Single Cell Transcriptomics
portes grátis
Single Cell Transcriptomics
Methods and Protocols
Calogero, Raffaele A.; Benes, Vladimir
Springer-Verlag New York Inc.
12/2022
390
Dura
Inglês
9781071627556
15 a 20 dias
954
Descrição não disponível.
Guidance on processing the 10x Genomics Single Cell Gene Expression Assay.- BD Rhapsody (TM) Single-Cell Analysis System Workflow: From sample to multimodal single cell sequencing data.- Profiling transcriptional heterogeneity with Seq-Well S3: A low-cost, portable, high-fidelity platform for massively-parallel single-cell RNA-seq.- A MATQ-seq based protocol for single-cell RNA-seq in bacteria.- Full-length single-cell RNA-sequencing with FLASH-seq.- Plant single cell/nucleus RNA-seq workflow.- Ensuring Quality Cell Input for Single Cell Sequencing Experiments by Viability and Singlet Enrichment using Cell Sorting.- Tissue RNA integrity in Visium Spatial Protocol (Fresh Frozen Samples).- Single cell RNAseq data QC and preprocessing.- Single cell RNAseq complexity reduction.- Functional-feature-based data reduction using sparsely connected autoencoders.- Single cell RNAseq clustering.- Identifying Gene Markers AssociatedTo Cell Subpopulations.- A guide to trajectory inference and RNA velocity.- Integration of scATAC-seq with scRNA-seq data.- Using "Galaxy-rCASC", a public Galaxy instance for single-cell RNA-Seq data analysis.- Bringing cell subpopulation discovery on a cloud-HPC using rCASC and StreamFlow.- Profiling RNA editing in single cells.
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RNAseq;CITE-seq;optimal clustering;Spatial transcriptomics;fastq files
Guidance on processing the 10x Genomics Single Cell Gene Expression Assay.- BD Rhapsody (TM) Single-Cell Analysis System Workflow: From sample to multimodal single cell sequencing data.- Profiling transcriptional heterogeneity with Seq-Well S3: A low-cost, portable, high-fidelity platform for massively-parallel single-cell RNA-seq.- A MATQ-seq based protocol for single-cell RNA-seq in bacteria.- Full-length single-cell RNA-sequencing with FLASH-seq.- Plant single cell/nucleus RNA-seq workflow.- Ensuring Quality Cell Input for Single Cell Sequencing Experiments by Viability and Singlet Enrichment using Cell Sorting.- Tissue RNA integrity in Visium Spatial Protocol (Fresh Frozen Samples).- Single cell RNAseq data QC and preprocessing.- Single cell RNAseq complexity reduction.- Functional-feature-based data reduction using sparsely connected autoencoders.- Single cell RNAseq clustering.- Identifying Gene Markers AssociatedTo Cell Subpopulations.- A guide to trajectory inference and RNA velocity.- Integration of scATAC-seq with scRNA-seq data.- Using "Galaxy-rCASC", a public Galaxy instance for single-cell RNA-Seq data analysis.- Bringing cell subpopulation discovery on a cloud-HPC using rCASC and StreamFlow.- Profiling RNA editing in single cells.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
