Succinct Representation of Single Cells

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ZengFLab from gravatar.com ZengFLab

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: Feng Zeng
  • Requires: Python >=3.10
Classifiers
Report project as malware

Project description

SURE: SUccinct REpresentation of cells

SURE introduces a vector quantization-based probabilistic generative model for calling metacells and use them as landmarks that form a coordinate system for cell ID. Analyzing single-cell omics data in a manner analogous to reference genome-based genomic analysis.

$$\color{red}\text{\textbf{UPDATE}}$$

An update has been distributed. Users can access to it via SUREv2. It provides Python classes that users can call SURE in scripts. It also provide the command that users can run SURE in the shell. Additionally, SUREv2 supports the calling of metacells for multi-omics datasets.

Installation

  1. Create a virtual environment
conda create -n SUREv1 python=3.10 scipy numpy pandas scikit-learn && conda activate SUREv1
  1. Install PyTorch following the official instruction.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
  1. Install SURE
pip3 install SURE-tools

Example 1: Calling metacells for a single-cell dataset

Users can refer to here for details.

Example 2: The hierarchical assembly of large-scale dataset(s)

Users can refer to here for details.

Example 3: Human brain cell atlas

Users can refer to here for details.

Example 4: Metacell calling for scATAC-seq data

Users can refer to here for details.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ZengFLab from gravatar.com ZengFLab

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: Feng Zeng
  • Requires: Python >=3.10
Classifiers

Release history Release notifications | RSS feed

4.8.9

4.8.8

4.8.7

4.8.6

4.8.5

4.8.4

4.8.3

4.8.2

4.8.1

4.8.0

4.7.8

4.7.7

4.7.6

4.7.5

4.7.4

4.7.3

4.7.2

4.7.1

4.7.0

4.6.10

4.6.9

4.6.8

4.6.7

4.6.6

4.6.5

4.6.4

4.6.3

4.6.2

4.6.1

4.6.0

4.5.18

4.5.17

4.5.16

4.5.15

4.5.14

4.5.13

4.5.12

4.5.11

4.5.10

4.5.9

4.5.8

4.5.7

4.5.6

4.5.5

4.5.4

4.5.3

4.5.2

4.5.1

4.5.0

4.4.10

4.4.9

4.4.8

4.4.7

4.4.6

4.4.5

4.4.4

4.4.3

4.4.2

4.4.1

4.4.0

4.3.0

4.2.6

4.2.5

4.2.4

4.2.3

4.2.2

4.2.1

4.2.0

4.1.1

4.1.0

4.0.30

4.0.29

4.0.28

4.0.27

4.0.26

4.0.25

4.0.24

4.0.23

4.0.22

4.0.21

4.0.20

4.0.19

4.0.18

4.0.17

4.0.16

4.0.15

4.0.14

4.0.13

4.0.12

4.0.11

4.0.10

4.0.9

4.0.8

4.0.7

4.0.6

4.0.5

4.0.4

4.0.3

4.0.2

4.0.1

4.0.0

3.7.4

3.7.3

3.7.2

3.7.1

3.7.0

3.6.14

3.6.13

3.6.12

3.6.11

3.6.10

3.6.9

3.6.8

3.6.7

3.6.6

3.6.5

3.6.4

3.6.3

3.6.2

3.6.1

3.6.0

3.5.27

3.5.26

3.5.25

3.5.24

3.5.23

3.5.22

3.5.21

3.5.20

3.5.19

3.5.18

3.5.17

3.5.16

3.5.15

3.5.14

3.5.13

3.5.12

3.5.11

3.5.10

3.5.9

3.5.8

3.5.7

3.5.6

3.5.5

3.5.4

3.5.3

3.5.2

3.5.1

3.5.0

3.4.29

3.4.28

3.4.27

3.4.26

3.4.25

3.4.24

3.4.23

3.4.22

3.4.21

3.4.20

3.4.19

3.4.18

3.4.17

3.4.16

3.4.15

3.4.14

3.4.13

3.4.12

3.4.10

3.4.9

3.4.8

3.4.7

3.4.6

3.4.5

3.4.4

3.4.3

3.4.2

3.4.1

3.4.0

3.3.37

3.3.36

3.3.35

3.3.34

3.3.33

3.3.32

3.3.31

3.3.30

3.3.29

3.3.28

3.3.27

3.3.26

3.3.25

3.3.24

3.3.23

3.3.22

3.3.21

3.3.20

3.3.19

3.3.18

3.3.17

3.3.16

3.3.15

3.3.14

3.3.13

3.3.12

3.3.11

3.3.10

3.3.9

3.3.8

3.3.7

3.3.6

3.3.5

3.3.4

3.3.3

3.3.2

3.3.1

3.3.0

3.2.41

3.2.40

3.2.39

3.2.38

3.2.37

3.2.36

3.2.35

3.2.34

3.2.33

3.2.32

3.2.31

3.2.30

3.2.29

3.2.28

3.2.27

3.2.26

3.2.25

3.2.24

3.2.23

3.2.22

3.2.21

3.2.20

3.2.19

3.2.18

3.2.17

3.2.16

3.2.15

3.2.14

3.2.13

3.2.12

3.2.11

3.2.10

3.2.9

3.2.8

3.2.7

3.2.6

3.2.5

3.2.4

3.2.3

3.2.2

3.2.1

3.2.0

3.1.9

3.1.8

3.1.7

3.1.6

3.1.5

3.1.4

3.1.3

3.1.2

3.1.1

3.1.0

3.0.10

3.0.9

3.0.8

3.0.7

3.0.6

3.0.5

3.0.4

3.0.3

3.0.2

3.0.1

3.0.0

2.4.104

2.4.103

2.4.102

2.4.101

2.4.100

2.4.99

2.4.98

2.4.97

2.4.96

2.4.95

2.4.94

2.4.93

2.4.92

2.4.91

2.4.90

2.4.89

2.4.88

2.4.87

2.4.86

2.4.85

2.4.84

2.4.83

2.4.82

2.4.81

2.4.80

2.4.79

2.4.78

2.4.77

2.4.76

2.4.75

2.4.74

2.4.73

2.4.72

2.4.71

This version

2.4.70

2.4.69

2.4.68

2.4.67

2.4.66

2.4.65

2.4.64

2.4.63

2.4.60

2.4.59

2.4.58

2.4.57

2.4.56

2.4.55

2.4.54

2.4.53

2.4.52

2.4.51

2.4.50

2.4.49

2.4.48

2.4.47

2.4.45

2.4.44

2.4.43

2.4.42

2.4.41

2.4.40

2.4.39

2.4.38

2.4.37

2.4.36

2.4.35

2.4.34

2.4.33

2.4.32

2.4.31

2.4.29

2.4.28

2.4.25

2.4.24

2.4.23

2.4.22

2.4.21

2.4.20

2.4.19

2.4.18

2.4.17

2.4.16

2.4.15

2.4.14

2.4.13

2.4.12

2.4.11

2.4.10

2.4.9

2.4.8

2.4.7

2.4.6

2.4.5

2.4.4

2.4.3

2.4.2

2.4.1

2.4.0

2.3.2

2.3.1

2.3.0

2.2.28

2.2.27

2.2.26

2.2.25

2.2.24

2.2.23

2.2.21

2.2.20

2.2.19

2.2.18

2.2.17

2.2.16

2.2.15

2.2.14

2.2.13

2.2.12

2.2.11

2.2.10

2.2.9

2.2.8

2.2.7

2.2.6

2.2.5

2.2.4

2.2.3

2.2.2

2.2.1

2.2.0

2.1.92

2.1.91

2.1.90

2.1.89

2.1.88

2.1.87

2.1.86

2.1.85

2.1.84

2.1.83

2.1.82

2.1.81

2.1.80

2.1.79

2.1.78

2.1.77

2.1.76

2.1.74

2.1.73

2.1.71

2.1.70

2.1.69

2.1.68

2.1.67

2.1.66

2.1.65

2.1.64

2.1.63

2.1.62

2.1.61

2.1.60

2.1.59

2.1.58

2.1.57

2.1.56

2.1.55

2.1.54

2.1.53

2.1.52

2.1.51

2.1.50

2.1.49

2.1.48

2.1.47

2.1.46

2.1.45

2.1.44

2.1.43

2.1.42

2.1.41

2.1.40

2.1.39

2.1.38

2.1.37

2.1.36

2.1.35

2.1.34

2.1.33

2.1.32

2.1.31

2.1.30

2.1.29

2.1.28

2.1.27

2.1.26

2.1.25

2.1.24

2.1.22

2.1.21

2.1.20

2.1.19

2.1.18

2.1.17

2.1.16

2.1.15

2.1.14

2.1.13

2.1.12

2.1.11

2.1.10

2.1.9

2.1.8

2.1.7

2.1.6

2.1.5

2.1.4

2.1.3

2.1.2

2.1.1

2.1.0

2.0.10

2.0.9

2.0.8

2.0.7

2.0.6

2.0.5

2.0.4

2.0.3

2.0.2

2.0.1

1.0.10

1.0.9

1.0.8

1.0.7

1.0.6

1.0.5

1.0.4

1.0.3

1.0.2

1.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sure_tools-2.4.70.tar.gz (85.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sure_tools-2.4.70-py3-none-any.whl (116.2 kB view details)

Uploaded Python 3

File details

Details for the file sure_tools-2.4.70.tar.gz.

File metadata

  • Download URL: sure_tools-2.4.70.tar.gz
  • Upload date:
  • Size: 85.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for sure_tools-2.4.70.tar.gz
Algorithm Hash digest
SHA256 5a17685877081b3a0a7887f9aa0622fd304023efc68598ec3185caf6e6fd6a24
MD5 a78bfc365171fa6e6145ee5d830d224a
BLAKE2b-256 273a3b6d6bb71cce5b72a2d0eaea19afcb45cddc586bbb4b7f357a5241376d41

See more details on using hashes here.

File details

Details for the file sure_tools-2.4.70-py3-none-any.whl.

File metadata

  • Download URL: sure_tools-2.4.70-py3-none-any.whl
  • Upload date:
  • Size: 116.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for sure_tools-2.4.70-py3-none-any.whl
Algorithm Hash digest
SHA256 5754632e81792cc9445902c61ea3eb19c3aac5237ed3074310c20249f0c33904
MD5 493d0a4ba20d052ff89ec8fa3a5fbcfe
BLAKE2b-256 3281c088c0025fc9305e63f20076f63bb4cff382f1fbada80cd25648e240e023

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page