CellRank's reproducibility repository.

Overview

CellRank's reproducibility repository

We believe that reproducibility is key and have made it as simple as possible to reproduce our results. Please either open an issue or contact as at [email protected] should you experience difficulties reproducing any result.

Manuscript, code and data

CellRank is published in Nature Methods and the software package can be found at our main website, cellrank.org. Raw published data is available from the Gene Expression Omnibus (GEO) under accession codes:

Processed data, including spliced and unspliced count abundances, is available on figshare. To ease reproducibility, our data examples can also be accessed through CellRank's dataset interface.

Navigating this repository

We've organized this repository along the categories below. For each item, you can click the link under nbviewer to open the notebook in the browser using nbviewer. There is no 1-1 mapping from figures to notebooks - some notebooks produce panels for several figures, and some figures contain panels from several notebooks. The tables we provide here make the connection between figures and notebooks explicit. At the top of each notebook, we indicate the package versions we use.

Results

Main Figures
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Extended Data Figures
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Supplementary Figures
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Supplementary Fig. 17 NA (microscopy results) NA (microscopy results)
Supplementary Tables
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Owner
Theis Lab
Institute of Computational Biology
Theis Lab
Autonomous Movement from Simultaneous Localization and Mapping

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Tooling for GANs in TensorFlow

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The first dataset of composite images with rationality score indicating whether the object placement in a composite image is reasonable.

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Code and model benchmarks for "SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology"

NeurIPS 2020 SEVIR Code for paper: SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology Requirement

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PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

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Code for the ICCV2021 paper "Personalized Image Semantic Segmentation"

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Submission to Twitter's algorithmic bias bounty challenge

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MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble

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DiAne is a smart fuzzer for IoT devices

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Action Segmentation Evaluation

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