TSNE analysis for analyzing and visualizing TSNE algorithm.

Usage

tsne_analysis(sample_gene, group_sample, seed = 1, tsne_dims = 2)

Arguments

sample_gene: Dataframe: All genes in all samples expression dataframe of RNA-Seq (1st-col: 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.
tsne_dims: Numeric: TSNE dimensionality number. Default: 2.

Value

Table: TSNE analysis for analyzing and visualizing TSNE algorithm.

Author

benben-miao

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 <- tsne_analysis(gene_expression, samples_groups)
head(res)
#>       TSNE1     TSNE2
#> 1 -67.41252 -16.61397
#> 2  43.08349 -34.02654
#> 3 123.32273  54.14358
#> 4 -42.52065 -31.30027
#> 5  94.98790  48.97986
#> 6 -23.90637 -22.26434

# 4. Set tsne_dims = 3
res <- tsne_analysis(gene_expression, samples_groups, tsne_dims = 3)
head(res)
#>        TSNE1      TSNE2      TSNE3
#> 1  29.250264 -15.141306 -40.375437
#> 2 -47.013447 -13.546879   8.119351
#> 3  11.078193  -7.835674  99.084440
#> 4   4.104299 -10.244024 -45.251763
#> 5  12.249987 -20.984402  76.807522
#> 6  -5.797345  -0.517750 -33.130167