Dataset Information

Poisson factor models with applications to non-normalized microRNA profiling.

ABSTRACT:

Motivation

Next-generation (NextGen) sequencing is becoming increasingly popular as an alternative for transcriptional profiling, as is the case for micro RNAs (miRNA) profiling and classification. miRNAs are a new class of molecules that are regulated in response to differentiation, tumorigenesis or infection. Our primary motivating application is to identify different viral infections based on the induced change in the host miRNA profile. Statistical challenges are encountered because of special features of NextGen sequencing data: the data are read counts that are extremely skewed and non-negative; the total number of reads varies dramatically across samples that require appropriate normalization. Statistical tools developed for microarray expression data, such as principal component analysis, are sub-optimal for analyzing NextGen sequencing data.

Results

We propose a family of Poisson factor models that explicitly takes into account the count nature of sequencing data and automatically incorporates sample normalization through the use of offsets. We develop an efficient algorithm for estimating the Poisson factor model, entitled Poisson Singular Value Decomposition with Offset (PSVDOS). The method is shown to outperform several other normalization and dimension reduction methods in a simulation study. Through analysis of an miRNA profiling experiment, we further illustrate that our model achieves insightful dimension reduction of the miRNA profiles of 18 samples: the extracted factors lead to more accurate and meaningful clustering of the cell lines.

Availability

The PSVDOS software is available on request.

SUBMITTER: Lee S

PROVIDER: S-EPMC3634185 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Poisson factor models with applications to non-normalized microRNA profiling.

Lee Seonjoo S Chugh Pauline E PE Shen Haipeng H Eberle R R Dittmer Dirk P DP

Bioinformatics (Oxford, England) 20130221 9

<h4>Motivation</h4>Next-generation (NextGen) sequencing is becoming increasingly popular as an alternative for transcriptional profiling, as is the case for micro RNAs (miRNA) profiling and classification. miRNAs are a new class of molecules that are regulated in response to differentiation, tumorigenesis or infection. Our primary motivating application is to identify different viral infections based on the induced change in the host miRNA profile. Statistical challenges are encountered because ...[more]

PMID: 23428639

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Dataset Information

Poisson factor models with applications to non-normalized microRNA profiling.

Motivation

Results

Availability

Publications

Poisson factor models with applications to non-normalized microRNA profiling.

Similar Datasets

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