MAGMA

SHORT NAME: MAGMA
FULL NAME: Multi-marker Analysis of GenoMic Annotation
YEAR : 2015
URL: https://ctg.cncr.nl/software/magma
CITATION: de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015). MAGMA: generalized gene-set analysis of GWAS data. PLoS computational biology, 11(4), e1004219.

LDSC-SEG

SHORT NAME:LDSC-SEG
FULL NAME: LD score regression applied to specifically expressed genes
YEAR : 2018
URL: https://github.com/bulik/ldsc
CITATION:Finucane, H. K., Reshef, Y. A., Anttila, V., Slowikowski, K., Gusev, A., Byrnes, A., ... & Price, A. L. (2018). Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nature genetics, 50(4), 621-629.
KEY WORD: LDSC, tissue, cell type

SHORT NAME:scDRS
FULL NAME: single-cell Disease Relevance Score
YEAR : 2022
URL: https://github.com/martinjzhang/scDRS
CITATION:Zhang, M.J., Hou, K., Dey, K.K. et al. Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data. Nat Genet (2022). https://doi.org/10.1038/s41588-022-01167-z
KEY WORD: GWAS, scRNA-seq

SHORT NAME:SCAVENGE
FULL NAME: Single Cell Analysis of Variant Enrichment through Network propagation of GEnomic data
URL: https://github.com/sankaranlab/SCAVENGE
YEAR : 2022
CITATION: Yu, F., Cato, L.D., Weng, C. et al. Variant to function mapping at single-cell resolution through network propagation. Nat Biotechnol (2022). https://doi.org/10.1038/s41587-022-01341-y
KEY WORD: GWAS, scATAC-seq, network propagation

SHORT NAME: sc-linker
FULL NAME: sc-linker
URL:https://karthikj89-scgenetics-wwwscgwas-ktmead.streamlitapp.com/
URL:https://alkesgroup.broadinstitute.org/LDSCORE/Jagadeesh_Dey_sclinker/
YEAR : 2022
DESCRIPTION: a framework for integrating single-cell RNA-sequencing, epigenomic SNP-to-gene maps and genome-wide association study summary statistics to infer the underlying cell types and processes by which genetic variants influence disease
CITATION: Yu, F., Cato, L.D., Weng, C. et al. Variant to function mapping at single-cell resolution through network propagation. Nat Biotechnol (2022). https://doi.org/10.1038/s41587-022-01341-y
KEY WORD: GWAS, scRNA-seq

FULL NAME:scRNA-seq assisted GWAS analysis
SHORT NAME:scGWAS
URL:https://github.com/bsml320/scGWAS
DESCRIPTION:scGWAS leverages scRNA-seq data to identify the genetically mediated associations between traits and cell types.
CITATION: Jia, P., Hu, R., Yan, F., Dai, Y., & Zhao, Z. (2022). scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies. Genome biology, 23(1), 1-24.

SHORT NAME:SCENT
FULL NAME: single-cell enhancer target gene mapping
URL: https://github.com/immunogenomics/SCENT
YEAR : 2024
CITATION: Sakaue, S., Weinand, K., Isaac, S., Dey, K. K., Jagadeesh, K., Kanai, M., ... & Raychaudhuri, S. (2024). Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles. Nature Genetics, 1-12.
KEY WORD: Possion regression, scATAC-seq, scRNA-seq

SHORT NAME:SCARlink
FULL NAME: single-cell ATAC + RNA linking
URL: https://github.com/snehamitra/SCARlink/
YEAR : 2024
CITATION: Mitra, S., Malik, R., Wong, W., Rahman, A., Hartemink, A. J., Pritykin, Y., ... & Leslie, C. S. (2024). Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis. Nature Genetics, 1-10.
KEY WORD: Possion regression, scATAC-seq, scRNA-seq, tile-level accessibility

SHORT NAME:SCAVENGE
FULL NAME: Single Cell Analysis of Variant Enrichment through Network propagation of GEnomic data
URL: https://github.com/sankaranlab/SCAVENGE
YEAR : 2022
CITATION: Yu, F., Cato, L.D., Weng, C. et al. Variant to function mapping at single-cell resolution through network propagation. Nat Biotechnol (2022). https://doi.org/10.1038/s41587-022-01341-y
KEY WORD: GWAS, scATAC-seq, network propagation

SHORT NAME: EPIC
FULL NAME: cEll tyPe enrIChment
URL: https://github.com/rujinwang/EPIC
YEAR : 2022
DESCRIPTION: Inferring relevant tissues and cell types for complex traits in genome-wide association studies
CITATION: Wang, R., Lin, D. Y., & Jiang, Y. (2022). EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing. PLoS genetics, 18(6), e1010251.
KEY WORD: GWAS, scRNA-seq

SHORT NAME: TCSC
FULL NAME: Tissue co-regulation score regression
URL: https://github.com/TiffanyAmariuta/TCSC/
YEAR : 2022
DESCRIPTION: TCSC is a statistical genetics method to identify causal tissues in diseases and complex traits. We leverage TWAS and GWAS summary statistics while explicitly modeling the genetic co-regulation of genes across tissues.
KEY WORD: Amariuta, Tiffany, Katie Siewert-Rocks, and Alkes L. Price. "Modeling tissue co-regulation to estimate tissue-specific contributions to disease." bioRxiv (2022).