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  29.722650 -29.60331
#> 2 -58.256581 -63.65201
#> 3  50.814277 108.29664
#> 4   8.804477 -44.87441
#> 5  44.802722  85.24188
#> 6  -7.535410 -38.35476

# 4. Set tsne_dims = 3
res <- tsne_analysis(gene_expression, samples_groups, tsne_dims = 3)
head(res)
#>         TSNE1       TSNE2       TSNE3
#> 1   50.852298   5.2688844 -62.8285274
#> 2    2.930825 -55.3187881  56.6204979
#> 3 -158.002406 -22.7746260   0.7410368
#> 4   69.094971  -2.3864599 -25.1125610
#> 5 -122.877310 -32.8406105 -17.8739967
#> 6   53.943997   0.7815635  -0.2766055