UMAP analysis for analyzing RNA-Seq data.
Arguments
- sample_gene
Dataframe: gene expression dataframe (1st-col: Transcripts or Genes, 2nd-col~: Samples).
- group_sample
Dataframe: Samples and groups for gene expression (1st-col: Samples, 2nd-col: Groups).
- seed
Numeric: set seed for robust result. Default: 1.
- method
Character: 'naive' (an implementation written in pure R) and 'umap-learn' (requires python package 'umap-learn').
Examples
# 1. Library TOmicsVis package
library(TOmicsVis)
# 2. Use example dataset
data(gene_expression)
head(gene_expression)
#> Genes CT_1 CT_2 CT_3 LT20_1 LT20_2 LT20_3 LT15_1 LT15_2
#> 1 transcript_0 655.78 631.08 669.89 654.21 402.56 447.09 510.08 442.22
#> 2 transcript_1 92.72 112.26 150.30 88.35 76.35 94.55 120.24 80.89
#> 3 transcript_10 21.74 31.11 22.58 15.09 13.67 13.24 12.48 7.53
#> 4 transcript_100 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
#> 5 transcript_1000 0.00 14.15 36.01 0.00 0.00 193.59 208.45 0.00
#> 6 transcript_10000 89.18 158.04 86.28 82.97 117.78 102.24 129.61 112.73
#> LT15_3 LT12_1 LT12_2 LT12_3 LT12_6_1 LT12_6_2 LT12_6_3
#> 1 399.82 483.30 437.89 444.06 405.43 416.63 464.75
#> 2 73.94 96.25 82.62 85.48 65.12 61.94 73.44
#> 3 13.35 11.16 11.36 6.96 7.82 4.01 10.02
#> 4 0.00 0.00 0.00 0.00 0.00 0.00 0.00
#> 5 232.40 148.58 0.00 181.61 0.02 12.18 0.00
#> 6 85.70 80.89 124.11 115.25 113.87 107.69 119.83
data(samples_groups)
head(samples_groups)
#> Samples Groups
#> 1 CT_1 CT
#> 2 CT_2 CT
#> 3 CT_3 CT
#> 4 LT20_1 LT20
#> 5 LT20_2 LT20
#> 6 LT20_3 LT20
# 3. Default parameters
res <- umap_analysis(gene_expression, samples_groups)
head(res)
#> UMAP1 UMAP2
#> CT_1 -0.6752746 0.49425898
#> CT_2 1.0232441 0.03062202
#> CT_3 -0.4722297 -1.32183550
#> LT20_1 -0.2414214 0.13870703
#> LT20_2 0.1991701 -1.23434000
#> LT20_3 0.6431577 1.11879669