DataSheet_1_sc-ImmuCC: hierarchical annotation for immune cell types in single-cell RNA-seq.docx by Ying Jiang (5910)

“…Here, we developed a tool named sc-ImmuCC for hierarchical annotation of immune cell types from scRNA-Seq data, based on the optimized gene sets and ssGSEA algorithm. sc-ImmuCC simulates the natural differentiation of immune cells, and the hierarchical annotation includes three layers, which can annotate nine major immune cell types and 29 cell subtypes. …”

DataSheet_2_sc-ImmuCC: hierarchical annotation for immune cell types in single-cell RNA-seq.xlsx by Ying Jiang (5910)

“…Here, we developed a tool named sc-ImmuCC for hierarchical annotation of immune cell types from scRNA-Seq data, based on the optimized gene sets and ssGSEA algorithm. sc-ImmuCC simulates the natural differentiation of immune cells, and the hierarchical annotation includes three layers, which can annotate nine major immune cell types and 29 cell subtypes. …”

Table 1_CEACAM6 as a machine learning derived immune biomarker for predicting neoadjuvant chemotherapy response in HR+/HER2− breast cancer.xlsx by Dalang Fang (22130155)

“…Gene set enrichment analysis (GSEA), CIBERSORT-based immune infiltration, and drug sensitivity prediction using oncoPredict and GDSC2 were performed. …”

Mis-splicing and breast cancer: systematic analysis of splicing variants of BRCA2 exons 2-9 by minigene assays by Eladio Andrés Velasco (3369893)

“…The low accuracy of ESE-prediction algorithms may be circumvented by functional ESE-mapping that represents an optimal strategy to identify spliceogenic ESE-variants. …”

Code by Baoqiang Chen (21099509)

“…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. …”

Core data by Baoqiang Chen (21099509)

“…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. …”