Merge pull request #22 from complextissue/dev

Add citation

.vscode/extensions.json

@@ -10,7 +10,6 @@
         "ms-python.black-formatter",
         "ms-python.flake8",
         "shardulm94.trailing-spaces",
-        "swyddfa.esbonio",
         "ms-vscode.makefile-tools",
     ]
 }

CITATION.cff

@@ -1,11 +1,69 @@
 cff-version: 1.2.0
-message: "If you use pytximport, please cite it as below. Please also cite the original tximport package."
+title: >-
+  Gene count estimation with pytximport enables reproducible
+  analysis of bulk RNA sequencing data in Python
+message: >-
+  If you use this software, please cite it using the
+  metadata from this file.
+type: software
 authors:
-  - family-names: "Kuehl"
-    given-names: "Malte"
-  - family-names: "Puelles"
-    given-names: "Victor G."
-title: "pytximport: Gene count estimation from transcript quantification files in Python"
+  - given-names: Malte
+    family-names: Kuehl
+    affiliation: Aarhus University
+    orcid: 'https://orcid.org/0000-0003-4167-2498'
+  - given-names: Milagros N.
+    family-names: Wong
+    affiliation: Aarhus University
+  - given-names: Nicola
+    family-names: Wanner
+    affiliation: University Medical Center Hamburg-Eppendorf
+  - given-names: Stefan
+    family-names: Bonn
+    affiliation: University Medical Center Hamburg-Eppendorf
+  - given-names: Victor G.
+    family-names: Puelles
+    orcid: 'https://orcid.org/0000-0002-7735-5462'
+    affiliation: Aarhus University
+identifiers:
+  - type: doi
+    value: 10.1093/bioinformatics/btae700
+    description: Bioinformatics manuscript
+repository-code: 'https://github.com/complextissue/pytximport'
+url: 'https://pytximport.readthedocs.io'
+abstract: >-
+  Transcript quantification tools efficiently map bulk RNA
+  sequencing reads to reference transcriptomes. However,
+  their output consists of transcript count estimates that
+  are subject to multiple biases and cannot be readily used
+  with existing differential gene expression analysis tools
+  in Python.
+
+
+  Here we present pytximport, a Python implementation of the
+  tximport R package that supports a variety of input
+  formats, different modes of bias correction, inferential
+  replicates, gene-level summarization of transcript counts,
+  transcript-level exports, transcript-to-gene mapping
+  generation and optional filtering of transcripts by
+  biotype. pytximport is part of the scverse ecosystem of
+  open-source Python software packages for omics analyses
+  and includes both a Python as well as a command-line
+  interface.
+
+
+  With pytximport, we propose a bulk RNA sequencing analysis
+  workflow based on Bioconda and scverse ecosystem packages,
+  ensuring reproducible analyses through Snakemake rules. We
+  apply this pipeline to a publicly available RNA-sequencing
+  dataset, demonstrating how pytximport enables the creation
+  of Python-centric workflows capable of providing insights
+  into transcriptomic alterations.
+keywords:
+  - RNA-Seq
+  - tximport
+  - Python
+  - scverse
+license: GPL-3.0-or-later
+commit: d9533f5
 version: 0.10.0
-date-released: 2024-10-09
-url: "https://doi.org/10.5281/zenodo.13907917"
+date-released: '2024-11-20'

README.md

@@ -15,6 +15,11 @@
 
 `pytximport` is a Python package for efficient (gene-)count estimation from transcript quantification files produced by pseudoalignment/quasi-mapping tools such as `salmon`, `kallisto`, `rsem` and others. `pytximport` is a port of the popular [tximport Bioconductor R package](https://bioconductor.org/packages/release/bioc/html/tximport.html).
 
+## Manuscript & Documentation
+
+The pytximport manuscript can be accessed at: [https://doi.org/10.1093/bioinformatics/btae700](https://doi.org/10.1093/bioinformatics/btae700).
+Detailled documentation is made available at: [https://pytximport.readthedocs.io](https://pytximport.readthedocs.io/en/latest/start.html).
+
 ## Installation
 
 The recommended way to install `pytximport` is through Bioconda:
@@ -78,10 +83,6 @@ Common options are:
 - `-tx`: Provide this flag to return transcript-level instead of gene-summarized data. Incompatible with gene-level input and `counts_from_abundance=length_scaled_tpm`.
 - `--help`: Display all configuration options.
 
-## Documentation
-
-Detailled documentation is made available at: [https://pytximport.readthedocs.io](https://pytximport.readthedocs.io/en/latest/start.html).
-
 ## Development status
 
 `pytximport` is still in development and has not yet reached version 1.0.0 in the [SemVer](https://semver.org/) versioning scheme. While it should work for almost all use cases and we regularly compare outputs against the R implementation, breaking changes between minor versions may occur. If you encounter any problems, please open a GitHub issue. If you are a Python developer, we welcome pull requests implementing missing features, adding more extensive unit tests and bug fixes.
@@ -95,7 +96,7 @@ The `tximport` package has become a main stay in the bulk RNA sequencing communi
 
 Please cite both the original publication as well as this Python implementation:
 
-- Kuehl, M., & Puelles, V. (2024). pytximport: Gene count estimation from transcript quantification files in Python (0.10.0). Zenodo. https://doi.org/10.5281/zenodo.13907918
+- Kuehl, M., Wong, M. N., Wanner, N., Bonn, S., & Puelles, V. G. (2024). Gene count estimation with pytximport enables reproducible analysis of bulk RNA sequencing data in Python. Bioinformatics, btae700. https://doi.org/10.1093/bioinformatics/btae700
 - Charlotte Soneson, Michael I. Love, Mark D. Robinson. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences, F1000Research, 4:1521, December 2015. doi: 10.12688/f1000research.7563.1
 
 ## License

docs/source/start.md

@@ -15,6 +15,11 @@
 
 `pytximport` is a Python package for efficient (gene-)count estimation from transcript quantification files produced by pseudoalignment/quasi-mapping tools such as `salmon`, `kallisto`, `rsem` and others. `pytximport` is a port of the popular [tximport Bioconductor R package](https://bioconductor.org/packages/release/bioc/html/tximport.html).
 
+## Manuscript & Documentation
+
+The pytximport manuscript can be accessed at: [https://doi.org/10.1093/bioinformatics/btae700](https://doi.org/10.1093/bioinformatics/btae700).
+Detailled documentation is made available at: [https://pytximport.readthedocs.io](https://pytximport.readthedocs.io/en/latest/start.html).
+
 ## Installation
 
 The recommended way to install `pytximport` is through Bioconda:
@@ -65,10 +70,6 @@ Common options are:
 - `-tx`: Provide this flag to return transcript-level instead of gene-summarized data. Incompatible with gene-level input and `counts_from_abundance=length_scaled_tpm`.
 - `--help`: Display all configuration options.
 
-## Documentation
-
-Detailled documentation is made available at: [https://pytximport.readthedocs.io](https://pytximport.readthedocs.io/en/latest/start.html).
-
 ## Development status
 
 `pytximport` is still in development and has not yet reached version 1.0.0 in the [SemVer](https://semver.org/) versioning scheme. While it should work for almost all use cases and we regularly compare outputs against the R implementation, breaking changes between minor versions may occur. If you encounter any problems, please open a GitHub issue. If you are a Python developer, we welcome pull requests implementing missing features, adding more extensive unit tests and bug fixes.
@@ -82,7 +83,7 @@ The `tximport` package has become a main stay in the bulk RNA sequencing communi
 
 Please cite both the original publication as well as this Python implementation:
 
-- Kuehl, M., & Puelles, V. (2024). pytximport: Gene count estimation from transcript quantification files in Python (Version 0.10.0) [Computer software]. https://github.com/complextissue/pytximport
+- Kuehl, M., Wong, M. N., Wanner, N., Bonn, S., & Puelles, V. G. (2024). Gene count estimation with pytximport enables reproducible analysis of bulk RNA sequencing data in Python. Bioinformatics, btae700. https://doi.org/10.1093/bioinformatics/btae700
 - Charlotte Soneson, Michael I. Love, Mark D. Robinson. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences, F1000Research, 4:1521, December 2015. doi: 10.12688/f1000research.7563.1
 
 ## License