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The Power Decoder Simulator for the Evaluation of Pooled shRNA Screen Performance.

Stombaugh J, Licon A, Strezoska Ž, Stahl J, Anderson SB, Banos M, van Brabant Smith A, Birmingham A, Vermeulen A - J Biomol Screen (2015)

Bottom Line: Using the negative binomial distribution, it models both the relative abundance of multiple shRNAs within a single screening replicate and the biological noise between replicates for each individual shRNA.We demonstrate that this simulator can successfully model the data from an actual laboratory experiment.The Power Decoder simulator is written in R and Python and is available for download under the GNU General Public License v3.0.

View Article: PubMed Central - PubMed

Affiliation: Dharmacon, part of GE Healthcare, Lafayette, CO, USA.

No MeSH data available.


Differential enrichment and depletion of short hairpin RNAs (shRNAs) in simulated screens. MA plots for two representative examples of simulated data from shRNA pooled screens with in silico twofold enrichment and depletion of shRNAs based on (A) Screen 100_2x and (B) Screen 500_2x. The shRNAs with significantly (p* ≤ 0.05) higher and lower abundance in T1 in the simulated next-generation sequencing count data are in red and blue, respectively. Power values listed are mean ± standard deviation over 900 simulations.
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fig3-1087057115576715: Differential enrichment and depletion of short hairpin RNAs (shRNAs) in simulated screens. MA plots for two representative examples of simulated data from shRNA pooled screens with in silico twofold enrichment and depletion of shRNAs based on (A) Screen 100_2x and (B) Screen 500_2x. The shRNAs with significantly (p* ≤ 0.05) higher and lower abundance in T1 in the simulated next-generation sequencing count data are in red and blue, respectively. Power values listed are mean ± standard deviation over 900 simulations.

Mentions: We developed these techniques into a software tool called the Power Decoder simulator. The Power Decoder simulator is a suite of scripts written in Python and R and is available under the GNU General Public License v3.0 at https://sourceforge.net/projects/powerdecoder/. These command-line tools take user inputs specifying parameters such as experimental T0 or pilot data on which to base simulation models and the number of simulations to perform. Automatically generated outputs include plots such as those shown in Figures 2and3 (including Suppl. Figs. S1–S3) as well as comma-separated text files containing the data on which these figures are based.


The Power Decoder Simulator for the Evaluation of Pooled shRNA Screen Performance.

Stombaugh J, Licon A, Strezoska Ž, Stahl J, Anderson SB, Banos M, van Brabant Smith A, Birmingham A, Vermeulen A - J Biomol Screen (2015)

Differential enrichment and depletion of short hairpin RNAs (shRNAs) in simulated screens. MA plots for two representative examples of simulated data from shRNA pooled screens with in silico twofold enrichment and depletion of shRNAs based on (A) Screen 100_2x and (B) Screen 500_2x. The shRNAs with significantly (p* ≤ 0.05) higher and lower abundance in T1 in the simulated next-generation sequencing count data are in red and blue, respectively. Power values listed are mean ± standard deviation over 900 simulations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2 - License 3
Show All Figures
getmorefigures.php?uid=PMC4543901&req=5

fig3-1087057115576715: Differential enrichment and depletion of short hairpin RNAs (shRNAs) in simulated screens. MA plots for two representative examples of simulated data from shRNA pooled screens with in silico twofold enrichment and depletion of shRNAs based on (A) Screen 100_2x and (B) Screen 500_2x. The shRNAs with significantly (p* ≤ 0.05) higher and lower abundance in T1 in the simulated next-generation sequencing count data are in red and blue, respectively. Power values listed are mean ± standard deviation over 900 simulations.
Mentions: We developed these techniques into a software tool called the Power Decoder simulator. The Power Decoder simulator is a suite of scripts written in Python and R and is available under the GNU General Public License v3.0 at https://sourceforge.net/projects/powerdecoder/. These command-line tools take user inputs specifying parameters such as experimental T0 or pilot data on which to base simulation models and the number of simulations to perform. Automatically generated outputs include plots such as those shown in Figures 2and3 (including Suppl. Figs. S1–S3) as well as comma-separated text files containing the data on which these figures are based.

Bottom Line: Using the negative binomial distribution, it models both the relative abundance of multiple shRNAs within a single screening replicate and the biological noise between replicates for each individual shRNA.We demonstrate that this simulator can successfully model the data from an actual laboratory experiment.The Power Decoder simulator is written in R and Python and is available for download under the GNU General Public License v3.0.

View Article: PubMed Central - PubMed

Affiliation: Dharmacon, part of GE Healthcare, Lafayette, CO, USA.

No MeSH data available.