README.md

In lihuamei/LinDeconSeq: Cell Type Deconvolution using gene expression data for bulk samples.

LinDeconSeq

Cell Type Deconvolution using gene expression data for bulk samples.

Installing the package

You can install the package using devtools::install_github:

devtools::install_github("lihuamei/LinDeconSeq")

Getting started with LinDeconSeq

In this tutorial we will use GSE19830 (mixture of Liver, Brain and Lung) as an example.

library(LinDeconSeq)
pures <- shen_orr$data[, rowSums(shen_orr$annotation$pure) != 0 ] %>% t
markerRes <- findMarkers(pures[, colnames(shen_orr$phenotype)], shen_orr$phenotype, QN = TRUE)
[INFO] 9 samples and 6669 genes in the reference profile
[INFO] 2873 candidate cell type-specific genes detected with q.cut 0.01
[INFO] Select seed genes and random permutating...
[INFO] Assigning cell type-specific genes to each cell subset
[INFO] Optimizing cell type-specific genes to derive signature matrix...
[INFO] Group size -> 50, condition number -> 1.518792
[INFO] 979 low confidence marker genes have been filtered out.

Deconvolution

To deconvolve the dataset, signature marker genes must be known in advance.

fractions <- deconSeq(shen_orr$data %>% t, markerRes$sigMatrix$sig.mat, verbose = TRUE)
[INFO] There are 42 bulk samples need to be deconvoluted
[INFO] Show deconvolution results....
                 Liver        Brain         Lung
GSM495209 9.995712e-01 0.0004288179 0.000000e+00
GSM495210 9.995061e-01 0.0004938515 0.000000e+00
GSM495211 9.956582e-01 0.0036376592 7.041480e-04
GSM495212 0.000000e+00 1.0000000000 0.000000e+00
GSM495213 9.291706e-04 0.9986788620 3.919674e-04
GSM495214 5.796167e-04 0.9993892521 3.113119e-05
GSM495215 4.002953e-06 0.0000000000 9.999960e-01
GSM495216 0.000000e+00 0.0000000000 1.000000e+00
GSM495217 0.000000e+00 0.0000000000 1.000000e+00
GSM495218 8.380125e-02 0.3066126236 6.095861e-01
GSM495219 9.013318e-02 0.3073880816 6.024787e-01
GSM495220 8.759564e-02 0.3053518980 6.070525e-01
GSM495221 6.544839e-01 0.0914730557 2.540430e-01
GSM495222 6.490951e-01 0.0914795481 2.594253e-01
GSM495223 6.523207e-01 0.0887322675 2.589470e-01
...

More Information

Please see Tutorial.

Citation

Please cite the publication: Li H, Sharma A, Ming W, et al. A deconvolution method and its application in analyzing the cellular fractions in acute myeloid leukemia samples[J]. BMC genomics, 2020, 21(1): 1-15.

lihuamei/LinDeconSeq documentation built on Nov. 29, 2024, 2:59 p.m.