PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements

Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane S.; Thomas, Paul D.

doi:10.1093/nar/gkw1138

Cited by 1,943 publications

(1,749 citation statements)

References 17 publications

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“…c , Gene Ontology (GO) analysis of tested protein-coding non-eGenes. We used the PANTHER overrepresentation test 78 (release 20160715) against 20,972 human genes as background to test for enrichment in GO biological processes using the GO database release 2017-02-28. Significant GO IDs (Bonferroni adjusted P < 0.05) were selected for analysis with REVIGO 79 to group similar ontological terms, which yielded 22 over-represented GO IDs.…”

Section: Extended Datamentioning

confidence: 99%

Genetic effects on gene expression across human tissues

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Nhgri³

et al. 2017

Nature

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Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

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Section: Extended Datamentioning

confidence: 99%

Genetic effects on gene expression across human tissues

groups

Fund

Nhgri³

et al. 2017

Nature

3,584

2,412

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“…In order to determine the average difference in β value produced by 450K and EPIC, we subtracted the mean β for all subjects at each probe on EPIC from the mean β for all subjects at each probe on 450K and conducted paired t-tests to check for statistical significance. We also conducted a pathway analysis to determine if the sites with large differences between the two platforms are enriched for any biological pathways [19]. …”

Section: Methodsmentioning

confidence: 99%

Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

et al. 2018

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Analysis of DNA methylation helps to understand the effects of environmental exposures as well as the role of epigenetics in human health. Illumina, Inc. recently replaced the HumanMethylation450 BeadChip (450K) with the EPIC BeadChip, which nearly doubles the measured CpG sites to >850,000. Although the new chip uses the same underlying technology, it is important to establish if data between the two platforms are comparable within cohorts and for meta-analyses. DNA methylation was assessed by 450K and EPIC using whole blood from newborn (n = 109) and 14-year-old (n = 86) participants of the Center for the Health Assessment of Mothers and Children of Salinas. The overall per-sample correlations were very high (r >0.99), although many individual CpG sites, especially those with low variance of methylation, had lower correlations (median r = 0.24). There was also a small subset of CpGs with large mean methylation β-value differences between platforms, in both the newborn and 14-year datasets. However, estimates of cell type proportion prediction by 450K and EPIC were highly correlated at both ages. Finally, differentially methylated positions between boys and girls replicated very well by both platforms in newborns and older children. These findings are encouraging for application of combined data from EPIC and 450K platforms for birth cohorts and other population studies. These data in children corroborate recent comparisons of the two BeadChips in adults and in cancer cell lines. However, researchers should be cautious when characterizing individual CpG sites and consider independent methods for validation of significant hits.

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“…The PANTHER 385 (Protein ANalysis THrough Evolutionary Relationships) (Mi et al, 2017) protein class (Mi et 386 al., 2013) of the putative ancestor with highest sequence similarity of the microProtein was 387 determined. Additionally, all annotated non-transcription factor-related microProtein 388 candidates were grouped into the 19 remaining parental classes.…”

Section: Classification Of Microprotein Candidates 383mentioning

confidence: 99%