TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

Abstract

BackgroundSeveral tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input.ResultsTRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified.ConclusionsTRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.

A molecular view of the normal human thyroid structure and function reconstructed from its reference transcriptome map

“…Briefly, a TRAM map provides a reference gene expression value for all human mapped loci following intra-sample normalization (the raw value is expressed as percentage of the mean value for that sample) and inter-sample normalization (the value is further normalized by the quantile method to provide the mean value among the expression values available for all samples and having the same rank when each profile is ordered by descending order of these values) [17]. To maximize the data that may be extracted from diverse experimental platforms in a cross-platform model, overcoming the typical limitation of the standard quantile method requiring each platform provides the same number of genes/values, we applied the scaled quantile method.…”

“…To maximize the data that may be extracted from diverse experimental platforms in a cross-platform model, overcoming the typical limitation of the standard quantile method requiring each platform provides the same number of genes/values, we applied the scaled quantile method. This allowed the normalization of data derived from platforms with a highly different number of probes by adjusting the rank for each value in a sample in proportion to the sample having the maximum number of values, so effectively averaging highest/lowest values of a sample with the highest/lowest values of the other samples [17]. The final result is a reference expression value for a locus summarizing each available data point, allowing the comparison between two biological conditions when reference values for a given locus are present in both (A and B) sample pools considered, in the form of A/B ratio.…”

“…Due to the very small number of RNA-Seq studies available for the whole adult normal human thyroid (many experiments are performed on non-coding RNA expression, on fetal thyroid transcriptome or on cell lines), we have selected datasets obtained by expression microarrays published online from 2002 to 2013 for this study. Thirty-five suitable gene expression profile datasets found from different sources were combined and integrated using TRAM (Transcriptome Mapper) software [17], which is able to generate transcriptome maps from any source listing gene expression values for a given gene set, e.g. expression microarray, thus allowing a typical reference value of expression for each of the known and uncharacterized (unmapped) transcripts assayed by any of the experimental platforms used in this regard to be obtained (Fig.…”

Genome-scale analysis of human mRNA 5′ coding sequences based on expressed sequence tag (EST) database

“…This table is imported into the 5′_ORF_Extender as a first step, allowing analysis to be limited to the mRNAs and corresponding ESTs that are mapped to the same defined locus. Due to possible errors in the large text file generated by UniGene Tabulator data parsing, a quality control assessment of the completeness of the UniGene entries was made as described in the software guide of the TRAM tool [11].…”

Systematic reanalysis of partial trisomy 21 cases with or without Down syndrome suggests a small region on 21q22.13 as critical to the phenotype

“…First, we used the software Transcriptome Mapper (TRAM) (86) to process human genome data downloaded from the ‘NCBI Gene’ (http://www.ncbi.nlm.nih.gov/gene) databank and to build an updated framework of the structure of Hsa21 based on known Hsa21 genes. The framework was imported in a spreadsheet table and then enriched with coordinates for single nucleotide polymorphisms (SNPs), STSs, bacterial artificial chromosome (BAC) clones, nucleotide positions determined by Array CGH as limits of altered regions in individual subjects, cytogenetic band limits and key CNVs.…”