About using FDR in heatmap

[Pedramto89]

Story

I did an analysis for cell-to-cell proximity and tried to visualize the results via heatmap built in function in giotto. However, I am not sure how in this code or plot, the FDR has been involved and should be interpreted.

...

Error Message

# Your error message here

Expected behavior

I expected to see a kind of plot that involves the FDR results into the cell-to-cell proximity enrichment scores. I used this code:
"cell_proximity_results <- cellProximityEnrichment(
gobject = my_giotto_object,
spatial_network_name = "kNN_network",
cluster_column = "subcluster_combined",
number_of_simulations = 1000,
adjust_method = "fdr",
set_seed = TRUE,
seed_number = 1234
)"

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System Information

Please replace the following according to your machine:

• OS: Mac OS 13.5.1 (22G90), Apple M1

[Pedramto89]

Hi @RubD
I hope you are well. I am still waiting for your response. In the cell proximity analysis in Giotto, I am not sure how we should visualize the statically significant results?
Thnx!

[RubD]

hi @Pedramto89, the result from cellProximityEnrichment() is a simple list.

The first element of the list is the raw simulation table data and the second element provides a data.table with information about enrichment and significance (e.g. fdr). You can work with the data.table or convert that into a data.frame if you want (e.g. as.data.frame(cell_proximity_results[[2]]) and then filter the results as you wish.

[Pedramto89]

Thank you for your prompt response @RubD !

I guess you are referring to this:
"> str(cell_proximity_results)
List of 2
$ raw_sim_table:Classes ‘data.table’ and 'data.frame': 35023 obs. of 5 variables:
..$ unified_int: chr [1:35023] "NA--NA" "Malignant_1--Malignant_1" "Malignant_1--Malignant_3" "Fibroblast_2--Malignant_1" ...
..$ type_int : chr [1:35023] NA "homo" "hetero" "hetero" ...
..$ round : chr [1:35023] "original" "original" "original" "original" ...
..$ V1 : num [1:35023] 17096 608 86 274 301 ...
..$ orig : chr [1:35023] "original" "original" "original" "original" ...
..- attr(, ".internal.selfref")=
..- attr(, "index")= int(0)
.. ..- attr(, "__unified_int")= int [1:35023] 26 52 79 111 135 164 194 223 249 275 ...
$ enrichm_res :Classes ‘data.table’ and 'data.frame': 29 obs. of 13 variables:
..$ unified_int : Factor w/ 29 levels "","Fibroblast_1",..: 29 28 27 26 25 24 23 22 21 20 ...
..$ type_int : chr [1:29] NA "homo" "homo" "homo" ...
..$ original : num [1:29] 17096 608 399 197 475 ...
..$ simulations : num [1:29] 0 186 123 62 151 ...
..$ enrichm : num [1:29] 14.06 1.71 1.7 1.65 1.65 ...
..$ p_higher_orig: num [1:29] 0 0 0 0 0 0 0 0.039 0.384 0.659 ...
..$ p_lower_orig : num [1:29] 1 1 1 1 1 1 1 0.963 0.644 0.356 ...
..$ p.adj_higher : num [1:29] 0 0 0 0 0 ...
..$ p.adj_lower : num [1:29] 1 1 1 1 1 ...
..$ PI_value : num [1:29] 42.18 5.12 5.09 4.95 4.95 ...
..$ int_ranking : int [1:29] 1 2 3 4 5 6 7 8 9 10 ...
..$ first_type : chr [1:29] "Malignant_1" "Fibroblast_3" "Malignant_3" ...
..$ second_type : chr [1:29] "NA" "Malignant_1" "Fibroblast_3" "Malignant_3" ...
..- attr(, ".internal.selfref")="

As you know, in most biological experiments, the statistical ajd.p.val cutoff is lower than 0.05;however, here, I see p.adj_higher and p.adj_lower which makes me confused about which one should I select as the cutoff?
ALso, for the enrichm, I guess the more is the score, the more probable that two cells are close to each other spatially, and negative values show the opposite, am I correct?
I tried to read the documentation but could not find any useful like.