update sage to 0.14.4 (#105)

OpenMS · Oct 30, 2023 · 947b56a · 947b56a
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diff --git a/Linux/64bit/Sage/README.md b/Linux/64bit/Sage/README.md
@@ -25,6 +25,13 @@ Additionally, Sage was designed with cloud computing in mind - massively paralle
 Sage is **simple to configure**, **powerful** and **flexible**. 
 It also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-licensed) and free.
 
+## Citation
+
+If you use Sage in a scientific publication, please cite the following paper:
+
+[Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale](https://doi.org/10.1021/acs.jproteome.3c00486)
+
+
 ## Features
 
 - Incredible performance out of the box
@@ -44,6 +51,5 @@ It also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-lic
 - Support for reading/writing directly from [AWS S3](https://sage-docs.vercel.app/docs/configuration/aws)
 
 
-<!-- <img src="figures/TMT_Panel.png" width="800"> -->
 
 Check out the [blog post introducing Sage](https://lazear.github.io/sage/) for more information and full benchmarks!
diff --git a/Linux/64bit/Sage/sage b/Linux/64bit/Sage/sage
diff --git a/MacOS/64bit/Sage/README.md b/MacOS/64bit/Sage/README.md
@@ -25,6 +25,13 @@ Additionally, Sage was designed with cloud computing in mind - massively paralle
 Sage is **simple to configure**, **powerful** and **flexible**. 
 It also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-licensed) and free.
 
+## Citation
+
+If you use Sage in a scientific publication, please cite the following paper:
+
+[Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale](https://doi.org/10.1021/acs.jproteome.3c00486)
+
+
 ## Features
 
 - Incredible performance out of the box
@@ -44,6 +51,5 @@ It also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-lic
 - Support for reading/writing directly from [AWS S3](https://sage-docs.vercel.app/docs/configuration/aws)
 
 
-<!-- <img src="figures/TMT_Panel.png" width="800"> -->
 
 Check out the [blog post introducing Sage](https://lazear.github.io/sage/) for more information and full benchmarks!
diff --git a/MacOS/64bit/Sage/sage b/MacOS/64bit/Sage/sage
diff --git a/Windows/64bit/Sage/DOCS.md b/Windows/64bit/Sage/DOCS.md
@@ -198,7 +198,10 @@ For additional information about configuration options and output file formats,
       "peak_scoring": "Hybrid", // See DOCS.md for details - recommend that you do not change this setting
       "integration": "Sum",   // Optional["Sum" | "Apex"], use sum of MS1 traces in peak, or MS1 intensity at peak apex
       "spectral_angle": 0.7,  // Optional[float] {default = 0.7}, normalized spectral angle cutoff for calling an MS1 peak
-      "ppm_tolerance": 5.0    // Optional[float] {default = 5.0}, tolerance (in p.p.m.) for DICE window around calculated precursor mass
+      "ppm_tolerance": 5.0,    // Optional[float] {default = 5.0}, tolerance (in p.p.m.) for DICE window around calculated precursor mass
+      // Optional[bool] {default = true}. Combine all charge states for quantification. Setting this to false
+      // quantifies each peptide-charge precursor in `precursor_charge` range (see below) separately
+      "combine_charge_states": true
     }
   },
   "precursor_tol": {        // Tolerance can be either "ppm" or "da"

diff --git a/Windows/64bit/Sage/README.md b/Windows/64bit/Sage/README.md
@@ -25,6 +25,13 @@ Additionally, Sage was designed with cloud computing in mind - massively paralle
 Sage is **simple to configure**, **powerful** and **flexible**. 
 It also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-licensed) and free.
 
+## Citation
+
+If you use Sage in a scientific publication, please cite the following paper:
+
+[Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale](https://doi.org/10.1021/acs.jproteome.3c00486)
+
+
 ## Features
 
 - Incredible performance out of the box
@@ -44,6 +51,5 @@ It also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-lic
 - Support for reading/writing directly from [AWS S3](https://sage-docs.vercel.app/docs/configuration/aws)
 
 
-<!-- <img src="figures/TMT_Panel.png" width="800"> -->
 
 Check out the [blog post introducing Sage](https://lazear.github.io/sage/) for more information and full benchmarks!
diff --git a/Windows/64bit/Sage/sage.exe b/Windows/64bit/Sage/sage.exe