![]() GSE194122_openproblems_neurips2021_multiome_BMMC_processed.h5ad. Single-cell multiomics data collected from bone marrow mononuclear cells of 12 healthy human donors.īurkhardt DB, Lücken MD, Lance C, Cannoodt R, Pisco AO, Krishnaswamy S, Theis FJ, Bloom JM ![]() In the competition, participants were tasked with challenges including modality prediction, matching profiles from different modalities, and learning a joint embedding from multiple modalities. The dataset was designed with a nested batch layout such that some donor samples were measured at multiple sites with some donors measured at a single site. The resulting data was then annotated to identify cell types and remove doublets. Samples were prepared using a standard protocol at four sites. The dataset was generated to support Multimodal Single-Cell Data Integration Challenge at NeurIPS 2021. xz compression format, be sure to use the correct file. cd /opt download file from downloads page tar -xzvf cellranger-7.1.0.tar.gz. In this example, we unpack it in a directory called /opt. Half the samples were measured using the 10X Multiome Gene Expression and Chromatin Accessability kit and half were measured using the 10X 3' Single-Cell Gene Expression kit with Feature Barcoding in combination with the BioLegend TotalSeq B Universal Human Panel v1.0. Step 1 Download and unpack the cellranger-7.1.0.tar.gz tar file in any location. Single-cell multiomics data collected from bone marrow mononuclear cells of 12 healthy human donors. ![]() Genome binding/occupancy profiling by high throughput sequencing GEO help: Mouse over screen elements for information.Ī sandbox for prediction and integration of DNA, RNA, and proteins in single cellsĮxpression profiling by high throughput sequencing ![]()
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