A Menke

AD White

AH Mokdad

AL Price

BE Stranger

D Kahle

DP Judge

E Garfield

ET Lim

GL Splansky

GM Church

GR Abecasis

JE Hirsch

JE Lunshof

K Narayan

KA Frazer

KA Tryka

MD Mailman

MP Ball

N Siva

NC Liu

PC Sham

R Chen

S Purcell

Scientific Reports

AbstractThe Personal Genome Project (PGP) is an effort to enroll many participants to create an open-access repository of genome, health and trait data for research. However, PGP participants are not enrolled for studying any specific traits and participants choose the phenotypes to disclose. To measure the extent and willingness and to encourage and guide participants to contribute phenotypes, we developed an algorithm to score and rank the phenotypes and participants of the PGP. The scoring algorithm calculates the participation index (P-index) for every participant, where 0 indicates no reported phenotypes and 100 indicate complete phenotype reporting. We calculated the P-index for all 5,015 participants in the PGP and they ranged from 0 to 96.7. We found that participants mainly have either high scores (P-index &gt; 90, 29.5%) or low scores (P-index &lt; 10, 57.8%). While, there are significantly more males than female participants (1,793 versus 1,271), females tend to have on average higher P-indexes (P = 0.015). We also reported the P-indexes of participants based on demographics and states like Missouri and Massachusetts have better P-indexes than states like Utah and Minnesota. The P-index can therefore be used as an unbiased way to measure and rank participant’s phenotypic contribution towards the PGP.</jats:p

Yingleong Chan

Michael Tung

Alexander S. Garruss

Sarah W. Zaranek

Ying Kai Chan

Jeantine E. Lunshof

Alexander W. Zaranek

Madeleine P. Ball

Michael F. Chou

Elaine T. Lim

George M. Church

Crossref

An unbiased index to quantify participant’s phenotypic contribution to an open-access cohort

An unbiased index to quantify participant’s phenotypic contribution to an open-access cohort

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