chenhcs / GIANTLinks
GIANT (Gene-based data Integration and ANalysis Technique) is a method for large-scale joint analyses of atlas-level single cell data.
☆14Updated 2 years ago
Alternatives and similar repositories for GIANT
Users that are interested in GIANT are comparing it to the libraries listed below
Sorting:
- SMILE: Mutual Information Learning for Integration of Single Cell Omics Data☆11Updated 2 years ago
- ☆12Updated 4 years ago
- ☆19Updated 4 years ago
- ☆11Updated 2 years ago
- MOJITOO: a fast and universal method for integration of multimodal single cell data☆11Updated last year
- A sandbox for benchmarking detection of out-of-reference cells in single-cell genomics data☆13Updated last year
- Learning motif contributions to cell transitions using sequence features and graphs.☆28Updated last year
- ☆11Updated 2 years ago
- ☆12Updated 2 years ago
- ☆13Updated last year
- A single-cell analysis toolkit to jointly analyze samples from distinct conditions☆34Updated 8 months ago
- ☆12Updated 3 years ago
- Analysis of imbalanced data and its impacts in a scRNA-seq integration setting☆31Updated 9 months ago
- ☆15Updated 10 months ago
- ☆16Updated 2 years ago
- Learning meaningful representations of genes☆20Updated 5 months ago
- Breast Cancer Single Cell Atlas☆12Updated 3 years ago
- Single Cell Pretrained Regulatory network INference from Transcripts☆11Updated last year
- Gene Expression Decomposition and Integration☆19Updated 10 months ago
- ☆13Updated 10 months ago
- ☆13Updated 8 months ago
- Supporting material for publication: "Ovarian cancer mutational processes drive site-specific immune evasion"☆24Updated 7 months ago
- Code and example of the D-SPIN framework☆24Updated last week
- ☆12Updated 5 years ago
- python API to the CoGAPS NMF package☆19Updated 7 months ago
- ☆17Updated last year
- tumor - cancer cell line alignment. Use it on the depmap portal or install it with pip.☆11Updated 2 years ago
- single-cell Nucleosome Methylation Transcription☆14Updated 7 years ago
- R package for transfer learning of single-cell RNA-seq denoising☆30Updated 3 years ago
- Reworked clustering metrics for assessing performance in imbalanced settings☆17Updated last year