Dataset Information

PoDCall: positive droplet calling and normalization of droplet digital PCR DNA methylation data.

ABSTRACT:

Motivation

Droplet digital PCR (ddPCR) holds great promises for investigating DNA methylation with high sensitivity. Yet, the lack of methods for analyzing ddPCR DNA methylation data has resulted in users processing the data manually at the expense of standardization.

Results

PoDCall is an R package performing automated calling of positive droplets, quantification and normalization of methylation levels in ddPCR experiments. A Shiny application provides users with an intuitive and interactive interface to access PoDCall functionalities.

Availability and implementation

The PoDCall R package is freely available on Bioconductor at https://bioconductor.org/packages/PoDCall/. The Shiny application can be executed from the R console using the wrapper function PoDCall::podcallShiny().

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Jeanmougin M

PROVIDER: S-EPMC9825742 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

PoDCall: positive droplet calling and normalization of droplet digital PCR DNA methylation data.

Jeanmougin Marine M Brodal Hans Petter HP Dietrichson Pharo Heidi H Vedeld Hege Marie HM Lind Guro Elisabeth GE

Bioinformatics (Oxford, England) 20230101 1

<h4>Motivation</h4>Droplet digital PCR (ddPCR) holds great promises for investigating DNA methylation with high sensitivity. Yet, the lack of methods for analyzing ddPCR DNA methylation data has resulted in users processing the data manually at the expense of standardization.<h4>Results</h4>PoDCall is an R package performing automated calling of positive droplets, quantification and normalization of methylation levels in ddPCR experiments. A Shiny application provides users with an intuitive and ...[more]

PMID: 36448696

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Project description:BackgroundAlu repeats, belonging to the Short Interspersed Repetitive Elements (SINEs) class, contain about 25% of CpG sites in the human genome. Alu sequences lie in gene-rich regions, so their methylation is an important transcriptional regulation mechanism. Aberrant Alu methylation has been associated with tumor aggressiveness, and also previously discussed in hematological malignancies, by applying different approaches. Moreover, today different techniques designed to measure global DNA methylation are focused on the methylation level of specific repeat elements. In this work we propose a new method of investigating Alu differential methylation, based on droplet digital PCR (ddPCR) technology.MethodsForty-six patients with hematological neoplasms were included in the study: 30 patients affected by chronic lymphocytic leukemia, 7 patients with myelodysplastic syndromes at intermediate/high risk, according with the International Prognostic Scoring System, and 9 patients with myelomonocytic leukemia. Ten healthy donors were included as controls. Acute promyelocytic leukemia-derived NB4 cell line, either untreated or treated with decitabine (DEC) hypomethylating agent, was also analyzed. DNA samples were investigated for Alu methylation level by digestion of genomic DNA with isoschizomers with differential sensitivity to DNA methylation, followed by ddPCR.ResultsUsing ddPCR, a significant decrease of the global Alu methylation level in DNA extracted from NB4 cells treated with DEC, as compared to untreated cells, was observed. Moreover, comparing the global Alu methylation levels at diagnosis and after azacytidine (AZA) treatment in MDS patients, a statistically significant decrease of Alu sequences methylation after therapy as compared to diagnosis was evident. We also observed a significant decrease of the Alu methylation level in CLL patients compared to HD, and, finally, for CMML patients, a decrease of Alu sequences methylation was observed in patients harboring the SRSF2 hotspot gene mutation c.284C>D.ConclusionsIn our work, we propose a method to investigate Alu differential methylation based on ddPCR technology. This assay introduces ddPCR as a more sensitive and immediate technique for Alu methylation analysis. To date, this is the first application of ddPCR to study DNA repetitive elements. This approach may be useful to profile patients affected by hematologic malignancies for diagnostic/prognostic purpose.

Dataset Information

PoDCall: positive droplet calling and normalization of droplet digital PCR DNA methylation data.

Motivation

Results

Availability and implementation

Supplementary information

Publications

PoDCall: positive droplet calling and normalization of droplet digital PCR DNA methylation data.

Similar Datasets

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