FlowSorted.CordBloodCombined.450k.compTable: FlowSorted.CordBloodCombined.450k.compTable

In immunomethylomics/FlowSorted.CordBloodCombined.450k: Illumina 450k/EPIC data on FACS and MACS umbilical blood cells

Description

The FlowSorted.CordBloodCombined.450k.compTable contains the average DNA methylation values used for IDOL deconvolution (Gervin K, Salas LA et al. under review), these data are derived from 263 umbilical blood cell references available in ExperimentHub (FlowSorted.CordBloodCombined.450k).

Researchers who want to project directly their estimates can use this matrix of different cellular populations ( T lymphocytes (CD4+ and CD8+), B cells (CD19+), monocytes (CD14+), NK cells (CD56+), Granulocytes, and nucleated red blood cells of cell sorted umbilical cord blood. The estimates were contrasted versus FACS proportions in 22 umbilical samples, and validated using 197 umbilical cord blood samples.

Usage

#data("FlowSorted.CordBloodCombined.450k.compTable")
#head(FlowSorted.CordBloodCombined.450k.compTable)
#See ?estimateCellCounts2 for deconvolution

Format

A class: matrix, dimensions: 517 7 The format is: num [1:517, 1:7] 0.0568 0.214 0.908 0.839 ...

Value

numeric matrix 517 rows 7 columns

See Also

References

1. K Gervin, LA Salas et al. (2019) Systematic evaluation and validation of references and library selection methods for deconvolution of cord blood DNA methylation data. Clin Epigenetics 11,125. doi: 10.1186/s13148-019-0717-y

2. KM Bakulski, et al. (2016) DNA methylation of cord blood cell types: Applications for mixed cell birth studies. Epigenetics 11:5. doi:10.1080/15592294.2016.1161875.

3. K Gervin, et al. (2016) Cell type specific DNA methylation in cord blood: A 450K-reference data set and cell count-based validation of estimated cell type composition. Epigenetics 11:690-8. doi:10.1080/15592294.2016.1214782.

4. OM de Goede, et al. (2015) Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells. Clin Epigenetics. 7:95. doi:10.1186/s13148-015-0129-6.

5. X Lin, et al. (2018) Cell type-specific DNA methylation in neonatal cord tissue and cord blood: A 850K-reference panel and comparison of cell-types. Epigenetics. 13:941-58. doi:10.1080/15592294.2018.1522929.

6. LA Salas et al. (2018). An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome Biology 19, 64. doi: 10.1186/s13059-018-1448-7.

7. DC Koestler et al. (2016). Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL). BMC bioinformatics. 17, 120. doi: 10.1186/s12859-016-0943-7.

8. EA Houseman et al. (2012) DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13, 86. doi:10.1186/1471-2105-13-86.

9. minfi package for tools for estimating cell type composition in blood using these data

Examples

# Explore the reference library
#data("FlowSorted.CordBloodCombined.450k.compTable")
#head(FlowSorted.CordBloodCombined.450k.compTable)

immunomethylomics/FlowSorted.CordBloodCombined.450k documentation built on Jan. 23, 2022, 5:50 p.m.