Reviewers are not allowed to consider the prior history of the applicant. This is nonsensical and leads to wasteful expenditure of taxpayer funds. It’s clear that the past predicts the future. We threw out the baby with the bath water in NIH peer review. Combine that with low quality reviewers, who may have never had a grant of their own, and you can see the fundamental problem.
@doctorveera Statistically significant or biologically significant? I can’t tell without the biological effect size. Without direct experimental validation, these are localizations, not identifications.
Very perceptive. I’ve been lucky to be funded by NIH for 40 years. It’s a grind and has never been easy or fair. PIs are treated worse now by university/institutional admin than they ever been. I’m sure there are bad PIs, but years of high level productivity in a highly competitive environment speaks for itself to some extent.
I don’t understand this: “Without action, the status quo persists: researchers redundantly sequence the same samples”. Given the massive variation in humans and context dependence, the real value is in new data collection. I don’t know anyone sequencing the same samples. Value is in new samples.
@FrnkNlsn Thank you! This is one of the most useful posts that I've seen! I'll be using this in my studies of the genetic basis of person-specific changes in gene expression correlations.