GeneSigDB—a curated database of gene expression signatures

The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org

An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase

Gene expression profiling has the potential to enhance current methods for the diagnosis of haematological malignancies. Here, we present data on 204 analyses from an international standardization programme that was conducted in 11 laboratories as a prephase to the Microarray Innovations in LEukemia (MILE) study. Each laboratory prepared two cell line samples, together with three replicate leukaemia patient lysates in two distinct stages: (i) a 5-d course of protocol training, and (ii) independent proficiency testing. Unsupervised, supervised, and r2 correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability

Distinct 15q genotypes in Russell-Silver and ring 15 syndromes

Individuals with a ring 15 chromosome [r(15)] and those with Russell- Silver syndrome have short stature, developmental delay, triangular face, and clinodactyly. To assess whether the apparent phenotypic overlap of these conditions reflects a common genetic cause, the extent of deletions in chromosome 15q was determined in 5 patients with r(15), 1 patient with del 15q26.1-qter, and 5 patients with Russell-Silver syndrome. All patients with Russell-Silver syndrome were diploid for genetic markers in distal 15q, indicating that Russell-Silver syndrome in these individuals was unlikely to be related to the expression of single alleles at these or linked genetic loci. At least 3 distinct sites of chromosome breakage close to the telomere were found in the r(15) and del 15q25.1-qter patients, with 1 r(15) patient having both a terminal and an interstitial deletion. Although the patient with del 15q25.1-qter exhibited the largest deletion and the most profound growth retardation, the degree of growth impairment among the r(15) patients was not correlated with the size of the deleted interval. Rather, the parental origin of the ring chromosome in several patients was associated with phenotypes that are also seen in patients with either Prader-Willi (PWS) or Angelman (AS) syndromes, conditions that result from uniparental expression of genes on chromosome 15. In fact, unequal representation of chromosome 15 alleles in 1 patient with r(15) suggests the possibility that a mosaic karyotype composed of the constitutional cell line and cell line(s) possibly deficient in the ring chromosome might be present. The PWS-like or AS-like phenotypes could be explained by postzygotic loss of the ring chromosome, leading to uniparental inheritance of the intact chromosome in some tissues of r(15) patients