Evidence map›Paper›PMID 20699007›Full record

SynthesisBMC genomics2010

A novel tissue-specific meta-analysis approach for gene expression predictions, initiated with a mammalian gene expression testis database.

Kshitish K Acharya, Darshan S Chandrashekar, Neelima Chitturi, Hardik Shah, Varun Malhotra, K S Sreelakshmi, H Deepti, Akhilesh Bajpai, Sravanthi Davuluri, Pranami Bora and 1 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 22 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Transcriptome profiling of mice testes following low dose irradiation.Reproductive biology and endocrinology : RB&E · 2013
    Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Kshitish K AcharyaInstitute of Bioinformatics and Applied Biotechnology, Biotech Park, Electronic City, Bangalore - 560100, Karnataka state, India. kshitish@ibab.ac.in
Darshan S Chandrashekar
Neelima Chitturi
Hardik Shah
Varun Malhotra
K S Sreelakshmi
H Deepti
Akhilesh Bajpai
Sravanthi Davuluri
Pranami Bora
Leena Rao
Institute of Bioinformatics and Applied Biotechnology · INBiotech Park · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the recent years, there has been a rise in gene expression profiling reports. Unfortunately, it has not been possible to make maximum use of available gene expression data. Many databases and programs can be used to derive the possible expression patterns of mammalian genes, based on existing data. However, these available resources have limitations. For example, it is not possible to obtain a list of genes that are expressed in certain conditions. To overcome such limitations, we have taken up a new strategy to predict gene expression patterns using available information, for one tissue at a time.

resultsThe first step of this approach involved manual collection of maximum data derived from large-scale (genome-wide) gene expression studies, pertaining to mammalian testis. These data have been compiled into a Mammalian Gene Expression Testis-database (MGEx-Tdb). This process resulted in a richer collection of gene expression data compared to other databases/resources, for multiple testicular conditions. The gene-lists collected this way in turn were exploited to derive a 'consensus' expression status for each gene, across studies. The expression information obtained from the newly developed database mostly agreed with results from multiple small-scale studies on selected genes. A comparative analysis showed that MGEx-Tdb can retrieve the gene expression information more efficiently than other commonly used databases. It has the ability to provide a clear expression status (transcribed or dormant) for most genes, in the testis tissue, under several specific physiological/experimental conditions and/or cell-types.

conclusionsManual compilation of gene expression data, which can be a painstaking process, followed by a consensus expression status determination for specific locations and conditions, can be a reliable way of making use of the existing data to predict gene expression patterns. MGEx-Tdb provides expression information for 14 different combinations of specific locations and conditions in humans (25,158 genes), 79 in mice (22,919 genes) and 23 in rats (14,108 genes). It is also the first system that can predict expression of genes with a 'reliability-score', which is calculated based on the extent of agreements and contradictions across gene-sets/studies. This new platform is publicly available at the following web address: http://resource.ibab.ac.in/MGEx-Tdb/.

Indexed as

Databases, Nucleic AcidGene ExpressionAnimalsHumansInternetMaleMiceOrgan SpecificityRatsReproducibility of ResultsTestis

Identifiers

PMID20699007
PMCPMC3091663
OpenAlexW2096808972

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.