hypeR: an R package for geneset enrichment workflows

This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

show abstract

“…Geneset enrichment analyses were performed using the hypeR R-package 45 . The background population of genes was set to all detected genes.…”

Section: Geneset Enrichmentmentioning

confidence: 99%

A molecular single-cell lung atlas of lethal COVID-19

Melms

Biermann

Huang

et al. 2021

Nature

509

645

View full text Add to dashboard Cite

show abstract

“…20 A comparison of intermediate responders' GEP with those of the good and poor responders was also performed. Following this, functional annotation of the significant genes according to pathways (hypeR R package 21 ) and cell types was performed (using an Enrichrbased gene enrichment analysis 22 ), and two publicly available gene sets (ARCHS4 and the Human Gene Atlas). 23 24 ARCHS4 is a published database of cell types derived by mining RNAseq data from public gene expression databases.…”

Section: Immune Gene Expression Pathways and Cell Type Analysismentioning

confidence: 99%

“…27 Longitudinal (treatment-induced) significant changes in gene expression were evaluated in paired samples of good and poor responders in two separate SAM analyses. 20 For pathway analysis, the Molecular Signature Database (MSigDB)'s hallmarks gene sets 26 and hypeR R package 21 was used to describe the biological pathways represented by differentially expressed genes. Similarly, longitudinal 28 that is associated with prediction of immunotherapy response, were evaluated in good and poor responders.…”

Section: Immune Gene Expression Pathways and Cell Type Analysismentioning

confidence: 99%

Differential and longitudinal immune gene patterns associated with reprogrammed microenvironment and viral mimicry in response to neoadjuvant radiotherapy in rectal cancer

Wilkins

Fontana

Nyamundanda

et al. 2021

J Immunother Cancer

View full text Add to dashboard Cite

BackgroundRectal cancers show a highly varied response to neoadjuvant radiotherapy/chemoradiation (RT/CRT) and the impact of the tumor immune microenvironment on this response is poorly understood. Current clinical tumor regression grading systems attempt to measure radiotherapy response but are subject to interobserver variation. An unbiased and unique histopathological quantification method (change in tumor cell density (ΔTCD)) may improve classification of RT/CRT response. Furthermore, immune gene expression profiling (GEP) may identify differences in expression levels of genes relevant to different radiotherapy responses: (1) at baseline between poor and good responders, and (2) longitudinally from preradiotherapy to postradiotherapy samples. Overall, this may inform novel therapeutic RT/CRT combination strategies in rectal cancer.MethodsWe generated GEPs for 53 patients from biopsies taken prior to preoperative radiotherapy. TCD was used to assess rectal tumor response to neoadjuvant RT/CRT and ΔTCD was subjected to k-means clustering to classify patients into different response categories. Differential gene expression analysis was performed using statistical analysis of microarrays, pathway enrichment analysis and immune cell type analysis using single sample gene set enrichment analysis. Immunohistochemistry was performed to validate specific results. The results were validated using 220 pretreatment samples from publicly available datasets at metalevel of pathway and survival analyses.ResultsΔTCD scores ranged from 12.4% to −47.7% and stratified patients into three response categories. At baseline, 40 genes were significantly upregulated in poor (n=12) versus good responders (n=21), including myeloid and stromal cell genes. Of several pathways showing significant enrichment at baseline in poor responders, epithelial to mesenchymal transition, coagulation, complement activation and apical junction pathways were validated in external cohorts. Unlike poor responders, good responders showed longitudinal (preradiotherapy vs postradiotherapy samples) upregulation of 198 immune genes, reflecting an increased T-cell-inflamed GEP, type-I interferon and macrophage populations. Longitudinal pathway analysis suggested viral-like pathogen responses occurred in post-treatment resected samples compared with pretreatment biopsies in good responders.ConclusionThis study suggests potentially druggable immune targets in poor responders at baseline and indicates that tumors with a good RT/CRT response reprogrammed from immune “cold” towards an immunologically “hot” phenotype on treatment with radiotherapy.

show abstract

“…HypeR, an R package was used for pathway analysis and visualization ( Federico and Monti, 2020 ). Gene set enrichment analysis was performed with hallmark gene sets in Molecular Signature Database (MSigDB).…”

Section: Methodsmentioning

confidence: 99%

DNA Methylation as a Marker of Body Shape in Premenopausal Women

Divoux

Eroshkin²,

Erdős

et al. 2021

Front. Genet.

View full text Add to dashboard Cite

Preferential accumulation of fat in the gluteo-femoral (GF) depot (pear shape) rather than in the abdominal (A) depot (apple shape), protects against the development of metabolic diseases but the underlying molecular mechanism is still unknown. Recent data, including our work, suggest that differential epigenetic marking is associated with regulation of genes attributed to distinct fat distribution. Here, we aimed to compare the genomic DNA methylation signatures between apple and pear-shaped premenopausal women. To investigate the contribution of upper and lower body fat, we used paired samples of A-FAT and GF-FAT, analyzed on the BeadChip Methylation Array and quantified the differentially methylated sites between the 2 groups of women. We found unique DNA methylation patterns within both fat depots that are significantly different depending on the body fat distribution. Around 60% of the body shape specific DNA methylation sites identified in adipose tissue are maintained ex vivo in cultured preadipocytes. As it has been reported before in other cell types, we found only a hand full of genes showing coordinated differential methylation and expression levels. Finally, we determined that more than 50% of the body shape specific DNA methylation sites could also be detected in whole blood derived DNA. These data reveal a strong DNA methylation program associated with adipose tissue distribution with the possibility that a simple blood test could be used as a predictive diagnostic indicator of young women who are at increased risk for progressing to the apple body shape with a higher risk of developing obesity related complications.Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT02728635 and https://clinicaltrials.gov/ct2/show/NCT02226640, identifiers NCT02728635 and NCT02226640.

show abstract

hypeR: an R package for geneset enrichment workflows

Cited by 125 publications

References 6 publications

A molecular single-cell lung atlas of lethal COVID-19

A molecular single-cell lung atlas of lethal COVID-19

Differential and longitudinal immune gene patterns associated with reprogrammed microenvironment and viral mimicry in response to neoadjuvant radiotherapy in rectal cancer

DNA Methylation as a Marker of Body Shape in Premenopausal Women

Contact Info

Product

Resources

About