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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F11%3A00054378%21RIV12-MSM-14330___
rdf:type
skos:Concept n16:Vysledek
rdfs:seeAlso
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3259109/pdf/1471-2105-12-485.pdf
dcterms:description
We present a method that normalizes and statistically scores microscopy based RNAi screens, exploiting individual cell information of hundreds of cells per knockdown. Each cell’s individual population context is employed in normalization. We present results on two infection screens for hepatitis C and dengue virus, both showing considerable effects on observed phenotypes due to population context. In addition, we show on a nonvirus screen that these effects can be found also in RNAi data in the absence of any virus. Using our approach to normalize against these effects we achieve improved performance in comparison to an analysis without this normalization and hit scoring strategy. Furthermore, our approach results in the identification of considerably more significantly enriched pathways in hepatitis C virus replication than using a standard analysis approach. We present a method that normalizes and statistically scores microscopy based RNAi screens, exploiting individual cell information of hundreds of cells per knockdown. Each cell’s individual population context is employed in normalization. We present results on two infection screens for hepatitis C and dengue virus, both showing considerable effects on observed phenotypes due to population context. In addition, we show on a nonvirus screen that these effects can be found also in RNAi data in the absence of any virus. Using our approach to normalize against these effects we achieve improved performance in comparison to an analysis without this normalization and hit scoring strategy. Furthermore, our approach results in the identification of considerably more significantly enriched pathways in hepatitis C virus replication than using a standard analysis approach.
dcterms:title
Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens
skos:prefLabel
Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens
skos:notation
RIV/00216224:14330/11:00054378!RIV12-MSM-14330___
n16:predkladatel
n17:orjk%3A14330
n3:aktivita
n4:P n4:Z
n3:aktivity
P(2B06052), Z(MSM0021622419)
n3:cisloPeriodika
485
n3:dodaniDat
n9:2012
n3:domaciTvurceVysledku
n13:8544212
n3:druhVysledku
n5:J
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
216300
n3:idVysledku
RIV/00216224:14330/11:00054378
n3:jazykVysledku
n11:eng
n3:klicovaSlova
high-content screening; normalization; cell-based analysis
n3:klicoveSlovo
n8:high-content%20screening n8:normalization n8:cell-based%20analysis
n3:kodStatuVydavatele
GB - Spojené království Velké Británie a Severního Irska
n3:kontrolniKodProRIV
[1AA2B3DDBC01]
n3:nazevZdroje
BMC Bioinformatics
n3:obor
n21:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
11
n3:projekt
n6:2B06052
n3:rokUplatneniVysledku
n9:2011
n3:svazekPeriodika
12
n3:tvurceVysledku
Eils, Roland Rohr, Karl Kaderali, Lars Matula, Petr Knapp, Bettina Kiani, Narsis A Kumar, Anil Erfle, Hoger Rebhan, Ilka Binder, Marco Bartenschlager, Ralf
n3:zamer
n10:MSM0021622419
s:issn
1471-2105
s:numberOfPages
14
n18:organizacniJednotka
14330