update readme

README.md

@@ -22,7 +22,12 @@ pfm =  [0.01  1.0  0.98  0.0   0.0   0.0   0.98  0.0   0.18  1.0
         0.0   0.0  0.0   0.77  0.01  0.0   0.0   0.0   0.56  0.0
         0.0   0.0  0.0   0.05  0.99  0.04  0.01  0.11  0.24  0.0]
 
-logoplot(pfm)
+# Define the background probabilities for (A, C, G, T)
+
+background = [0.25, 0.25, 0.25, 0.25]
+
+logoplot(pfm, background)
+
 ```
 will give
 
@@ -32,6 +37,15 @@ The function `logoplot(pfm)` produces a plot where:
 - The x-axis shows the positions in the PWM. 
 - The y-axis shows the information content (bits) for each position.
 
+Here, `background` is an array representing the background probabilities for A, C, G, and T. These should sum to 1. In this case, a uniform background of `[0.25, 0.25, 0.25, 0.25]` is used, assuming equal probabilities for each base.
+
+You can also simply call 
+```
+logoplot(pfm)
+```
+to get identical results as above, where background is set to be `[0.25, 0.25, 0.25, 0.25]` by default.
+
+
 ## Plotting your PWMs with crosslinking tendencies
 
 The cross-linked PWMs not only display the PWM but also account for crosslinking tendencies, which is typically done for RNA-binding proteins (RBPs).

src/plot_logo.jl

@@ -36,7 +36,6 @@ end
 
 @userplot LogoPlot
 @recipe function f(data::LogoPlot; 
-                   background = [0.25 for _ = 1:4],
                    dna=true, 
                    xaxis=false,
                    yaxis=false,
@@ -76,6 +75,7 @@ end
     thickness_scaling --> thickness_scaling
     size --> logo_size
     pfm = data.args[1]
+    background = length(data.args) ≥ 2 ? data.args[2] : [0.25 for _ = 1:4]
     coords = freq2xy(pfm; background=background, dna=dna, beta=beta,
                      logo_x_offset=logo_x_offset, 
                      logo_y_offset=logo_y_offset);