Merge pull request #101 from bigbio/dev

Dev

Author: ypriverol

CITATION.cff

@@ -0,0 +1,29 @@
+cff-version: 1.2.0
+message: "If you use ibaqpy in your research, please cite this work."
+title: "ibaqpy: A scalable Python package for baseline quantification in proteomics leveraging SDRF metadata"
+authors:
+  - family-names: "Zheng"
+    given-names: "Ping"
+  - family-names: "Audain"
+    given-names: "Enrique"
+  - family-names: "Webel"
+    given-names: "Henry"
+  - family-names: "Dai"
+    given-names: "Chengxin"
+  - family-names: "Klein"
+    given-names: "Joshua"
+  - family-names: "Hitz"
+    given-names: "Marc-Phillip"
+  - family-names: "Sachsenberg"
+    given-names: "Timo"
+  - family-names: "Bai"
+    given-names: "Mingze"
+  - family-names: "Perez-Riverol"
+    given-names: "Yasset"
+abstract: "Intensity-based absolute quantification (iBAQ) is essential in proteomics as it allows for the assessment of a protein's absolute abundance in various samples or conditions. However, the computation of these values for increasingly large-scale and high-throughput experiments, such as those using DIA, TMT, or LFQ workflows, poses significant challenges in scalability and reproducibility. Here, we present ibaqpy, a Python package designed to compute iBAQ values efficiently for experiments of any scale."
+date-released: "2025-02-08"
+doi: "10.1101/2025.02.08.637208"
+url: "https://www.biorxiv.org/content/early/2025/02/08/2025.02.08.637208"
+journal: "bioRxiv"
+publisher: "Cold Spring Harbor Laboratory"
+version: "2025.02.08.637208"

README.md

@@ -221,9 +221,13 @@ Options:
   --help               Show this message and exit.
 ```
 
-### How to cite ibaqpy
+### Citation
 
-Wang H, Dai C, Pfeuffer J, Sachsenberg T, Sanchez A, Bai M, Perez-Riverol Y. Tissue-based absolute quantification using large-scale TMT and LFQ experiments. Proteomics. 2023 Oct;23(20):e2300188. doi: [10.1002/pmic.202300188](https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202300188). Epub 2023 Jul 24. PMID: 37488995.
+> Zheng P, Audain E, Webel H, Dai C, Klein J, Hitz MP, Sachsenberg T, Bai M, Perez-Riverol Y. ibaqpy: A scalable Python package for baseline quantification in proteomics leveraging SDRF metadata. bioRxiv 2025.02.08.637208; doi: https://doi.org/10.1101/2025.02.08.637208
+
+Other relevant publications:
+
+> Wang H, Dai C, Pfeuffer J, Sachsenberg T, Sanchez A, Bai M, Perez-Riverol Y. Tissue-based absolute quantification using large-scale TMT and LFQ experiments. Proteomics. 2023 Oct;23(20):e2300188. doi: [10.1002/pmic.202300188](https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202300188). Epub 2023 Jul 24. PMID: 37488995.
 
 ### Credits