Normalizing for Individual Cell Population Context in the
Analysis of High-Content Cellular Screens

J 2011

Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens

KNAPP, Bettina; Ilka REBHAN; Anil KUMAR; Petr MATULA; Narsis A KIANI et al.

Základní údaje

Originální název

Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens

Autoři

KNAPP, Bettina; Ilka REBHAN; Anil KUMAR; Petr MATULA; Narsis A KIANI; Marco BINDER; Hoger ERFLE; Karl ROHR; Roland EILS; Ralf BARTENSCHLAGER a Lars KADERALI

Vydání

BMC Bioinformatics, BioMed Central, 2011, 1471-2105

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10103 Statistics and probability

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 2.751

Kód RIV

RIV/00216224:14330/11:00054378

Organizační jednotka

Fakulta informatiky

UT WoS

000299110500001

Klíčová slova anglicky

high-content screening; normalization; cell-based analysis

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 17. 4. 2012 14:20, doc. RNDr. Petr Matula, Ph.D.

Anotace

V originále

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.

Návaznosti

MSM0021622419, záměr

Název: Vysoce paralelní a distribuované výpočetní systémy

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Vysoce paralelní a distribuované výpočetní systémy

2B06052, projekt VaV

Název: Vytipování markerů, screening a časná diagnostika nádorových onemocnění pomocí vysoce automatizovaného zpracování multidimenzionálních biomedicínských obrazů (Akronym: Biomarker)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Vytipování markerů, screening a časná diagnostika nádorových onemocnění pomocí vysoce automatizovaného zpracování multidimenzionálních biomedicínských obrazů

Citovat

KNAPP, Bettina; Ilka REBHAN; Anil KUMAR; Petr MATULA; Narsis A KIANI; Marco BINDER; Hoger ERFLE; Karl ROHR; Roland EILS; Ralf BARTENSCHLAGER a Lars KADERALI. Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens. BMC Bioinformatics. BioMed Central, 2011, roč. 12, č. 485, s. 1-14. ISSN 1471-2105.

@article{962192,
   author = {Knapp, Bettina and Rebhan, Ilka and Kumar, Anil and Matula, Petr and Kiani, Narsis A and Binder, Marco and Erfle, Hoger and Rohr, Karl and Eils, Roland and Bartenschlager, Ralf and Kaderali, Lars},
   article_number = {485},
   keywords = {high-content screening; normalization; cell-based analysis},
   language = {eng},
   issn = {1471-2105},
   journal = {BMC Bioinformatics},
   title = {Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens},
   url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3259109/pdf/1471-2105-12-485.pdf},
   volume = {12},
   year = {2011}
}

TY  - JOUR
ID  - 962192
AU  - Knapp, Bettina - Rebhan, Ilka - Kumar, Anil - Matula, Petr - Kiani, Narsis A - Binder, Marco - Erfle, Hoger - Rohr, Karl - Eils, Roland - Bartenschlager, Ralf - Kaderali, Lars
PY  - 2011
TI  - Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens
JF  - BMC Bioinformatics
VL  - 12
IS  - 485
SP  - 1-14
EP  - 1-14
PB  - BioMed Central
SN  - 14712105
KW  - high-content screening
KW  - normalization
KW  - cell-based analysis
UR  - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3259109/pdf/1471-2105-12-485.pdf
L2  - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3259109/pdf/1471-2105-12-485.pdf
N2  - 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.
ER  -

KNAPP, Bettina; Ilka REBHAN; Anil KUMAR; Petr MATULA; Narsis A KIANI; Marco BINDER; Hoger ERFLE; Karl ROHR; Roland EILS; Ralf BARTENSCHLAGER a Lars KADERALI. Normalizing for Individual Cell Population Context in the Analysis of High-Content Cellular Screens. \textit{BMC Bioinformatics}. BioMed Central, 2011, roč.~12, č.~485, s.~1-14. ISSN~1471-2105.

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