4,366 BSF + 7,640 PCF cells
PRJEB58781 · ZENODO 7508131 · ELIFE 86325
追溯12,006个复制期锥虫细胞
本页把论文统计、ENA原始测序文件、Zenodo处理对象和作者交互图谱逐层分开。4,366个血流型与7,640个前循环型细胞均使用作者真实坐标，但两套UMAP是分别计算的，不能拼接为一个共同空间。
Profiling the bloodstream form and procyclic form Trypanosoma brucei cell cycle using single-cell transcriptomics. Briggs EM et al. eLife 12:e86325 (2023).
52 paired FASTQ files
9.94 GB deposited
Separate BSF and PCF UMAP/MNN
COUNTING AND COORDINATE BOUNDARY
细胞数可以相加，UMAP距离不能跨图谱比较
12,006来自作者细胞级阶段表的行数。BSF与PCF的整合、MNN和UMAP分别完成；本站保留两个独立入口，不做拼接、配准或重新降维。
AUTHOR METADATA · EXACT CELL COUNTS
新鲜与冻存样本、阶段标签均保留作者命名
FORM / PHASEEARLY G1LATE G1S · G2M · UNLABELLED
BSF4,366 cells9578691,009 · 977 · 554
PCF7,640 cells1,4712,0111,829 · 1,595 · 734
ENA · RAW SEQUENCING LAYER
26个NextSeq 2000运行提供52个双端FASTQ
ENA run and FASTQ counts describe sequencing files, not retained cells. The 12,006-cell total comes from author processed metadata after quality control.
ZENODO · AUTHOR PROCESSED LAYER
整合对象、阶段表、归一化矩阵与分析代码均已公开
FILE / ROLESIZEMD5STATUS
BSF_integrated_with_phase.rdsIntegrated BSF Seurat object with phase and UMAP82.98 MB
fe05f59b4f1e609310f24d0204b2ff5eAuthor depositPCF_integrated_with_phase.rdsIntegrated PCF Seurat object with phase and UMAP175.01 MB
38c38b056ec9d2b2000a6dba0d9036f5Author depositBSF_phase.csv4,366 cell-level phase rows173.29 kB
0bae6b3b7b7e7e0b4819397aad89d9b4Author depositPCF_phase.csv7,640 cell-level phase rows303.93 kB
8b10d233bd4f3b2de287d5dc6e0415bfAuthor depositBSF_normcounts.csvAuthor normalized-count table31.56 MB
2a96d3c670dc34f4975c5f3ed47d7de4Author depositPCF_normcounts.csvAuthor normalized-count table182.62 MB
d59e1d90f0555d24c3f36fade3af43d0Author depositThe current Zenodo API exposes 39 files totalling 9.94 GB under CC BY 4.0. File totals describe the repository snapshot retrieved on 2026-07-26.
AUTHOR CELL×GENE · TRYPCELL CONVERSION
真实UMAP、MNN和元数据直接转换；表达按需读取
The active author CELLxGENE matrix contains non-negative fractional values and is labelled as author normalized expression, not raw UMI counts.
BSF and PCF UMAP/MNN embeddings were created separately by the authors. TrypCell keeps them as separate views and does not merge, align or recompute either coordinate space.
TrypCell converts author FlatBuffer columns into static browser arrays and requests expression columns on demand. It does not relabel phases, rerun MNN/UMAP, normalize or impute expression.