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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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COLONOMICS - predictive models for normal colon gene expression and DNA methylation for TWAS and MWAS

Authors: Moreno, Victor; Diez-Obrero, Virginia; Diaz-Villanueva, Anna; Sanz-Pamplona, Rebeca;

COLONOMICS - predictive models for normal colon gene expression and DNA methylation for TWAS and MWAS

Abstract

We provide significant SNP prediction models derived from the COLONOMICS data (https://www.colonomics.org). Genotypes were obtained by Affymetrix 6.0 array, imputed to TopMed panel. Gene expression was obtained from Affymetrix U219 array, DNA methylation was obtained with Illuminan 450K array and miRNA expression was obtained by NGS. We provide SNP prediction models for 1,758 genes, 30,530 CpG probes and 38 miRNAs obtained from colon normal biopsy samples. These features can be predicted from SNPs located within ��1Mb, which we assumed they act through cis mechanisms. We include the model���s summary statistics and corresponding SNP weights in SQLite objects. Models were trained using the elastic net procedure employed in the PredictDB pipeline (https://predictdb.org), according to which only models with a predictive performance p-value < 0.05 and R2 > 0.1 are considered significant. We adjusted the models by basic covariates, i.e., sex, age, tissue type and colon anatomic location where biopsies were collected (left and right colon). Genome coordinates refer to GRCh37/hg19.

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Keywords

predictdb, TWAS, MWAS, gene expression, DNA methylation, microRNAs, SNP prediction models

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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