Single-cell transcriptomic profiling of patient-derived pancreatic ductal adenocarcinoma primary cell cultures
Single-cell transcriptomic dataset comprising 41 patient-derived cell cultures (PDCs) established from pancreatic ductal adenocarcinoma (PDAC). The dataset was generated using Evercode™ technology with the Whole Transcriptome v2 kit (Parse Biosciences, ECW02130), based on Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq). For scRNA-seq, PDCs were processed in two batches, 14 samples in the first batch (R1) and 27 samples in the second batch (R2). Sequencing was performed separately for each batch using the Illumina NovaSeq X Plus platform. Paired-end reads were generated on a 10B flow cell with 200 sequencing cycles. FASTQ quality control (QC), barcode correction, alignment to the human reference genome (GRCh38.p13), multiplet detection, and raw count matrix generation were performed using the split-pipe pipeline (v1.1.1, Parse Biosciences) with default parameters. This single-cell collection of experimentally derived models reveals transcriptional heterogeneity both within and across PDCs. The submitted file consists of the count matrix along with the corresponding metadata.
Single-cell transcriptomic dataset comprising 41 patient-derived cell cultures (PDCs) established from pancreatic ductal adenocarcinoma (PDAC). The dataset was generated using Evercode™ technology with the Whole Transcriptome v2 kit (Parse Biosciences, ECW02130), based on Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq). For scRNA-seq, PDCs were processed in two batches, 14 samples in the first batch (R1) and 27 samples in the second batch (R2). Sequencing was performed separately for each batch using the Illumina NovaSeq X Plus platform. Paired-end reads were generated on a 10B flow cell with 200 sequencing cycles. FASTQ quality control (QC), barcode correction, alignment to the human reference genome (GRCh38.p13), multiplet detection, and raw count matrix generation were performed using the split-pipe pipeline (v1.1.1, Parse Biosciences) with default parameters. This single-cell collection of experimentally derived models reveals transcriptional heterogeneity both within and across PDCs. The submitted file consists of the count matrix along with the corresponding metadata.
European Bioinformatics Institute