Science Score: 67.0%
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✓codemeta.json file
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✓DOI references
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Low similarity (4.4%) to scientific vocabulary
Keywords
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Repository
Multimodal Data (.h5mu) implementation for Python
Basic Info
- Host: GitHub
- Owner: scverse
- License: bsd-3-clause
- Language: Python
- Default Branch: main
- Homepage: https://mudata.rtfd.io
- Size: 1.05 MB
Statistics
- Stars: 99
- Watchers: 6
- Forks: 20
- Open Issues: 14
- Releases: 10
Topics
Metadata Files
README.md
MuData – multimodal data
For using MuData in multimodal omics applications see muon.
Data structure
In the same vein as AnnData is designed to represent unimodal annotated datasets in Python, MuData is designed to provide functionality to load, process, and store multimodal omics data.
MuData
.obs -- annotation of observations (cells, samples)
.var -- annotation of features (genes, genomic loci, etc.)
.obsm -- multidimensional cell annotation,
incl. a boolean for each modality
that links .obs to the cells of that modality
.varm -- multidimensional feature annotation,
incl. a boolean vector for each modality
that links .var to the features of that modality
.mod
AnnData
.X -- data matrix (cells x features)
.obs -- cell metadata (assay-specific)
.var -- annotation of features (genes, peaks, genomic sites)
.obsm
.varm
.uns
.uns
Overview
Input
MuData can be thought of as a multimodal container, in which every modality is an AnnData object:
```py from mudata import MuData
mdata = MuData({'rna': adatarna, 'atac': adataatac}) ```
If multimodal data from 10X Genomics is to be read, convenient readers are provided by muon that return a MuData object with AnnData objects inside, each corresponding to its own modality:
```py import muon as mu
mu.read10xh5("filteredfeaturebc_matrix.h5")
MuData object with nobs × nvars = 10000 × 80000
2 modalities
rna: 10000 x 30000
var: 'geneids', 'featuretypes', 'genome', 'interval'
atac: 10000 x 50000
var: 'geneids', 'featuretypes', 'genome', 'interval'
uns: 'atac', 'files'
```
I/O with .h5mu files
MuData objects represent modalities as collections of AnnData objects. These collections can be saved to disk and retrieved using HDF5-based .h5mu files, which design is based on .h5ad file structure.
```py import mudata as md
mdatapbmc.write("pbmc10k.h5mu") mdata = md.read("pbmc_10k.h5mu") ```
It allows to effectively use the hierarchical nature of HDF5 files and to read/write AnnData object directly from/to .h5mu files:
py
adata = md.read("pbmc_10k.h5mu/rna")
md.write("pbmc_10k.h5mu/rna", adata)
Citation
If you use mudata in your work, please cite the publication as follows:
MUON: multimodal omics analysis framework
Danila Bredikhin, Ilia Kats, Oliver Stegle
Genome Biology 2022 Feb 01. doi: 10.1186/s13059-021-02577-8.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
mudata is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
Owner
- Name: scverse
- Login: scverse
- Kind: organization
- Website: https://scverse.org
- Twitter: scverse_team
- Repositories: 28
- Profile: https://github.com/scverse
Foundational tools for omics data in the life sciences
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Bredikhin"
given-names: "Danila"
orcid: "https://orcid.org/0000-0001-8089-6983"
- family-names: "Kats"
given-names: "Ilia"
orcid: "https://orcid.org/0000-0001-5220-5671"
title: "muon"
version: 1.0.0
date-released: 2021-06-01
url: "https://github.com/scverse/muon"
preferred-citation:
type: article
authors:
- family-names: "Bredikhin"
given-names: "Danila"
orcid: "https://orcid.org/0000-0001-8089-6983"
- family-names: "Kats"
given-names: "Ilia"
orcid: "https://orcid.org/0000-0001-5220-5671"
- family-names: "Stegle"
given-names: "Oliver"
orcid: "https://orcid.org/0000-0002-8818-7193"
doi: "10.1186/s13059-021-02577-8"
journal: "Genome Biology"
month: 2
title: "MUON: multimodal omics analysis framework"
year: 2022
GitHub Events
Total
- Create event: 2
- Release event: 1
- Issues event: 25
- Watch event: 22
- Issue comment event: 22
- Push event: 19
- Pull request event: 8
- Fork event: 4
Last Year
- Create event: 2
- Release event: 1
- Issues event: 25
- Watch event: 22
- Issue comment event: 22
- Push event: 19
- Pull request event: 8
- Fork event: 4
Committers
Last synced: 6 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Danila Bredikhin | d****n@e****e | 454 |
| Ilia Kats | i****s@g****t | 83 |
| mkeller | 7****k | 5 |
| ilan-gold | i****d@g****m | 5 |
| Max Frank | m****k@g****m | 4 |
| Wouter-Michiel Vierdag | w****v@h****m | 3 |
| Isaac Virshup | i****p@g****m | 3 |
| bv2 | b****n@g****m | 3 |
| Isaac E | m****y@g****m | 2 |
| Philipp Weiler | w****p@g****m | 2 |
| Lukas Heumos | l****s@p****t | 2 |
| Jeongbin Park | p****7@g****m | 1 |
| Michaela Müller | 5****e | 1 |
| Robrecht Cannoodt | r****d@g****m | 1 |
| mikelkou | m****i@c****k | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 5 months ago
All Time
- Total issues: 68
- Total pull requests: 39
- Average time to close issues: 8 months
- Average time to close pull requests: 3 months
- Total issue authors: 41
- Total pull request authors: 13
- Average comments per issue: 2.44
- Average comments per pull request: 0.92
- Merged pull requests: 27
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 17
- Pull requests: 12
- Average time to close issues: 2 months
- Average time to close pull requests: 12 days
- Issue authors: 12
- Pull request authors: 3
- Average comments per issue: 1.41
- Average comments per pull request: 0.83
- Merged pull requests: 7
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ivirshup (9)
- gtca (7)
- grst (5)
- Zethson (4)
- scverse-bot (4)
- emdann (2)
- racng (2)
- bio-la (2)
- ouyaqing (1)
- mumichae (1)
- Imipenem (1)
- joshchiou (1)
- martinkim0 (1)
- raozuming (1)
- danli349 (1)
Pull Request Authors
- gtca (26)
- ilan-gold (7)
- ilia-kats (4)
- votti (4)
- IsaacUtah1379 (2)
- martinkim0 (2)
- keller-mark (1)
- mffrank (1)
- Zethson (1)
- rcannood (1)
- mumichae (1)
- ivirshup (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
-
Total downloads:
- pypi 65,477 last-month
- Total docker downloads: 7,246
-
Total dependent packages: 26
(may contain duplicates) -
Total dependent repositories: 12
(may contain duplicates) - Total versions: 17
- Total maintainers: 1
pypi.org: mudata
Multimodal data
- Documentation: https://mudata.readthedocs.io/en/latest/
- License: BSD License
-
Latest release: 0.3.2
published 8 months ago
Rankings
Maintainers (1)
conda-forge.org: mudata
- Homepage: https://github.com/scverse/mudata
- License: BSD-3-Clause
-
Latest release: 0.2.0
published over 3 years ago
Rankings
Dependencies
- anndata *
- mudata *
- numpy *
- pandas *
- actions/checkout v2 composite
- actions/setup-python v2 composite
- psf/black stable composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- codecov/codecov-action v2 composite
- actions/checkout v2 composite
- actions/setup-python v1 composite
- actions/checkout v2 composite
- actions/setup-python v1 composite