Merge pull request #43 from wkumler/v1.4.1

Releasing RaMS v1.4.1

.gitignore

@@ -7,6 +7,7 @@
 *.mzXML
 *.sqlite
 *.parquet
+*duckdb
 
 .Rproj.user
 README.Rmd

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: RaMS
 Type: Package
 Title: R Access to Mass-Spec Data
-Version: 1.4.0
+Version: 1.4.1
 Authors@R: c(
   person(given = "William", family = "Kumler", email = "[email protected]",
          role = c("aut", "cre", "cph")),
@@ -26,7 +26,7 @@ Imports:
     data.table,
     utils,
     stats
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Suggests: 
     testthat,
     knitr,

NAMESPACE

@@ -22,4 +22,5 @@ import(utils)
 import(xml2)
 importFrom(base64enc,base64decode)
 importFrom(base64enc,base64encode)
+importFrom(data.table,"%between%")
 importFrom(stats,approx)

NEWS.md

@@ -1,5 +1,9 @@
 # RaMS (development version)
 
+# RaMS 1.4.1
+ - Added timezone support to metadata's timestamps (mzML files are all UTC)
+ - Fixed several bugs in the README and vignettes (it's been a minute since I recompiled these!)
+
 # RaMS 1.4
  - Added MS3 support to file reading and minification
    - MS3 data is not automatically requested with "everything" (the default) and must instead be added (e.g. `grab_what=c("everything", "MS3")`)

R/RaMS-package.R

@@ -12,7 +12,7 @@
 #' alias `%between%`) imported from `data.table`.
 #'
 #' See the package intro on GitHub at https://github.com/wkumler/RaMS and
-#' explore the vignettes with \code{vignette("help", package = "mypkg")}
+#' explore the vignette with \code{vignette("Intro-to-RaMS", package = "RaMS")}
 #'
 #' @keywords internal
 "_PACKAGE"

R/grabMzmlFunctions.R

@@ -283,7 +283,7 @@ grabMzmlMetadata <- function(xml_data){
   time_node <- xml2::xml_find_first(xml_data, xpath = "//d1:run")
   time_val <- xml2::xml_attr(time_node, "startTimeStamp")
   if(!is.na(time_val)){
-    time_stamp <- as.POSIXct(strptime(time_val, "%Y-%m-%dT%H:%M:%SZ"))
+    time_stamp <- as.POSIXct(strptime(time_val, "%Y-%m-%dT%H:%M:%SZ", tz="UTC"))
   } else {
     time_stamp <- as.POSIXct(NA)
   }

README.md

@@ -74,7 +74,9 @@ msdata <- grabMSdata(files = msdata_files[2:4], grab_what = c("BPC", "MS1"))
 
 Some additional examples can be found below, but a more thorough
 introduction can be found in [the
-vignette](https://htmlpreview.github.io/?https://github.com/wkumler/RaMS/blob/master/doc/Intro-to-RaMS.html).
+vignette](https://cran.r-project.org/web/packages/RaMS/vignettes/Intro-to-RaMS.html)
+or by typing `vignette("Intro-to-RaMS", package = "RaMS")` in the R
+console after installation.
 
 #### BPC/TIC data:
 
@@ -214,62 +216,106 @@ For example, we may be interested in the major fragments of a specific
 molecule:
 
 ``` r
-msdata$MS2[premz%between%pmppm(118.0865) & int>mean(int)] %>%
+msdata$MS2[premz%between%pmppm(351.0817) & int>mean(int)] %>%
   plot(int~fragmz, type="h", data=., ylab="Intensity", xlab="Fragment m/z")
 ```
 
 ![](man/figures/README-plotfragdata-1.png)<!-- -->
 
-Or want to search for precursors with a specific neutral loss:
+Or want to search for precursors with a specific neutral loss above a
+certain intensity:
 
 ``` r
-msdata$MS2[, neutral_loss:=premz-fragmz] %>%
-  filter(neutral_loss%between%pmppm(60.02064, 5)) %>%
+msdata$MS2[, neutral_loss:=premz-fragmz][int>1e4] %>%
+  filter(neutral_loss%between%pmppm(126.1408, 5)) %>%
   head(3) %>% knitr::kable()
 ```
 
-|       rt |    premz |   fragmz |        int | voltage | filename         | neutral_loss |
-|---------:|---------:|---------:|-----------:|--------:|:-----------------|-------------:|
-| 4.182333 | 118.0864 | 58.06590 | 390179.500 |      35 | DDApos_2.mzML.gz |     60.02055 |
-| 4.276100 | 116.0709 | 56.05036 |   1093.988 |      35 | DDApos_2.mzML.gz |     60.02050 |
-| 4.521367 | 118.0864 | 58.06589 | 343084.000 |      35 | DDApos_2.mzML.gz |     60.02056 |
+|       rt |    premz |   fragmz |      int | voltage | filename                               | neutral_loss |
+|---------:|---------:|---------:|---------:|--------:|:---------------------------------------|-------------:|
+| 47.27750 | 351.0817 | 224.9409 | 16333.23 |      40 | Blank_129I_1L_pos_20240207-MS3.mzML.gz |     126.1408 |
+| 47.35267 | 351.0818 | 224.9410 | 27353.09 |      40 | Blank_129I_1L_pos_20240207-MS3.mzML.gz |     126.1408 |
+| 47.42767 | 351.0818 | 224.9410 | 33843.92 |      40 | Blank_129I_1L_pos_20240207-MS3.mzML.gz |     126.1408 |
+
+#### SRM/MRM data
+
+Selected/multiple reaction monitoring files don’t have data stored in
+the typical MSn format but instead encode their values as chromatograms.
+To extract data in this format, include `"chroms"` in the `grab_what`
+argument:
+
+``` r
+chromsdata <- grabMSdata(files = msdata_files[7], grab_what = "chroms", verbosity = 0)
+```
+
+which has individual reactions separated by the `chrom_type` column (and
+the associated index) with relevant target/fragment data:
+
+``` r
+knitr::kable(head(chromsdata$chroms, 3))
+```
+
+| chrom_type | chrom_index | target_mz | product_mz |       rt | int | filename         |
+|:-----------|:------------|----------:|-----------:|---------:|----:|:-----------------|
+| TIC        | 0           |        NA |         NA | 2.000000 |   0 | wk_chrom.mzML.gz |
+| TIC        | 0           |        NA |         NA | 2.048077 |   0 | wk_chrom.mzML.gz |
+| TIC        | 0           |        NA |         NA | 2.096154 |   0 | wk_chrom.mzML.gz |
 
 #### Minifying MS files
 
-As of version 1.1.0, `RaMS` also has functions that allow irrelevant
-data to be removed from the file to reduce file sizes. See the
-[vignette](https://htmlpreview.github.io/?https://github.com/wkumler/RaMS/blob/master/doc/Minifying-files-with-RaMS.html)
+As of version 1.1.0, `RaMS` has functions that allow irrelevant data to
+be removed from the file to reduce file sizes. See the
+[vignette](https://cran.r-project.org/web/packages/RaMS/vignettes/Minifying-files-with-RaMS.html)
 for more details.
 
 #### tmzML documents
 
 Version 1.2.0 of RaMS introduced a new file type, the “transposed mzML”
 or “tmzML” file to resolve the large memory requirement when working
 with many files. See [the
-vignette](https://htmlpreview.github.io/?https://github.com/wkumler/RaMS/blob/master/doc/Intro-to-tmzML.html)
-for more details.
+vignette](https://cran.r-project.org/web/packages/RaMS/vignettes/Intro-to-tmzML.html)
+for more details, though note that I’ve largely deprecated this file
+type in favor of proper database solutions as in the [speed & size
+comparison
+vignette](https://cran.r-project.org/web/packages/RaMS/vignettes/speed_size_comparison.html).
 
 ## File types
 
 RaMS is currently limited to the modern **mzML** data format and the
-slightly older **mzXML** format, as well as the custom [**tmzML**
-format](https://htmlpreview.github.io/?https://github.com/wkumler/RaMS/blob/master/doc/Intro-to-tmzML.html)
-as of version 1.2.0. Tools to convert data from other formats are
-available through
+slightly older **mzXML** format. Tools to convert data from other
+formats are available through
 [Proteowizard’s](https://proteowizard.sourceforge.io/tools/msconvert.html)
 `msconvert` tool. Data can, however, be gzip compressed (file ending
 .gz) and this compression actually speeds up data retrieval
 significantly as well as reducing file sizes.
 
-Currently, `RaMS` handles MS<sup>1</sup> MS<sup>2</sup>, and MS<sup>3</sup>
-data. This should be easy enough to expand in the future, but right now
-I haven’t observed a demonstrated need for higher fragmentation level
-data collection.
+Currently, `RaMS` handles MS<sup>1</sup>, MS<sup>2</sup>, and
+MS<sup>3</sup> data. This should be easy enough to expand in the future,
+but right now I haven’t observed a demonstrated need for higher
+fragmentation level data collection.
+
+Additionally, note that files can be streamed from the internet directly
+if a URL is provided to `grabMSdata`, although this will usually take
+longer than reading a file from disk:
+
+``` r
+## Not run:
+# Find a file with a web browser:
+browseURL("https://www.ebi.ac.uk/metabolights/MTBLS703/files")
+
+# Copy link address by right-clicking "download" button:
+sample_url <- paste0("https://www.ebi.ac.uk/metabolights/ws/studies/MTBLS703/",
+                     "download/acefcd61-a634-4f35-9c3c-c572ade5acf3?file=",
+                     "FILES/161024_Smp_LB12HL_AB_pos.mzXML")
+
+msdata <- grabMSdata(sample_url, grab_what="everything", verbosity=2)
+msdata$metadata
+```
 
 For an analysis of how RaMS compares to other methods of MS data access
 and alternative file types, consider browsing the [speed & size
 comparison
-vignette](https://htmlpreview.github.io/?https://github.com/wkumler/RaMS/blob/master/doc/speed_size_comparison.html).
+vignette](https://cran.r-project.org/web/packages/RaMS/vignettes/speed_size_comparison.html).
 
 ## Contact
 
@@ -278,4 +324,4 @@ Issues page](https://github.com/wkumler/RaMS/issues).
 
 ------------------------------------------------------------------------
 
-README last built on 2023-11-29
+README last built on 2024-09-17