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

View Article: PubMed Central - PubMed

ABSTRACT

The 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 > 90, 29.5%) or low scores (P-index < 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.

No MeSH data available.


The distribution of the Participation index (P-index) for all participants of the PGP, sorted with higher scoring participants on the left and lower scoring participants on the right.
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f2: The distribution of the Participation index (P-index) for all participants of the PGP, sorted with higher scoring participants on the left and lower scoring participants on the right.

Mentions: Out of the 5,015 participants, 1,350 participants have a score of 0, indicating that over a quarter of the participants (26.9%) did not provide any valid phenotypes about themselves (Fig. 2). The median P-index is 6.79 and if we filter away the 1,350 participants with no phenotypes, the median P-index goes up to 33.76. The participant scores are mostly dichotomized into 2 distinct groups. Most participants either have P-indexes above 90 (1478 participants) or P-indexes below 10 (2900 participants). These 2 groups of participants make up 87.3% of all participants in the PGP (Fig. 2). As the high-scoring phenotypes are from the survey questionnaires, this implies that most participants either answer most of the surveys or do not take any them, which can explain for the dichotomy of the P-indexes.


An unbiased index to quantify participant ’ s phenotypic contribution to an open-access cohort
The distribution of the Participation index (P-index) for all participants of the PGP, sorted with higher scoring participants on the left and lower scoring participants on the right.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5384003&req=5

f2: The distribution of the Participation index (P-index) for all participants of the PGP, sorted with higher scoring participants on the left and lower scoring participants on the right.
Mentions: Out of the 5,015 participants, 1,350 participants have a score of 0, indicating that over a quarter of the participants (26.9%) did not provide any valid phenotypes about themselves (Fig. 2). The median P-index is 6.79 and if we filter away the 1,350 participants with no phenotypes, the median P-index goes up to 33.76. The participant scores are mostly dichotomized into 2 distinct groups. Most participants either have P-indexes above 90 (1478 participants) or P-indexes below 10 (2900 participants). These 2 groups of participants make up 87.3% of all participants in the PGP (Fig. 2). As the high-scoring phenotypes are from the survey questionnaires, this implies that most participants either answer most of the surveys or do not take any them, which can explain for the dichotomy of the P-indexes.

View Article: PubMed Central - PubMed

ABSTRACT

The 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 > 90, 29.5%) or low scores (P-index < 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.

No MeSH data available.