RnaSeqSampleSize
This app is a web interface for R package RnaSeqSampleSize, which provided an easy and automatic pipeline for RNA sequencing data sample size estimation.
View introduction and examples for RnaSeqSampleSize package
Install RnaSeqSampleSize package from Bioconductor
RnaSeqSampleSize: real data based sample size estimation for RNA sequencing
Estimate Sample Size or Power?
Sample Size
Power
power: Power to detecte prognostic genes
n: Sample Size
Sample Size Estimation by single parameter
Sample Size Estimation by prior data
Generate Power Curves
Parameters Optimization
f: FDR level
w: Ratio of normalization factors between two groups
m: Total number of genes for testing
m1: Expected number of prognostic genes
rho: Minimum fold changes for prognostic genes between two groups
lambda0: Average read counts for prognostic genes
phi0: Dispersion for prognostic genes
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Estimate by your prior data or TCGA data?
Upload Prior data
TCGA data
Choose TXT or CSV File from local drive, adjusting parameters if necessary
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Header
Gene ID in first row
Separator
Comma
Semicolon
Tab
Quote
None
Double Quote
Single Quote
TCGA data set:
BLCA
BRCA
CESC
COAD
HNSC
KIRC
LGG
LUAD
LUSC
PRAD
READ
THCA
UCEC
Use total count in prior data as library size
libSize: Library size for each sample
f: FDR level
m: Total number of genes for testing
m1: Expected number of prognostic genes
rho: Minimum fold changes for prognostic genes between two groups
repNumber: Number of genes used in estimation of read counts and dispersion distribution
Please Note: Estimation may use 5-10 minutes based on the parameters.
repNumber is limited to <=10 due to server resources. Please use RnaSeqSampleSize package in R if you need more repNumber.
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n: Sample Size
f: FDR level
m: Total number of genes for testing
m1: Expected number of prognostic genes
rho: Minimum fold changes for prognostic genes between two groups
lambda0: Average read counts for prognostic genes
phi0: Dispersion for prognostic genes
w: Ratio of normalization factors between two groups
n is limited to <=80 due to server resources. Please use RnaSeqSampleSize package in R if you need more n for Power Curves.
Make a Curve
Add a curve
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Please input the values for optimization with , and :, for example, '1:3,5' means '1,2,3,5'
Please Note: Estimation may use 5-10 minutes based on the parameters.
Parameters are limited to <=5 values due to server resources. Please use RnaSeqSampleSize package in R if you need more Parameters.
n: Sample Size
power: Power to detecte prognostic genes
m: Total number of genes for testing
m1: Expected number of prognostic genes
rho: Minimum fold changes for prognostic genes between two groups
lambda0: Average read counts for prognostic genes
phi0: Dispersion for prognostic genes
f: FDR level
Submit