Replaces new values with previous values of competing or miRNA counts.

This function replaces new values with previous values of competing or miRNA counts.

update_variables(input_graph, current_counts)

Arguments

input_graph	The processed graph object.
current_counts	The additional df that provided by user.

Value

the graph object.

Details

update_variables function provides updating edge variables to current values. If the microRNA or competing expression (or both) change (decreasing or increasing), this function switches the values that are found in a new dataset provided by user. But the current value dataset must be equal with initial dataset in terms of node name.

Examples

data('minsamp')
data('new_counts')

 minsamp%>%
 priming_graph(Competing_expression, miRNA_expression,
     aff_factor = c(seed_type,energy), deg_factor = region)%>%
   update_variables(new_counts)
#> Warning: First column is processed as competing and the second as miRNA.
#> # A tbl_graph: 8 nodes and 7 edges
#> #
#> # A rooted tree
#> #
#> # Node Data: 8 x 7 (active)
#>   name  type      node_id initial_count count_pre count_current changes_variable
#>   <chr> <chr>       <int>         <dbl>     <dbl>         <dbl> <chr>           
#> 1 Gene1 Competing       1         10000     10000         10000 Competing       
#> 2 Gene2 Competing       2         10000     10000         20000 Up              
#> 3 Gene3 Competing       3          5000      5000          5000 Competing       
#> 4 Gene4 Competing       4         10000     10000         10000 Competing       
#> 5 Gene5 Competing       5          5000      5000          5000 Competing       
#> 6 Gene6 Competing       6         10000     10000         10000 Competing       
#> # … with 2 more rows
#> #
#> # Edge Data: 7 x 22
#>    from    to Competing_name miRNA_name Competing_expre… miRNA_expression
#>   <int> <int> <chr>          <chr>                 <dbl>            <dbl>
#> 1     1     7 Gene1          Mir1                  10000             1000
#> 2     2     7 Gene2          Mir1                  10000             1000
#> 3     3     7 Gene3          Mir1                   5000             1000
#> # … with 4 more rows, and 16 more variables: seed_type <dbl>, energy <dbl>,
#> #   region <dbl>, dummy <dbl>, afff_factor <dbl>, degg_factor <dbl>,
#> #   comp_count_list <list>, comp_count_pre <dbl>, comp_count_current <dbl>,
#> #   mirna_count_list <list>, mirna_count_pre <dbl>, mirna_count_current <dbl>,
#> #   mirna_count_per_dep <dbl>, effect_current <dbl>, effect_pre <dbl>,
#> #   effect_list <list>
   #new_counts includes the current counts of nodes.