Dataset Information

Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools.

ABSTRACT: Single-cell RNA sequencing data require several processing procedures to arrive at interpretable results. While commercial platforms can serve as "one-stop shops" for data analysis, they relinquish the flexibility required for customized analyses and are often inflexible between experimental systems. For instance, there is no universal solution for the discrimination of informative or uninformative encapsulated cellular material; thus, pipeline flexibility takes priority. Here, we demonstrate a full data analysis pipeline, constructed modularly from open-source software, including tools that we have contributed. For complete details on the use and execution of this protocol, please refer to Petukhov et al. (2018), Heiser et al. (2020), and Heiser and Lau (2020).

SUBMITTER: Chen B

PROVIDER: S-EPMC8082116 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools.

Chen Bob B Ramirez-Solano Marisol A MA Heiser Cody N CN Liu Qi Q Lau Ken S KS

STAR protocols 20210417 2

Single-cell RNA sequencing data require several processing procedures to arrive at interpretable results. While commercial platforms can serve as "one-stop shops" for data analysis, they relinquish the flexibility required for customized analyses and are often inflexible between experimental systems. For instance, there is no universal solution for the discrimination of informative or uninformative encapsulated cellular material; thus, pipeline flexibility takes priority. Here, we demonstrate a ...[more]

PMID: 33982010

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Dataset Information

Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools.

Publications

Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools.

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