Skip to main content

stagewiseNN

stagewiseNN is a computational tool for constructing developmental tree from Multi-staged single-cell RNA-seq data.

(see StagewiseNN Documentation for detailed guides)

It starts from building a single-cell graph by connecting each cell to its k-nearest neighbors in the parent stage, followed by voting-based tree-construction and adaptive cluster refinement.

StagewiseNN

It is easy to use:

import swnn

# ====== Inputs ======
# data_matrix = ..
# stage_labels = ..
# group_labels = ..
# stage_order = [f'stage_{i}' for i in range(5)]

builder = swnn.Builder(stage_order=stage_order)
# step 1:
# building (stage-wise) single-cell graph
distmat, connect = builder.build_graph(
        X=data_matrix, stage_lbs=stage_labels,
    )
# step 2:
# build developmental tree from single-cell graph
builder.build_tree(group_labels, stage_labels,)

Installation

Requirements:

Install stagewiseNN by running (in the command line):

pip install swnn

or install from source code:

git clone https://github.com/zhanglabtools/stagewiseNN.git
cd stagewiseNN
python setup.py install

Contribute

Support

If you are having issues, please let us know. We have a mailing list located at:

Citation

If you find StagewiseNN helps, Please cite:

Pengcheng Ma, Xingyan Liu, Zaoxu Xu et al. Joint profiling of gene expression and chromatin accessibility of amphioxus development at single cell resolution, 18 May 2021, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-504113/v1]

Release files for swnn 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for swnn 0.1.0
File Size Uploaded
swnn-0.1.0.tar.gz 19.7 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for swnn 0.1.0
File Interpreter ABI Platform
swnn-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 19.7 MB

Release files / swnn-0.1.0.tar.gz

Download URL swnn-0.1.0.tar.gz
Size 19.7 MB
Tags Source
SHA-256 checksum
How to use checksums
9f6fa95eea985495d20b2437a64eb7f3aa847fc173eebc06a57288e05f1207ba
BLAKE2b-256 checksum
How to use checksums
31aaed6f802438726d030779e09044b2664b39053ed5eef17744e5d591c51f0e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.8.8

Release files / swnn-0.1.0-py3-none-any.whl

Download URL swnn-0.1.0-py3-none-any.whl
Size 18.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3b721ad7a1bb2452787afe112972d41e86e994a80b5f40d0aa979ce126296fc5
BLAKE2b-256 checksum
How to use checksums
27aa1a8cc256d5246bb5691ea71a846489d61f0112d98f8afefb560636d61c2c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.8.8

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page