TIPS: trajectory inference of pathway significance through pseudotime comparison for functional assessment of single-cell RNAseq data.
Brief Bioinform
; 22(5)2021 09 02.
Article
em En
| MEDLINE
| ID: mdl-34370020
ABSTRACT
Recent advances in bioinformatics analyses have led to the development of novel tools enabling the capture and trajectory mapping of single-cell RNA sequencing (scRNAseq) data. However, there is a lack of methods to assess the contributions of biological pathways and transcription factors to an overall developmental trajectory mapped from scRNAseq data. In this manuscript, we present a simplified approach for trajectory inference of pathway significance (TIPS) that leverages existing knowledgebases of functional pathways and other gene lists to provide further mechanistic insights into a biological process. TIPS identifies key pathways which contribute to a process of interest, as well as the individual genes that best reflect these changes. TIPS also provides insight into the relative timing of pathway changes, as well as a suite of visualizations to enable simplified data interpretation of scRNAseq libraries generated using a wide range of techniques. The TIPS package can be run through either a web server or downloaded as a user-friendly GUI run in R, and may serve as a useful tool to help biologists perform deeper functional analyses and visualization of their single-cell data.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Transdução de Sinais
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Biologia Computacional
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Perfilação da Expressão Gênica
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Análise de Célula Única
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RNA-Seq
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article