Merge branch 'model-extension'

Author: douweschulte

Cargo.toml

@@ -34,7 +34,7 @@ directories = "6.0"
 flate2 = "1.0"
 iai-callgrind = "0.14"
 itertools = "0.14"
-mzdata = {version="0.48", default-features = false, features = ["miniz_oxide"]}
+mzdata = {version="0.49", default-features = false, features = ["miniz_oxide"]}
 ndarray = "0.16"
 ordered-float = { version = "4.6", features = ["serde"] }
 png = "0.17"

examples/ion-explorer/Cargo.toml

@@ -0,0 +1,21 @@
+[package]
+name = "ion-explorer"
+version = "0.1.0"
+authors.workspace = true
+edition.workspace = true
+license.workspace = true
+publish = false
+
+[dependencies]
+clap = { workspace = true }
+directories = { workspace = true }
+itertools = { workspace = true }
+mzdata = { workspace = true, features = ["mgf", "mzml", "thermo"] }
+rustyms = { path = "../../rustyms", default-features = false, features = [
+    "mzdata",
+    "identification",
+] }
+serde_json = { workspace = true }
+
+[lints]
+workspace = true

examples/ion-explorer/README.md

@@ -0,0 +1,7 @@
+# Ion explorer
+
+```
+argo run -p ion-explorer --release -- --in-path /home/douwe/Downloads/raw_data/COVID19_IgG_14_DENOVO_5.csv --raw-file-directory /home/douwe/Downloads/raw_data/ --out-path .
+```
+
+This takes an identified peptides file and extracts and bins all peaks surrounding the main fragment series. This helps in discovering which fragments and neutral losses are actually generated by the used fragmentation method. It returns a separate csv file for all fragments with the mz, count, and average intensity for all detected peaks.

examples/ion-explorer/figure.r

@@ -0,0 +1,33 @@
+library(ggplot2)
+
+for (file in c("start", "fragment_b", "fragment_y", "fragment_v_0", "fragment_w_0", "fragment_w_1", "fragment_w_2", "fragment_w_3", "fragment_w_4", "fragment_w_5", "fragment_w_6", "fragment_precursor")) {
+    data = read.csv(paste(file, ".csv", sep=""), header=TRUE);
+    # data = data[data$count > 1000,];
+
+    plot = ggplot(data, aes(x=mz, y=count, size=avg_intensity, colour=avg_intensity)) +
+        geom_point() +
+        scale_size_continuous(range = c(0.25, 3)) +
+        xlab("Difference to theoretical ion") +
+        theme_bw() 
+
+    if (file == "fragment_y") {
+        plot = plot + geom_vline(xintercept=0, linetype="dashed") + geom_vline(xintercept=+18.011-0.984, linetype="dashed") + geom_vline(xintercept=-25.979+18.011, linetype="dashed")
+    }
+
+    ggsave(paste(file, ".png", sep=""), plot)
+}
+
+for (file in c("comparison_b_N_N[U:Deamidated]", "comparison_y_N_N[U:Deamidated]")) {
+    data = read.csv(paste(file, ".csv", sep=""), header=TRUE);
+    data = data[data$count_a > 20 | data$count_b > 20,];
+    max_a = max(data$avg_intensity_a);
+    max_b = max(data$avg_intensity_b);
+
+    ggplot(data, aes(x=mz, y=log2(count_a/count_b), colour=rgb(avg_intensity_a / max_a, 0, avg_intensity_b / max_b), size=avg_intensity_a)) +
+        geom_point() +
+        scale_size_continuous(range = c(0.25, 3)) +
+        theme_bw() +
+        guides(colour="none")
+
+    ggsave(paste(file, ".png", sep=""))
+}