1,721,095 research outputs found
A computational reconstruction of the adult human heart transcriptional profile
No full textThe reconstruction of the transcriptional profile of the adult human heart was attempted, by applying a bioinformatic and computational approach to UniGene data. A catalogue of 2077 expressed genes was produced. Over 1000 entries of the catalogue corresponded to putative novel genes. Highly expressed genes accounted for about 20% of the total. Almost all genes expressed in adult heart resulted to be active in at least one additional tissue and about 90% were found in over five additional tissues. A genomic map of 1364 genes expressed in heart, which also indicated chromosomal location, was produced, which could be conveniently used for the discovery of the determinants of gene-orphan heart diseases and for the detection of clusters of highly expressed genes. The catalogue and the genomic map of genes expressed in adult human heart are available on Internet at the sites: http://telethon.bio.unipd.it/GETProfiles/heart and http://telethon.bio.unipd.it/GETMaps/heart
A novel resource for the study of genes expressed in the adult human retina
No full textPURPOSE:
To reconstruct the transcriptional profile of the human adult retina and the genomic map of the genes expressed in this tissue.
METHODS:
Original software was used for the retrieval and analysis of records from UniGene (http://www.ncbi.nlm.nih. gov/UniGene/) pertaining to selected cDNA libraries from adult human retina.
RESULTS:
The 4974 genes reported so far to be expressed in retina were included in a catalog available on the Internet. For each entry, an estimation of the level of expression of the corresponding gene in the retina was provided. A high-resolution genomic map of the human retina was built up by inclusion of 3152 genes showing a precise and unique map assignment. The correspondence was established between 53 gene-orphan retinal diseases and clusters of genes expressed in the retina.
CONCLUSIONS:
The in silico reconstruction of the transcriptional profile of the adult human retina provides preliminary information on the pattern of genomic expression in this tissue. The chromosomal location of many retinal genes, combined with their expression data, should speed up the identification of genes involved in retinal diseases
Detecting differentially expressed genes in multiple tag sampling experiments: comparative evaluation of statistical tests
No full textThe comparison of several statistical methods currently used for detection of differentially expressed genes was attempted both by a simulation approach and by the analysis of data sets of human expressed sequence tags, obtained from UniGene. In the simulated mixed case, mimicking a situation close to reality, the general chi(2) test was unexpectedly the most efficient in multiple tag sampling experiments, especially when dealing with variations affecting weakly expressed genes. On the other hand, Audic and Claverie's method proved the most efficient for detecting differences in gene expression when dealing with pairwise comparisons. By applying the above methods on UniGene-based data sets concerning two human kidney tumours compared with normal kidney tissue, three novel genes overexpressed in these tumours were identified. Software and additional information on statistical methodologies, simulation approach and data are available at http://telethon.bio.unipd.it/bioinfo/IDEG6/
Impact of probe annotation on the integration of miRNA-mRNA expression profiles for miRNA target detection.
No full textMicroRNAs (miRNAs) are small non-coding RNAs that mediate gene expression at the post-transcriptional and translational levels by an imperfect binding to target mRNA 3'UTR regions. While the ab-initio computational prediction of miRNA-mRNA interactions still poses significant challenges, it is possible to overcome some of its limitations by carefully integrating into the analysis the paired expression profiles of miRNAs and mRNAs. In this work, we show how the choice of a proper probe annotation for microarray platforms is an essential requirement to achieve good sensitivity in the identification of miRNA-mRNA interactions. We compare the results obtained from the analysis of the same expression profiles using both gene and transcript based custom CDFs that we have developed for a number of different annotations (ENSEMBL, RefSeq, AceView). In all cases, transcript-based annotations clearly improve the effectiveness of data integration and thus provide a more reliable confirmation of computationally predicted miRNA-mRNA interactions
Differential expression of genes coding for ribosomal proteins in different human tissues
No full textMOTIVATION: To perform a computational and statistical study on a large set of gene expression data pertaining six adult human tissues (brain, liver, skeletal muscle, ovary, retina and uterus) for analyzing the expression of ribosomal protein genes.
RESULTS: Unexpectedly, in each of the considered tissues large variations in the expression of ribosomal protein genes were observed. Moreover, when comparing the expression levels of 89 ribosomal protein genes in six different tissues, 13 genes appeared differentially expressed among tissues.
AVAILABILITY: The expression data of the ribosomal protein genes together with supplementary material (complete transcriptional profiles of the considered human tissues) are freely available at the site GETProfiles (http://telethon.bio.unipd.it/GETProfiles/)
iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
Full text linkWhole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variants by three complementary callers (MuTect2, Strelka2 and VarScan2). The results are combined to obtain a single variant call format file for each sample and variants are annotated by integrating a wide range of information extracted from several reference databases, ultimately allowing variant and gene prioritization according to different criteria. iWhale allows users to conduct a complex series of WES analyses with a powerful yet customizable and easy-to-use tool, running on most operating systems (macOs, GNU/Linux and Windows). iWhale code is freely available at https://github.com/alexcoppe/iWhale and the docker image is downloadable from https://hub.docker.com/r/alexcoppe/iwhale
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