Evidence map›Paper›PMID 25326331›Full record

ArticleNucleic acids research2015

ImmuCo: a database of gene co-expression in immune cells.

Pingzhang Wang, Huiying Qi, Shibin Song, Shuang Li, Ningyu Huang, Wenling Han, Dalong Ma

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

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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

7 authors.

Pingzhang WangDepartment of Immunology, Key Laboratory of Medical Immunology, Ministry of Health, School of Basic Medical Sciences, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China Peking University Center for Human Disease Genomics, No. 38 Xueyuan Road, Beijing 100191, China wangpzh@bjmu.edu.cn.
Huiying QiDepartment of Natural Science in Medicine, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China.
Shibin SongInformation and Communication Center, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China.
Shuang LiInformation and Communication Center, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China.
Ningyu HuangInformation and Communication Center, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China.
Wenling HanDepartment of Immunology, Key Laboratory of Medical Immunology, Ministry of Health, School of Basic Medical Sciences, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China Peking University Center for Human Disease Genomics, No. 38 Xueyuan Road, Beijing 100191, China.
Dalong MaDepartment of Immunology, Key Laboratory of Medical Immunology, Ministry of Health, School of Basic Medical Sciences, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing 100191, China Peking University Center for Human Disease Genomics, No. 38 Xueyuan Road, Beijing 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current gene co-expression databases and correlation networks do not support cell-specific analysis. Gene co-expression and expression correlation are subtly different phenomena, although both are likely to be functionally significant. Here, we report a new database, ImmuCo (http://immuco.bjmu.edu.cn), which is a cell-specific database that contains information about gene co-expression in immune cells, identifying co-expression and correlation between any two genes. The strength of co-expression of queried genes is indicated by signal values and detection calls, whereas expression correlation and strength are reflected by Pearson correlation coefficients. A scatter plot of the signal values is provided to directly illustrate the extent of co-expression and correlation. In addition, the database allows the analysis of cell-specific gene expression profile across multiple experimental conditions and can generate a list of genes that are highly correlated with the queried genes. Currently, the database covers 18 human cell groups and 10 mouse cell groups, including 20,283 human genes and 20,963 mouse genes. More than 8.6 × 10(8) and 7.4 × 10(8) probe set combinations are provided for querying each human and mouse cell group, respectively. Sample applications support the distinctive advantages of the database.

Indexed as

Databases, GeneticTranscriptomeAnimalsGene Expression ProfilingHumansImmune SystemInternetMiceOligonucleotide Array Sequence Analysis

Identifiers

PMID25326331
PMCPMC4384033

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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.