Collect plots from ConsensusPartitionList object

Collect plots from ConsensusPartitionList object

# S4 method for ConsensusPartitionList
collect_plots(object, k = 2, fun = consensus_heatmap,
    top_value_method = object@top_value_method,
    partition_method = object@partition_method,
    verbose = TRUE, mc.cores = 1, cores = mc.cores, ...)

Arguments

object

A ConsensusPartitionList-class object from run_all_consensus_partition_methods.

k

Number of subgroups.

fun

Function used to generate plots. Valid functions are consensus_heatmap, plot_ecdf, membership_heatmap, get_signatures and dimension_reduction.

top_value_method

A vector of top-value methods.

partition_method

A vector of partitioning methods.

verbose

Whether to print message.

mc.cores

Number of cores. This argument will be removed in figure versions.

cores

Number of cores, or a cluster object returned by makeCluster.

...

other Arguments passed to corresponding fun.

Details

Plots for all combinations of top-value methods and parittioning methods are arranged in one single page.

This function makes it easy to directly compare results from multiple methods.

Value

No value is returned.

See also

collect_plots,ConsensusPartition-method collects plots for a single ConsensusPartition-class object.

Author

Zuguang Gu <z.gu@dkfz.de>

Examples

# \donttest{
data(golub_cola)
collect_plots(cola_rl, k = 3)
#> * applying consensus_heatmap() for SD:hclust.
#> * applying consensus_heatmap() for SD:kmeans.
#> * applying consensus_heatmap() for SD:skmeans.
#> * applying consensus_heatmap() for SD:pam.
#> * applying consensus_heatmap() for SD:mclust.
#> * applying consensus_heatmap() for CV:hclust.
#> * applying consensus_heatmap() for CV:kmeans.
#> * applying consensus_heatmap() for CV:skmeans.
#> * applying consensus_heatmap() for CV:pam.
#> * applying consensus_heatmap() for CV:mclust.
#> * applying consensus_heatmap() for MAD:hclust.
#> * applying consensus_heatmap() for MAD:kmeans.
#> * applying consensus_heatmap() for MAD:skmeans.
#> * applying consensus_heatmap() for MAD:pam.
#> * applying consensus_heatmap() for MAD:mclust.
#> * applying consensus_heatmap() for ATC:hclust.
#> * applying consensus_heatmap() for ATC:kmeans.
#> * applying consensus_heatmap() for ATC:skmeans.
#> * applying consensus_heatmap() for ATC:pam.
#> * applying consensus_heatmap() for ATC:mclust.

collect_plots(cola_rl, k = 3, fun = membership_heatmap)
#> * applying membership_heatmap() for SD:hclust.
#> * applying membership_heatmap() for SD:kmeans.
#> * applying membership_heatmap() for SD:skmeans.
#> * applying membership_heatmap() for SD:pam.
#> * applying membership_heatmap() for SD:mclust.
#> * applying membership_heatmap() for CV:hclust.
#> * applying membership_heatmap() for CV:kmeans.
#> * applying membership_heatmap() for CV:skmeans.
#> * applying membership_heatmap() for CV:pam.
#> * applying membership_heatmap() for CV:mclust.
#> * applying membership_heatmap() for MAD:hclust.
#> * applying membership_heatmap() for MAD:kmeans.
#> * applying membership_heatmap() for MAD:skmeans.
#> * applying membership_heatmap() for MAD:pam.
#> * applying membership_heatmap() for MAD:mclust.
#> * applying membership_heatmap() for ATC:hclust.
#> * applying membership_heatmap() for ATC:kmeans.
#> * applying membership_heatmap() for ATC:skmeans.
#> * applying membership_heatmap() for ATC:pam.
#> * applying membership_heatmap() for ATC:mclust.

collect_plots(cola_rl, k = 3, fun = get_signatures)
#> * applying get_signatures() for SD:hclust.
#> * 13/60 samples (in 1 classes) remain after filtering by silhouette (>= 0.5).
#> * Not enough samples.
#> * applying get_signatures() for SD:kmeans.
#> * 47/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 166b3798779e315445295e6a4ae05627 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 43 signatures (71.7%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for SD:skmeans.
#> * 19/60 samples (in 1 classes) remain after filtering by silhouette (>= 0.5).
#> * Not enough samples.
#> * applying get_signatures() for SD:pam.
#> * 36/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: ca5fd8466dc961e257add8dc7e395066 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 52 signatures (86.7%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for SD:mclust.
#> * 47/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: bd1a540da0706d6d20eb0732e4419b1a (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 41 signatures (68.3%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for CV:hclust.
#> * 32/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: cc483dfc15cb9729417e8211fed1509a (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 21 signatures (35.0%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for CV:kmeans.
#> * 55/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 7f3f8488c0140c24bff675150f7680e1 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 20 signatures (33.3%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for CV:skmeans.
#> * 51/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 0498c16333cafc996b0e6e3eea3752ee (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 20 signatures (33.3%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for CV:pam.
#> * 50/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 5f3d05dec28965cf40da3da78542892c (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 20 signatures (33.3%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for CV:mclust.
#> * 55/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 34798a7904b5bed656ed6eb66c83ad51 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 20 signatures (33.3%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for MAD:hclust.
#> * 14/60 samples (in 2 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: a39a9c8a3b976f53aec1eb2ce1c0447b (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 19 signatures (31.7%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for MAD:kmeans.
#> * 48/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: c7b59dddbb1b54521d90a3285ed688a8 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 52 signatures (86.7%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for MAD:skmeans.
#> * 24/60 samples (in 2 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 197fe66c9c3154fc695e1f02b1052c26 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 30 signatures (50.0%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for MAD:pam.
#> * 15/60 samples (in 1 classes) remain after filtering by silhouette (>= 0.5).
#> * Not enough samples.
#> * applying get_signatures() for MAD:mclust.
#> * 35/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: e662a063247bf611a0241fff1f546d5b (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 33 signatures (55.0%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for ATC:hclust.
#> * 19/60 samples (in 1 classes) remain after filtering by silhouette (>= 0.5).
#> * Not enough samples.
#> * applying get_signatures() for ATC:kmeans.
#> * 28/60 samples (in 2 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 857cb6959da3768dd59bf188978c1c85 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 16 signatures (26.7%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for ATC:skmeans.
#> * 52/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 0a522acd5f935a92b24e8845b329b589 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 40 signatures (66.7%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.
#> * applying get_signatures() for ATC:pam.
#> * 21/60 samples (in 1 classes) remain after filtering by silhouette (>= 0.5).
#> * Not enough samples.
#> * applying get_signatures() for ATC:mclust.
#> * 53/60 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
#> * cache hash: 4f16d338f4cb89429959b67e3a641d05 (seed 888).
#> * calculating row difference between subgroups by Ftest.
#> * 38 signatures (63.3%) under fdr < 0.05, group_diff > 0.
#> * making heatmaps for signatures.

# }