rpy2 - R in Python

rpy2 is an interface to R running embedded in a Python process.


on Pypi

Questions and issues

Consider having a look at the documentation. Otherwise questions should preferably be asked on the rpy mailing-list on SourceForge, or on StackOverflow. Bugs, or wishes, can also go to the Github page for the project.

Source code

Repository

The source code is also in a public repository on Github.

License

The same license as R: GPLv2 or greater.

rpy2 in the wild

The package is used in a wide range of domains. For example:

2020

  • Jenjaroenpun, Piroon, et al. "Decoding the epitranscriptional landscape from native RNA sequences." Nucleic Acids Research (2020).
  • Rotzinger, David C., et al. "CT pulmonary angiography for risk stratification of patients with nonmassive acute pulmonary embolism." Radiology: Cardiothoracic Imaging 2.4 (2020): e190188.
  • Zhou, Yonghe, et al. "Chromatic, achromatic and bimodal negative patterning discrimination by free-flying bumble bees." Animal Behaviour 169 (2020): 93-101.
  • Fugere, Tyler, Zhongning Jim Chen, and Issam Makhoul. "Practical Vitamin D Supplementation Using Machine Learning." Journal of bone metabolism 27.2 (2020): 111.
  • Ulu, K. Narynbek, et al. "On the Use of Cox Regression for Statistical Analysis of Fatigue Life Results." Journal of Testing and Evaluation 48.2 (2020): 1439-1451.
  • Ponti, Alexandre, et al. "First-Line Selective Internal Radiation Therapy in Patients with Uveal Melanoma Metastatic to the Liver." Journal of Nuclear Medicine 61.3 (2020): 350-356.
  • Diamantopoulos, Nikos, et al. "Engineering for a science-centric experimentation platform." Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Software Engineering in Practice. 2020.
  • Chopin, Nicolas, and Omiros Papaspiliopoulos. "Linear-Gaussian State-Space Models." An Introduction to Sequential Monte Carlo. Springer, Cham, 2020. 73-80.
  • Edgcomb, Juliet Beni, et al. "Predicting suicidal behavior and self-harm after general hospitalization of adults with serious mental illness." Journal of psychiatric research (2020).

2019

  • Diamantopoulos, Nikos, et al. "Engineering for a Science-Centric Experimentation Platform." arXiv preprint arXiv:1910.03878 (2019).
  • Ponti, Alexandre, et al. "First-Line Selective Internal Radiation Therapy in Patient with Uveal Melanoma Liver Metastases." Journal of Nuclear Medicine (2019): jnumed-119.
  • Levy, Joshua J., et al. "PyMethylProcess—convenient high-throughput preprocessing workflow for DNA methylation data." Bioinformatics (2019).
  • Gruber, Michaela, et al. "Growth dynamics in naturally progressing chronic lymphocytic leukaemia." Nature (2019): 1.
  • Dunnmon, Jared, et al. "Cross-Modal Data Programming Enables Rapid Medical Machine Learning." arXiv preprint arXiv:1903.11101 (2019).

2018

  • Christophides, Damianos, et al. "A method for automatic selection of parameters in NTCP modelling." International Journal of Radiation Oncology• Biology• Physics (2018).
  • Fadda, Giulia, et al. "MRI and laboratory features and the performance of international criteria in the diagnosis of multiple sclerosis in children and adolescents: a prospective cohort study." The Lancet Child & Adolescent Health (2018).
  • Muschelli, John, et al. "Neuroconductor: an R platform for medical imaging analysis." Biostatistics (2018).
  • Domingues, Rémi, et al. "A comparative evaluation of outlier detection algorithms: Experiments and analyses." Pattern Recognition 74 (2018): 406-421.
  • Poirion, Olivier B., and Benedicte Lafay. "Neo-formation of chromosomes in bacteria." bioRxiv (2018): 264945.
  • de Melo, Vinícius Veloso, and Wolfgang Banzhaf. "Automatic feature engineering for regression models with machine learning: An evolutionary computation and statistics hybrid." Information Sciences 430 (2018): 287-313.
  • Giuliano, Christopher J., et al. "MELK expression correlates with tumor mitotic activity but is not required for cancer growth." eLife 7 (2018).
  • De Vries, Stefan PW, et al. "Phylogenetic analyses and antimicrobial resistance profiles of Campylobacter spp. from diarrhoeal patients and chickens in Botswana." PloS one 13.3 (2018): e0194481.

2017

  • Cherifi, Nadir, et al. "Automatic Inference of Energy Models for Peripheral Components in Embedded Systems." FiCloud 2017: The 5th International Conference on Future Internet of Things and Cloud. 2017.
  • Lowe, Andrew John. "Language-agnostic data analysis workflows and reproducible research." (2017).
  • Alexander, William M., et al. "multiplierz v2. 0: a Python‐based ecosystem for shared access and analysis of native mass spectrometry data." Proteomics (2017).
  • Liu, Lingjie, et al. "An approach of identifying differential nucleosome regions in multiple samples." BMC genomics 18.1 (2017): 135.
  • Olesen, Scott W., Claire Duvallet, and Eric J. Alm. "dbOTU3: A new implementation of distribution-based OTU calling." PloS one 12.5 (2017): e0176335.
  • Peacock, Jacob, and Harish Sethu. "Which Leaflet is More Effective: A Reanalysis." (2017).
  • Sharker, Yushuf, and Eben Kenah. "Estimation of the Household Secondary Attack Rate: Binomial Considered Harmful." arXiv preprint arXiv:1705.01135 (2017).
  • Domingues, Rémi, et al. "A comparative evaluation of outlier detection algorithms: experiments and analyses." Pattern Recognition (2017).
  • Zhao, Xuefang, Alexandra M. Weber, and Ryan E. Mills. "A recurrence based approach for validating structural variation using long-read sequencing technology." bioRxiv (2017): 105817.
  • Laycock, Silas GT. "From blackbirds to black holes: Investigating capture-recapture methods for time domain astronomy." New Astronomy 54 (2017): 91-102.
  • Chiera, Belinda A., and Małgorzata W. Korolkiewicz. "Visualizing Big Data: Everything Old Is New Again." Big Data Management. Springer International Publishing, 2017. 1-27.
  • Amarante, Linda M., Marcelo S. Caetano, and Mark Laubach. "Medial frontal theta is entrained to rewarded actions." Journal of Neuroscience (2017): 1965-17.

2016

  • Freer, Rosie, et al. "A protein homeostasis signature in healthy brains recapitulates tissue vulnerability to Alzheimer’s disease." Science Advances 2.8 (2016): e1600947.
  • Haslwanter, Thomas. An Introduction to Statistics with Python. Springer, 2016.
  • Ekmekci, Berk, Charles E. McAnany, and Cameron Mura. "An Introduction to Programming for Bioscientists: A Python-Based Primer." PLoS Comput Biol 12.6 (2016): e1004867.
  • Analyzing genomics data at scale with R, AWS Lambda and Amazon API gateway (AWS Compute Blog)
  • Anaya, Jordan. "OncoLnc: Linking TCGA survival data to mRNAs, miRNAs, and lncRNAs." PeerJ PrePrints 4 (2016): e1780v1.
  • Cleland, Edward John, et al. "The bacterial microbiome in chronic rhinosinusitis: Richness, diversity, postoperative changes, and patient outcomes." American journal of rhinology & allergy 30.1 (2016): 37-43.
  • Vandenbulcke, Hélène, et al. "Alcohol intake increases the risk of hepatocellular carcinoma in patients with hepatitis C virus-related compensated cirrhosis: a prospective study." Journal of hepatology (2016).
  • Jeong, Seongwoon, et al. "A NoSQL Data Management Infrastructure for Bridge Monitoring." (2016).
  • Kenah, Eben, et al. "Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees." PLoS Comput Biol 12.4 (2016): e1004869.
  • Kittas, Aristotelis, et al. "Organizational principles of the Reactome human BioPAX model using graph theory methods." Journal of Complex Networks (2016): cnw003.

2015

  • Zhang, Zhi-Min, et al. "Multiscale peak detection in wavelet space." Analyst 140.23 (2015): 7955-7964.
  • Woon, Wei Lee, et al. "Changes in Occupational Skills-A Case Study Using Non-negative Matrix Factorization." Neural Information Processing. Springer International Publishing, 2015.
  • Antao, Tiago. Bioinformatics with Python cookbook. Packt Publishing Ltd, 2015.
  • Terna, Pietro. "Introducing the Swarm-Like Agent Protocol in Python (SLAPP)." Agent-based Models of the Economy. Palgrave Macmillan UK, 2015. 31-54.

2014

  • Nakamura, Kunio, et al. "Correlation between brain volume change and T2 relaxation time induced by dehydration and rehydration: implications for monitoring atrophy in clinical studies." NeuroImage: Clinical 6 (2014): 166-170.
  • Filosi, Michele, et al. "ReNette: a web-infrastructure for reproducible network analysis." bioRxiv (2014): 008433.
  • Angeli, Nicole F., et al. A process to support species conservation planning and climate change readiness in protected areas. No. e492v2. PeerJ PrePrints, 2014.
  • Röst, Hannes L., et al. "pyOpenMS: A Python‐based interface to the OpenMS mass‐spectrometry algorithm library." Proteomics 14.1 (2014): 74-77.
  • Heavey, Cathal, et al. "Development of an open-source discrete event simulation cloud enabled platform." Proceedings of the 2014 Winter Simulation Conference. IEEE Press, 2014.
  • De Melo, Vinícius Veloso. "Kaizen programming." Proceedings of the 2014 conference on Genetic and evolutionary computation. ACM, 2014.
  • Onggo, B. S., et al. "TOWARDS AUTOMATED SIMULATION INPUT DATA." 8TH SIMULATION WORKSHOP. 2014.
  • Via, Allegra, Kristian Rother, and Anna Tramontano. Managing Your Biological Data with Python. CRC Press, 2014.
  • Brown, Robert A., Sridar Narayanan, and Douglas L. Arnold. "Imaging of repeated episodes of demyelination and remyelination in multiple sclerosis." NeuroImage: Clinical 6 (2014): 20-25.

2013

  • Krishnan, Hari, et al. "Exploring Collaborative HPC Visualization Workflows using VisIt and Python." Proceedings of the 12th Python in Science Conference (SciPy 2013). 2013.
  • Parks, Donovan H., et al. "GenGIS 2: Geospatial analysis of traditional and genetic biodiversity, with new gradient algorithms and an extensible plugin framework." PloS one 8.7 (2013): e69885.

2012

  • Harper, Marc, and Christopher J. Lee. "Genome-wide analysis of mutagenesis bias and context sensitivity of N-methyl-N′-nitro-N-nitrosoguanidine (NTG)." Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 731.1 (2012): 64-67.
  • Strickland, C. M., et al. "PyMCMC: A Python Package for Bayesian Estimation Using Markov Chain Monte Carlo." (2012).
  • Vitolo, Claudia, W. O. U. T. E. R. Buytaert, and D. Reusser. "Hydrological Models as Web Services: An Implementation Using OGC Standards." Proceedings of the 10th International Conference on Hydroinformatics, HIC, Hamburg, Germany. 2012.
  • Talevich, Eric, et al. "Bio. Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython." BMC bioinformatics 13.1 (2012): 1.
  • Bagger, Frederik Otzen, et al. "HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis." Nucleic acids research (2012): gks1021.

2011

  • Buske, Orion J., et al. "Exploratory analysis of genomic segmentations with Segtools." BMC bioinformatics 12.1 (2011): 1.
  • Tolk, A., et al. "TOWARDS AUTOMATED SIMULATION INPUT DATA: AN OPEN SOURCE TOOL TO ENHANCE THE INPUT DATA PHASE IN DISCRETE EVENT SIMULATION."
  • Patton, Evan W., et al. "SemNExT: A Framework for Semantically Integrating and Exploring Numeric Analyses."
  • Connolly, Daniel W., et al. "Integrating R efficiently to allow secure, interactive analysis within a clinical data warehouse." The 8th International R User Conference. Vanderbilt University.
  • Masica, David L., and Rachel Karchin. "Correlation of somatic mutation and expression identifies genes important in human glioblastoma progression and survival." Cancer research 71.13 (2011): 4550-4561.
  • Simone, James. "PoS (Lattice 2011) 048 Data analysis using the Gnu R system for statistical computation." (2011).
  • Liu, Sanmin, et al. "HDX-analyzer: a novel package for statistical analysis of protein structure dynamics." BMC bioinformatics 12.1 (2011): 1.

2009

  • Roseline, Bilina, and Steve Lawford. "Python for Unified Research in Econometrics and Statistics." Available at SSRN 1429822 (2009).
  • Wijffels, Jan. "Prediction and Fuzzy Logic at ThomasCook to automate price settings of last minute offers." (2009).
  • McBeth, Rafe. "Computational investigation of biological dose-volume outcome predictors in 29 canine nasal tumor patients treated with stereotactic radiation therapy." (2007).