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siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens

Growing numbers of studies employ cell line-based systematic short interfering RNA (siRNA) screens to study gene functions and to identify drug targets. As multiple sources of variations that are unique to siRNA screens exist, there is a growing demand for a computational tool that generates normali...

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Detalles Bibliográficos
Autores principales: Singh, Nitin Kumar, Seo, Bo Yeun, Vidyasagar, Mathukumalli, White, Michael A., Kim, Hyun Seok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3630387/
https://www.ncbi.nlm.nih.gov/pubmed/23613684
http://dx.doi.org/10.5808/GI.2013.11.1.55
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author Singh, Nitin Kumar
Seo, Bo Yeun
Vidyasagar, Mathukumalli
White, Michael A.
Kim, Hyun Seok
author_facet Singh, Nitin Kumar
Seo, Bo Yeun
Vidyasagar, Mathukumalli
White, Michael A.
Kim, Hyun Seok
author_sort Singh, Nitin Kumar
collection PubMed
description Growing numbers of studies employ cell line-based systematic short interfering RNA (siRNA) screens to study gene functions and to identify drug targets. As multiple sources of variations that are unique to siRNA screens exist, there is a growing demand for a computational tool that generates normalized values and standardized scores. However, only a few tools have been available so far with limited usability. Here, we present siMacro, a fast and easy-to-use Microsoft Office Excel-based tool with a graphic user interface, designed to process single-condition or two-condition synthetic screen datasets. siMacro normalizes position and batch effects, censors outlier samples, and calculates Z-scores and robust Z-scores, with a spreadsheet output of >120,000 samples in under 1 minute.
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spelling pubmed-36303872013-04-23 siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens Singh, Nitin Kumar Seo, Bo Yeun Vidyasagar, Mathukumalli White, Michael A. Kim, Hyun Seok Genomics Inform Application Note Growing numbers of studies employ cell line-based systematic short interfering RNA (siRNA) screens to study gene functions and to identify drug targets. As multiple sources of variations that are unique to siRNA screens exist, there is a growing demand for a computational tool that generates normalized values and standardized scores. However, only a few tools have been available so far with limited usability. Here, we present siMacro, a fast and easy-to-use Microsoft Office Excel-based tool with a graphic user interface, designed to process single-condition or two-condition synthetic screen datasets. siMacro normalizes position and batch effects, censors outlier samples, and calculates Z-scores and robust Z-scores, with a spreadsheet output of >120,000 samples in under 1 minute. Korea Genome Organization 2013-03 2013-03-31 /pmc/articles/PMC3630387/ /pubmed/23613684 http://dx.doi.org/10.5808/GI.2013.11.1.55 Text en Copyright © 2013 by the Korea Genome Organization http://creativecommons.org/licenses/by-nc/3.0/ It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/).
spellingShingle Application Note
Singh, Nitin Kumar
Seo, Bo Yeun
Vidyasagar, Mathukumalli
White, Michael A.
Kim, Hyun Seok
siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens
title siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens
title_full siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens
title_fullStr siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens
title_full_unstemmed siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens
title_short siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens
title_sort simacro: a fast and easy data processing tool for cell-based genomewide sirna screens
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3630387/
https://www.ncbi.nlm.nih.gov/pubmed/23613684
http://dx.doi.org/10.5808/GI.2013.11.1.55
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