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1

GraphST

Python
83
star
2

Batch-effect-removal-benchmarking

A benchmark of batch-effect correction methods for single-cell RNA sequencing data
Jupyter Notebook
69
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3

cytofkit

cytofkit: an integrated flow/mass cytometry data analysis pipeline
R
57
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4

Rphenograph

Rphenograph: R implementation of the PhenoGraph algorithm
R
46
star
5

SEDR

Python
39
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6

SEDR_analyses

R
33
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7

ezSingleCell2

R
29
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8

SpatialGlue

SpatialGlue is a novel deep learning methods for spatial multi-omics data integration.
Python
28
star
9

FastIntegration

FastIntegrate integrates thousands of scRNA-seq datasets and outputs batch-corrected values for downstream analysis
R
22
star
10

cytofkit2

R
21
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11

DISCOtoolkit

R
19
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12

DISCO_manuscript

R
8
star
13

Mpath

Mpath: an algorithm for constructing multi-branching cell lineages from single-cell data
6
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14

DISCOtoolkit_py

Python version of DISCO toolkit
Python
6
star
15

ClusterX

ClusterX: Fast clustering by automatic search and find of density peaks
R
4
star
16

Bone_Marrow_Aging

R
3
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17

Harmony

R
2
star
18

GraphST_Tutorials

Python
2
star
19

cytofkit_analysis_data_code

The data and analysis scripts used in cytofkit paper
HTML
2
star
20

SpatialGlue_3M

Extended version of SpatialGlue for integration of spatial triplet modality data.
Python
2
star
21

uSORT

uSORT: A self-refining ordering pipeline for gene selection
R
1
star
22

DISCO_learning

Tell you how to use DISCO effectively
Jupyter Notebook
1
star
23

SpatialGlue_tutorials

The tutorial is to show how to apply SpatialGlue to integrate spatial multi-omics data to decipher tissue heterogeneity.
Python
1
star
24

heart_aging

The codes for the manuscript about heart aging
R
1
star