دورية أكاديمية
popsicleR: A R Package for Pre-processing and Quality Control Analysis of Single Cell RNA-seq Data
| العنوان: | popsicleR: A R Package for Pre-processing and Quality Control Analysis of Single Cell RNA-seq Data |
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| المؤلفون: | Grandi F., Caroli J., Romano O., Marchionni M., Forcato M., Bicciato S. |
| المساهمون: | Grandi, F., Caroli, J., Romano, O., Marchionni, M., Forcato, M., Bicciato, S. |
| بيانات النشر: | Academic Press |
| سنة النشر: | 2022 |
| المجموعة: | Padua Research Archive (IRIS - Università degli Studi di Padova) |
| مصطلحات موضوعية: | bioinformatic, data analysi, R language, single cell RNA-sequencing, software tools |
| الوصف: | The advent of single-cell sequencing is providing unprecedented opportunities to disentangle tissue complexity and investigate cell identities and functions. However, the analysis of single cell data is a challenging, multi-step process that requires both advanced computational skills and biological sensibility. When dealing with single cell RNA-seq (scRNA-seq) data, the presence of technical artifacts, noise, and biological biases imposes to first identify, and eventually remove, unreliable signals from low-quality cells and unwanted sources of variation that might affect the efficacy of subsequent downstream modules. Pre-processing and quality control (QC) of scRNA-seq data is a laborious process consisting in the manual combination of different computational strategies to quantify QC-metrics and define optimal sets of pre-processing parameters. Here we present popsicleR, a R package to interactively guide skilled and unskilled command line-users in the pre-processing and QC analysis of scRNA-seq data. The package integrates, into several main wrapper functions, methods derived from widely used pipelines for the estimation of quality-control metrics, filtering of low-quality cells, data normalization, removal of technical and biological biases, and for cell clustering and annotation. popsicleR starts from either the output files of the Cell Ranger pipeline from 10X Genomics or from a feature-barcode matrix of raw counts generated from any scRNA-seq technology. Open-source code, installation instructions, and a case study tutorial are freely available at https://github.com/bicciatolab/popsicleRTest. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | info:eu-repo/semantics/altIdentifier/pmid/35662457; info:eu-repo/semantics/altIdentifier/wos/WOS:000814716800008; volume:434; issue:11; firstpage:167560; journal:JOURNAL OF MOLECULAR BIOLOGY; https://hdl.handle.net/11577/3478747Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85127528877 |
| DOI: | 10.1016/j.jmb.2022.167560 |
| الإتاحة: | https://doi.org/10.1016/j.jmb.2022.167560Test https://hdl.handle.net/11577/3478747Test |
| حقوق: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.10514974 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.jmb.2022.167560 |
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