Statistics about literature curated ligand-receptor interactions

## Usage

curated_ligrec_stats(...)

## Arguments

...

Passed to curated_ligand_receptor_interactions, determines the set of all curated L-R interactions which will be compared against each of the individual resources.

## Value

A data frame with estimated counts of curated ligand-receptor interactions for each L-R resource.

## Details

The data frame contains the total number of interactions, the number of interactions which overlap with the set of curated interactions (curated_overlap), the number of interactions with literature references from the given resource (literature) and the number of interactions which are curated by the given resource (curated_self). This latter we defined according to our best knowledge, in many cases it's not possible to distinguish curated interactions). All these numbers are also presented as a percent of the total. Importantly, here we consider interactions curated only if they've been curated in a cell-cell communication context.

curated_ligand_receptor_interactions

## Examples

clr <- curated_ligrec_stats()
clr
#> # A tibble: 19 × 8
#>    resource         total curated_over…¹ liter…² curat…³ curat…⁴ liter…⁵ curat…⁶
#>    <chr>            <int>          <int>   <int>   <int>   <dbl>   <dbl>   <dbl>
#>  1 CellPhoneDB       1475           1254     386     486    85.0    26.2    32.9
#>  2 Cellinker         3765           2315    3765     973    61.5   100      25.8
#>  3 CellTalkDB        3473           3421    3160    3160    98.5    91.0    91.0
#>  4 CellChatDB        1894           1210     569     569    63.9    30.0    30.0
#>  5 CellCall           999            779       0       0    78.0     0       0
#>  6 connectomeDB2020  2313           2313    2311    2311   100      99.9    99.9
#>  7 Guide2Pharma       670            588     295     295    87.8    44.0    44.0
#>  8 Baccin2019        1694           1414    1393    1393    83.5    82.2    82.2
#>  9 Kirouac2010        152            125       0       0    82.2     0       0
#> 10 Ramilowski2015    1946           1903     274     274    97.8    14.1    14.1
#> 11 scConnect          479            439     291     291    91.6    60.8    60.8
#> 12 talklr            2485           2364     274     273    95.1    11.0    11.0
#> 13 ICELLNET           738            736     735     735    99.7    99.6    99.6
#> 14 EMBRACE           1702           1615       0       0    94.9     0       0
#> 15 LRdb              3310           3136    2052    2052    94.7    62.0    62.0
#> 16 iTALK             2639           2491       0       0    94.4     0       0
#> 17 SignaLink         1797            242    1797     217    13.5   100      12.1
#> 18 HPMR               595            567     550     550    95.3    92.4    92.4
#> 19 Wojtowicz2020      438            163       0       0    37.2     0       0
#> # … with abbreviated variable names ¹​curated_overlap, ²​literature,
#> #   ³​curated_self, ⁴​curated_overlap_pct, ⁵​literature_pct, ⁶​curated_self_pct