Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 2 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001006984	This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.	Illumina HiSeq 4000	4

Publications	Citations
miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data. Hippen AA, Falco MM, Weber LM, Erkan EP, Zhang K, Doherty JA, Vähärautio A, Greene CS, Hicks SC. PLoS Comput Biol 17: 2021 e1009290	39
Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones. Ianevski A, Nader K, Driva K, Senkowski W, Bulanova D, Moyano-Galceran L, Ruokoranta T, Kuusanmäki H, Ikonen N, Sergeev P, Vähä-Koskela M, Giri AK, Vähärautio A, Kontro M, Porkka K, Pitkänen E, Heckman CA, Wennerberg K, Aittokallio T. Nat Commun 15: 2024 8579	2