CellRank's reproducibility repository.

Last update: Oct 08, 2022

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

Figure	nbviewer	Notebook Path
Fig. 1	link	path
Fig. 2	link	path
Fig. 3	link	path
Fig. 4	link	path
Fig. 5 Palantir	link	path
Fig. 5 STEMNET	link	path
Fig. 5 Velocyto	link	path
Fig. 5 FateID	link	path
Fig. 6	link	path

Extended Data Figures

Figure	nbviewer	Notebook Path
Extended Data Fig. 1	NA (toy data)	NA (toy data)
Extended Data Fig. 2	link	path
Extended Data Fig. 3	link	path
Extended Data Fig. 4	link	path
Extended Data Fig. 5	link	path
Extended Data Fig. 6	link	path
Extended Data Fig. 7	link	path
Extended Data Fig. 8	link	path
Extended Data Fig. 9	link	path
Extended Data Fig. 10	link	path

Supplementary Figures

Figure	nbviewer	Notebook Path
Supplementary Fig. 1	link	path
Supplementary Fig. 2	link	path
Supplementary Fig. 3	link	path
Supplementary Fig. 4	link	path
Supplementary Fig. 5	link	path
Supplementary Fig. 6	link	path
Supplementary Fig. 7	link	path
Supplementary Fig. 8	link	path
Supplementary Fig. 9	link	path
Supplementary Fig. 10	link	path
Supplementary Fig. 11	link	path
Supplementary Fig. 12	link1 link2	path1 path2
Supplementary Fig. 13	link	path
Supplementary Fig. 14	link	path
Supplementary Fig. 15	link	path
Supplementary Fig. 16	link	path
Supplementary Fig. 17	NA (microscopy results)	NA (microscopy results)

Supplementary Tables

Table	nbviewer	Notebook Path
Supplementary Tab. 1	link	path
Supplementary Tab. 2	link	path
Supplementary Tab. 3	link	path

CellRank's reproducibility repository.

Related tags

Overview

CellRank's reproducibility repository

Manuscript, code and data

Navigating this repository

Results

Owner

Theis Lab

Official repository of the paper Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision

GULAG: GUessing LAnGuages with neural networks

Randomizes the warps in a stock pokeemerald repo.

Pytorch implementation of YOLOX、PPYOLO、PPYOLOv2、FCOS an so on.

Code for Blind Image Decomposition (BID) and Blind Image Decomposition network (BIDeN).

The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

OoD Minimum Anomaly Score GAN - Code for the Paper 'OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary'

OCR-D wrapper for detectron2 based segmentation models

Vehicles Counting using YOLOv4 + DeepSORT + Flask + Ngrok

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning

AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"

Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Official Repository of NeurIPS2021 paper: PTR

DAN: Unfolding the Alternating Optimization for Blind Super Resolution

Code for KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs