SKCM-095-03-1A
De-identified Human Immune Atlas donor/sample detail for CancerSCEM 2.0. The record preserves available public metadata while avoiding direct identifiers.
Donor-Level Analysis Results
Matrix-backed CancerSCEM donor analysis for SKCM-095-03-1A, generated 2026-07-09 12:54:49 +0800.
2,000Cells analyzed
20Clusters
25,112Expressed genes
7266Mean UMI
2083Mean genes
2.972Mean mito %
Gene Program Summary
| Program | Clusters | Mean Score | Max Score | Genes Used |
|---|---|---|---|---|
| B_plasma | 20 | 0.7518 | 3.1097 | 8 |
| Myeloid_APC | 20 | 0.5644 | 1.8748 | 9 |
| T_NK_cytotoxic | 20 | 0.3512 | 1.2481 | 10 |
| Checkpoint_exhaustion | 20 | 0.1845 | 0.5927 | 8 |
| Proliferation | 20 | 0.1338 | 1.2033 | 7 |
| Fibroblast_stroma | 20 | 0.0736 | 1.1998 | 8 |
| Endothelial | 20 | 0.0431 | 0.1617 | 7 |
| Epithelial_tumor | 20 | 0.0127 | 0.0735 | 8 |
Cluster QC
| Cluster | Cells | Mean UMI | Median Genes | Mean Mito % |
|---|---|---|---|---|
| cluster_1 | 355 | 4892.569 | 1816 | 3.0045 |
| cluster_2 | 284 | 4495.4472 | 1765 | 2.6953 |
| cluster_3 | 253 | 5941.8893 | 2096 | 2.5707 |
| cluster_4 | 163 | 10835.8834 | 3348 | 3.8353 |
| cluster_5 | 150 | 6129.4133 | 2018.5 | 3.9618 |
| cluster_6 | 148 | 7669.277 | 2331 | 3.7484 |
| cluster_7 | 97 | 11956.6804 | 2924 | 2.8727 |
| cluster_8 | 96 | 1115.0521 | 458.5 | 0.8241 |
| cluster_9 | 72 | 4310.5 | 1879.5 | 3.226 |
| cluster_10 | 69 | 41038.4493 | 3175 | 1.2087 |
| cluster_11 | 51 | 2958.0784 | 1042 | 4.0077 |
| cluster_12 | 47 | 1198.8298 | 566 | 3.8819 |
| cluster_13 | 45 | 6410.6 | 2359 | 2.4434 |
| cluster_14 | 35 | 5721.5143 | 2007 | 2.814 |
| cluster_15 | 34 | 6110.2059 | 2115.5 | 2.8495 |
| cluster_16 | 31 | 5554.2903 | 949 | 4.218 |
| cluster_17 | 29 | 11086.2414 | 3445 | 2.4874 |
| cluster_18 | 22 | 8467.0455 | 2898.5 | 1.9412 |
| cluster_19 | 13 | 9876.4615 | 2640 | 4.1036 |
| cluster_20 | 6 | 12235.6667 | 2588 | 3.9211 |
Top Cluster Marker Genes
| Cluster | Rank | Gene | Score | Mean Expr | Detect Fraction |
|---|---|---|---|---|---|
| cluster_10 | 1 | IGKC | 5.8999 | 7.8869 | 1 |
| cluster_7 | 1 | IL1B | 3.808 | 4.2972 | 1 |
| cluster_19 | 1 | IGFBP7 | 3.5286 | 3.5804 | 1 |
| cluster_6 | 1 | S100A9 | 3.2468 | 3.7863 | 0.9459 |
| cluster_11 | 1 | TPSB2 | 3.1539 | 3.1669 | 1 |
| cluster_20 | 1 | TBC1D4 | 3.1014 | 3.3379 | 1 |
| cluster_9 | 1 | GNLY | 2.9054 | 2.9974 | 0.9444 |
| cluster_4 | 1 | APOE | 2.8734 | 3.1436 | 0.9202 |
| cluster_18 | 1 | GZMB | 2.6108 | 2.8259 | 0.9091 |
| cluster_16 | 1 | HLA-DRA | 2.2176 | 3.8473 | 1 |
| cluster_2 | 1 | CCL5 | 2.0765 | 2.5817 | 0.9754 |
| cluster_5 | 1 | HLA-DRA | 2.0588 | 3.5684 | 1 |
| cluster_17 | 1 | HMGB2 | 2.0238 | 2.4015 | 0.9655 |
| cluster_8 | 1 | CXCL8 | 1.7737 | 2.5631 | 0.9375 |
| cluster_15 | 1 | XCL1 | 1.7141 | 1.7704 | 0.7353 |
| cluster_3 | 1 | IL32 | 1.6973 | 2.4675 | 0.9644 |
| cluster_13 | 1 | RORA | 1.6407 | 2.1718 | 0.9778 |
| cluster_12 | 1 | MGP | 1.6179 | 1.698 | 0.8936 |
| cluster_14 | 1 | TSHZ2 | 1.352 | 1.4992 | 0.8286 |
| cluster_1 | 1 | ZFP36L2 | 1.0556 | 2.3319 | 0.9746 |
| cluster_10 | 2 | IGHG1 | 5.3739 | 5.8215 | 1 |
| cluster_7 | 2 | CXCL8 | 3.4379 | 4.1457 | 1 |
| cluster_20 | 2 | TXN | 3.0885 | 3.7074 | 0.8333 |
| cluster_6 | 2 | TIMP1 | 2.7995 | 3.2618 | 0.9324 |
| cluster_11 | 2 | TPSAB1 | 2.7982 | 2.8046 | 0.9608 |
| cluster_4 | 2 | HLA-DRA | 2.7388 | 4.1797 | 0.9939 |
| cluster_19 | 2 | TAGLN | 2.5158 | 2.5473 | 1 |
| cluster_16 | 2 | CST3 | 2.1536 | 2.843 | 0.9677 |
| cluster_18 | 2 | PPP1R14B | 2.1433 | 2.4353 | 0.9091 |
| cluster_9 | 2 | NKG7 | 2.053 | 2.4783 | 0.9722 |
| cluster_17 | 2 | CRIP1 | 2.0038 | 2.9513 | 0.931 |
| cluster_5 | 2 | BANK1 | 1.702 | 1.7262 | 0.9667 |
| cluster_2 | 2 | CCL4 | 1.5808 | 2.3627 | 0.8944 |
| cluster_15 | 2 | XCL2 | 1.5011 | 1.6294 | 0.7353 |
| cluster_3 | 2 | IKZF2 | 1.4965 | 1.6342 | 0.8814 |
| cluster_12 | 2 | YBX3 | 1.4842 | 1.967 | 0.9362 |
| cluster_8 | 2 | NAMPT | 1.4641 | 2.8406 | 1 |
| cluster_13 | 2 | S100A4 | 1.2716 | 3.1273 | 0.9556 |
| cluster_14 | 2 | CXCL13 | 1.2075 | 1.2391 | 0.4286 |
| cluster_1 | 2 | BCL11B | 0.8807 | 1.4837 | 0.9099 |
Primary Metadata
Core de-identified metadata fields migrated from the ImmuneAging donor manifest.
Donor ID
SKCM-095-03-1A
Sample ID
SKCM-095-03-1A
Dataset
CancerSCEM 2.0
Cohort
CancerSCEM 2.0 Chinese subset; Melanoma
Age / Age Group
Pan-cancer Chinese cohort, per-donor ages not in CancerSCEM metadata
Sex
Not reported in public CancerSCEM metadata
Health Status
Melanoma; Tumour
Tissue / Cell Source
Tumour
Modality
scRNA-seq (10X Genomics)
Cell Count
7,839
Analysis Status
Matrix available; UMAP generated
UMAP Status
Ready
Metadata / Source Notes
Project ID: SKCM-095; Cancer type: Melanoma; Source: NCBI (SRA); Accession: PRJNA996416; Country: CHN; Sample type: Tumour; Protocol: 10X Genomics; Matrix: SKCM-095-03-1A.counts.matrix.tsv.gz (19.24 MB); UMAP: Scanpy-generated donor-level UMAP preview; cells=7839; raw genes=27192; Leiden clusters=20; coordinates TSV and summary JSON are available online.; Age/sex not reported in public CancerSCEM metadata. Age source: CancerSCEM 2.0 database; 400 samples across 47 cancer types; donor-level age not included in download.csv
Additional Clinical / Source Fields
Supplementary source metadata retained from the migrated manifest where available.
cancer type
Melanoma
cancer type short
SKCM
library count
1
library sample ids
SKCM-095-03-1A
source reference
CancerSCEM 2.0 metadata table; data source=NCBI (SRA); accession=PRJNA996416; downloaded 2026-07-06
data accession
PRJNA996416
project id
SKCM-095
sample type
Tumour
country
CHN
data source
NCBI (SRA)
accession no
PRJNA996416
construction protocol
10X Genomics
transcriptome profile
Yes
metabolic profile
Yes
matrix status
Matrix available
matrix file name
SKCM-095-03-1A.counts.matrix.tsv.gz
matrix file size bytes
20177190
matrix file size mb
19.24
matrix download url
umap coordinates url
umap summary url
umap pipeline
Scanpy 1.9.8 normalize_total/log1p/HVG/PCA/neighbors/leiden/umap; cells=7839; raw_genes=27192; leiden_clusters=20; generated 2026-07-07
matrix integrity status
Gzip readable; UMAP generated