prebs

prebs processes RNA-seq mapped reads to estimate gene expression values corresponding to microarray probe regions and applies microarray summarization algorithms to produce expression estimates comparable to microarray measurements for cross-platform integration.

Key Features:

• Cross-platform comparability: Produces RNA-seq–derived expression estimates that resemble microarray outputs by focusing on reads overlapping microarray probe regions.
• Probe-region expression estimation: Uses mapped reads in BAM format to estimate expression levels for sequences overlapping individual microarray probes.
• Microarray summarization adaptation: Applies a modified RMA (Robust Multi-array Average) algorithm and standard microarray summarization techniques to RNA-seq–based probe estimates.
• Probe-set output: Generates expression values for original microarray probe sets to enable direct comparison with microarray datasets.
• Facilitates database integration: Aligns RNA-seq–derived estimates with microarray-based measurements to support integration with existing microarray-dominated public repositories.

Scientific Applications:

• Comparative studies: Enables cross-platform analyses and meta-analyses involving large public datasets such as The Cancer Genome Atlas (TCGA) by providing comparable expression estimates.
• Gene signature retrieval: Improves retrieval of paired microarray samples and identification of gene signatures defined from RNA-seq when comparing to microarray-based repositories.

Methodology:

Input mapped reads in BAM format are used to estimate expression overlapping microarray probe regions, and these probe-level estimates are processed with a modified RMA (Robust Multi-array Average) and standard microarray summarization techniques to produce outputs comparable to traditional microarray gene expressions.