Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improve the power of transcriptome-wide association studies is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2020). On theSindex it has a DataRank of 0.165. It has been cited 2 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.165
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Institutes of Health
Grant: 5R01CA227237-03
(PQ3) A functional genomic approach to identification and interpretation of germline-tumor genetic interactions
National Institutes of Health
Grant: 5U01CA194393-04
Quantifying and Characterizing the shared genetic contribution to common cancers
National Institutes of Health
Grant: 5R01HG009120-04
Integrative approaches for mapping the genetic risk of complex traits
National Institutes of Health
Grant: 3U01HG009088-04S4
Powering whole genome sequence-based genetic discovery for common human diseases- Extended 2021-2022.
National Institutes of Health
Grant: 5R35CA197449-05
Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer Research
Fields of Study
Keywords
Sustainable Development Goals