performance of immunosignature-based binary classification for T. cruzi seropositivity against conventional ELISA test results.

Strengths

• Data is derived from a diagnostic platform using a high-complexity library of over 100,000 position-addressable peptides.
• The study design included training and independent testing cohorts for algorithm validation.
• The dataset supports analysis of four distinct bloodborne diseases (Chagas, hepatitis B, hepatitis C, West Nile virus) from a single assay.

Limitations

• The specific number of samples (rows) and measured features (columns) is not provided in the input.
• The dataset's applicability may be limited to the specific blood donor cohorts and pathogen strains studied.
• As a research dataset from a specific technology platform, it may require domain expertise in immunology or diagnostics for effective use.

Provenance

Source

Dryad

Collection Method

ImmunoSignature Technology (IST) applied to peripheral blood samples from healthy blood donors declared positive or negative for specific pathogens by bank testing.

Freshness

2020-06-24