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Series GSE193517 Query DataSets for GSE193517
Status Public on Feb 02, 2022
Title Mapping Transcriptomic Vector Field of Single Cells
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Other
Summary Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo, which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo’s power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.
 
Overall design This study contains three main experiments. The first two are about 10x scRNA-seq experiment and sequential lineage tracing of HL60 cell differentiation with static barcode and scSLAM-seq, respectively. The third one is about profiling human hematopoiesis in vitro with scNT-seq.
 
Contributor(s) Qiu X, Martin-Rufino JD, Weng C, Hosseinzadeh S
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Submission date Jan 12, 2022
Last update date Feb 02, 2022
Contact name Xiaojie Qiu
E-mail(s) xqiu@wi.mit.edu
Phone 2066698470
Organization name Whitehead Institute
Street address 455 Main St, Cambridge, MA
City Cambridge
State/province MA
ZIP/Postal code 02142
Country USA
 
Platforms (1)
GPL24676 Illumina NovaSeq 6000 (Homo sapiens)
Samples (1757)
GSM5811783 scNT-seq of HSPC day 7 timepoint
GSM5811784 scNT-seq of HSPC day 4 timepoint
GSM5811785 scNT-seq of HSPC day 7 timepoint, repeat
Relations
BioProject PRJNA796521

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Supplementary file Size Download File type/resource
GSE193517_HL60_10x.h5ad.gz 33.0 Mb (ftp)(http) H5AD
GSE193517_HL60_memory_seq.h5ad.gz 189.5 Mb (ftp)(http) H5AD
GSE193517_HSC.h5ad.gz 104.1 Mb (ftp)(http) H5AD
GSE193517_edge_df.csv.gz 456 b (ftp)(http) CSV
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Raw data are available in SRA
Processed data are available on Series record

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