update instrument list in readme

loosolab · Jun 7, 2019 · 594dd0f · 594dd0f
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diff --git a/README.Rmd b/README.Rmd
@@ -12,16 +12,17 @@ knitr::opts_chunk$set(
 ```
 
 # MARMoSET 
-
 A package to extract meta data out of Thermo Fischer raw files.
 Meta data refers to what is found in a raw file as parts of the file header, sample information, instrument method and mass spectrometer tune data.
 
 Works with the following instruments:
 
 * Thermo EASY-nLC
+* RSLCnano
 * Q Exactive Plus - Orbitrap MS
 * Q Exactive HF - Orbitrap MS
 * Q Exactive - Orbitrap MS
+* Orbitrap Fusion Lumos
 
 ## Motivation:
 
@@ -47,7 +48,7 @@ The c# command line tool can be used in R with `generate_json()` to create a JSO
 
 This JSON file can also be created by using the MARMoSET.exe externally.
 
-Due to the design of the RawFileReader the MARMoSET.exe and therefore this command is running as 64 bit code on Windows only. To use this package with another operating system, it is necessarry to already have the JSON file created. To open a JSON file in R the package `jsonlite` provides the function `fromJSON()`.
+Due to the design of the RawFileReader, the MARMoSET.exe and therefore this command is running as 64 bit code on Windows only. To use this package with another operating system, it is necessarry to already have the JSON file created. To open a JSON file in R the package `jsonlite` provides the function `fromJSON()`.
 
 ```{r}
 library(MARMoSET)
@@ -108,11 +109,13 @@ In the meta data of the 'Thermo EASY-nlc' is a gradient table. This table can be
 
 ```{r}
 gradient_table <- one_gradient_table(flat_json = flat_json, 
-                                     group_number = 1)
+                                     group_number = 1, 
+                                     lc_pump = "Thermo EASY-nLC")
 
-vector_of_gradient_tables <- gradient_tables(flat_json = flat_json)
+vector_of_gradient_tables <- gradient_tables(flat_json = flat_json,
+                                             lc_pump = "Thermo EASY-nLC")
 
-head(gradient_table, 3)
+head(gradient_table, 2)
 ```
 
 Finally to export all tables in a vector or one specific, the functions `save_group_table()` and `save_all_groups()`are helpful. The output of `gradient_tables()` or `match_terms()` goes in as `groups_vector` whereas the second argument, `output_path` expects a path with filename. `save_all_groups()` adds the group numbers automatically to each filename, `save_group_table()` takes it as third argument but doesn't add.

diff --git a/README.md b/README.md
@@ -8,9 +8,11 @@ A package to extract meta data out of Thermo Fischer raw files. Meta data refers
 Works with the following instruments:
 
 -   Thermo EASY-nLC
+-   RSLCnano
 -   Q Exactive Plus - Orbitrap MS
 -   Q Exactive HF - Orbitrap MS
 -   Q Exactive - Orbitrap MS
+-   Orbitrap Fusion Lumos
 
 Motivation:
 -----------
@@ -40,7 +42,7 @@ The c\# command line tool can be used in R with `generate_json()` to create a JS
 
 This JSON file can also be created by using the MARMoSET.exe externally.
 
-Due to the design of the RawFileReader the MARMoSET.exe and therefore this command is running as 64 bit code on Windows only. To use this package with another operating system, it is necessarry to already have the JSON file created. To open a JSON file in R the package `jsonlite` provides the function `fromJSON()`.
+Due to the design of the RawFileReader, the MARMoSET.exe and therefore this command is running as 64 bit code on Windows only. To use this package with another operating system, it is necessarry to already have the JSON file created. To open a JSON file in R the package `jsonlite` provides the function `fromJSON()`.
 
 ``` r
 library(MARMoSET)
@@ -106,11 +108,13 @@ In the meta data of the 'Thermo EASY-nlc' is a gradient table. This table can be
 
 ``` r
 gradient_table <- one_gradient_table(flat_json = flat_json, 
-                                     group_number = 1)
+                                     group_number = 1, 
+                                     lc_pump = "Thermo EASY-nLC")
 
-vector_of_gradient_tables <- gradient_tables(flat_json = flat_json)
+vector_of_gradient_tables <- gradient_tables(flat_json = flat_json,
+                                             lc_pump = "Thermo EASY-nLC")
 
-head(gradient_table, 3)
+head(gradient_table, 2)
 #>   Time[mm:ss] Duration[mm:ss] Flow[nl/min] Mixture[%B]
 #> 1       00:00           00:00          300           5
 #> 2       01:00           01:00          300           5

diff --git a/vignettes/using_MARMoSET.Rmd b/vignettes/using_MARMoSET.Rmd
@@ -23,9 +23,11 @@ Meta data refers to what is found in a raw file as parts of the file header, sam
 Works with the following instruments:
 
 * Thermo EASY-nLC
+* RSLCnano
 * Q Exactive Plus - Orbitrap MS
 * Q Exactive HF - Orbitrap MS
 * Q Exactive - Orbitrap MS
+* Orbitrap Fusion Lumos
 
 ## Motivation:
 
@@ -112,9 +114,11 @@ In the meta data of the 'Thermo EASY-nlc' is a gradient table. This table can be
 
 ```{r}
 gradient_table <- one_gradient_table(flat_json = flat_json, 
-                                     group_number = 1)
+                                     group_number = 1, 
+                                     lc_pump = "Thermo EASY-nLC")
 
-vector_of_gradient_tables <- gradient_tables(flat_json = flat_json)
+vector_of_gradient_tables <- gradient_tables(flat_json = flat_json,
+                                             lc_pump = "Thermo EASY-nLC")
 
 head(gradient_table, 2)
 ```
@@ -142,3 +146,7 @@ group_count(json)
 files_in_group(json, 1)
 
 ```
+
+## How to cite:
+
+Kiweler M, Looso M and Graumann J. MARMoSET – Extracting Publication-Ready Mass Spectrometry Metadata from RAW Files. Molecular & Cellular Proteomics (2019), DOI: 10.1074/mcp.TIR119.001505