{"id":2,"date":"2018-02-19T16:38:52","date_gmt":"2018-02-19T15:38:52","guid":{"rendered":"https:\/\/bioinfo.cipf.es\/ubb\/?page_id=2"},"modified":"2026-03-04T14:19:15","modified_gmt":"2026-03-04T13:19:15","slug":"tools","status":"publish","type":"page","link":"https:\/\/bioinfo.cipf.es\/cbl\/tools\/","title":{"rendered":"Tools"},"content":{"rendered":"
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A)\u00a0 Omics data meta-analysis tools\u00a0<\/b><\/span><\/h3>\n

MetaOmixTools<\/span><\/h4>\n

A user-friendly web suite for meta-analysis of ranked features and functional enrichment<\/strong><\/span><\/p>\n

MetaOmixTools<\/a> is a web-based, code-free platform designed to streamline meta-analysis of ranked feature lists and functional enrichment results. It integrates two modules: MetaRank, which produces consensus rankings using weighted (e.g., Rank Product) and unweighted (e.g., Robust Rank Aggregation) approaches, and MetaEnrich, which combines enrichment p-values across studies through established statistical methods. With real-time visualization and reproducible workflows, MetaOmixTools enables robust extraction of shared biological insights from heterogeneous multi-study datasets. Publication<\/a>.\u00a0<\/span><\/span><\/p>\n

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MetaFun<\/span><\/h4>\n

Unveiling Sex-based Differences in Multiple Transcriptomic Studies through Comprehensive Functional Meta-analysis<\/strong><\/span><\/p>\n

While sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack a deep analysis of sex as a variable in this context. To fill this knowledge gap, we created<\/span> MetaFun<\/a> as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness. Furthermore,<\/span> MetaFun<\/a> can be used to perform case-control meta-analyses, allowing researchers with basic programming skills to access this methodology.<\/span> Publication<\/a><\/span><\/p>\n

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B) Cancer tools<\/b><\/span><\/h3>\n

Web resources to compare results obtained in integrative approaches of different types of cancer, with the groups of proteins, genes and biological pathways of your research:<\/b><\/span><\/p>\n

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  1. MetaFun-NSCLC<\/b><\/span>:\u00a0 Functional signatures in <\/span>non-small-cell lung cancer<\/b>. <\/span><\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
  2. MetaFun-PDAC<\/b><\/span>: A comprehensive transcriptional signature in <\/span>pancreatic ductal adenocarcinoma<\/b><\/span> reveals new insights into the immune and desmoplastic microenvironments.<\/span>\u00a0 <\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
  3. MetaFun-ExoCellBC<\/b><\/span>: <\/span>Comparative profiling of whole-cell and exosome samples reveals protein signatures that stratify <\/span>breast cancer<\/b><\/span> subtypes.<\/span> <\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
  4. MetaFun-MBM<\/b><\/span>: Unveiling common transcriptomic features between <\/span>melanoma brain metastases<\/b> and neurodegenerative diseases. <\/span><\/span>Webtool<\/span><\/a>. <\/span>Preprint<\/span><\/a><\/li>\n
  5. MetaFun-BC<\/b><\/span>: DNA methylation signatures in <\/span>breast cancer<\/b><\/span>.<\/span> <\/span>Webtool<\/span><\/a>. <\/span>Preprint<\/span><\/a><\/li>\n<\/ol>\n
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    C) Neuroscience resources<\/b><\/span><\/h3>\n

    Web tools to identify transcriptomic and lipidomic signatures to improve diagnosis and treatment of brain diseases:<\/b><\/span><\/p>\n

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    1. Transcriptomic signatures in neurodegenerative diseases:<\/b><\/span>\n
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      1. MetaFun-PD:<\/b><\/span> Unveiling sex-based differences in <\/span>Parkinson Disease<\/b>: a comprehensive meta-analysis of transcriptomic studies<\/span>. <\/span><\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a>.<\/span><\/li>\n
      2. MetaFun-MS: <\/b><\/span>A deep transcriptome meta-analysis reveals sex differences in <\/span>Multiple Sclerosis<\/b>.<\/span><\/span> Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a>.\u00a0<\/span><\/li>\n
      3. MetaFun-AD: <\/b><\/span>An integrated approach to identify sex-specific genes, transcription factors, and pathways in <\/span>Alzheimer\u2019s disease<\/b>.<\/span><\/span> Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
      4. MetaFun-AD-miRNA: <\/b><\/span>The role of microRNAs to understand sex-based differences in <\/span>Alzheimer\u2019s disease<\/b>.<\/span> <\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a>.<\/span><\/li>\n<\/ol>\n<\/li>\n
      5. sc-RNA-seq atlas in neurodegenerative diseases<\/b>:<\/span><\/span>\n
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        1. CBL-atlas-Multiple Sclerosis:<\/b><\/span> Single cell landscape of sex differences in the progression of <\/span>multiple sclerosis<\/b>.<\/span> <\/span>Webtool<\/span><\/a>. <\/span>Preprint<\/span><\/a>.<\/span><\/li>\n
        2. CBL-atlas-Parkinson Disease:<\/span> <\/b>Single cell RNA seq metaanalysis reveals a higher neurodegenerative and inflammatory profile in males in <\/span>Parkinson’s Disease<\/b> (in progress). <\/span><\/span>Webtool<\/span><\/a><\/li>\n
        3. CBL-atlas-Alzheimer Disease:<\/b><\/span> Webtool<\/span><\/a><\/li>\n<\/ol>\n<\/li>\n
        4. MetaFun-SCI:<\/b><\/span> A <\/span>spinal cord injury<\/b> time and severity consensus transcriptomic reference suite in rat reveals translationally-relevant biomarker genes<\/span>.<\/span><\/span> Webtool<\/span><\/a>. <\/span>Preprint<\/span><\/a>\u00a0<\/span><\/li>\n
        5. MetaFun-SCZ<\/span><\/span><\/b><\/a>:<\/b><\/span> The impact of sex on gene expression in the brain of <\/span>schizophrenic patients<\/b>. <\/span><\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
        6. Study of differential sex profiles in neuroinflammation associated with alcohol use disorders:<\/b><\/span>\n
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          1. MetaFun-AUD:<\/b><\/span> Unveiling sex-based differences in the <\/span>effects of alcohol abuse<\/b>.<\/span><\/span> Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a>\u00a0<\/span><\/li>\n
          2. MetaFun-SAL-chronics:<\/span> <\/b>Novel insight into the lipid network of plasma extracellular vesicles reveal sex-based differences in the lipidomic profile of <\/span>alcohol use disorder<\/b> patients. <\/span><\/span>\u00a0<\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
          3. MetaFun-SAL: <\/b><\/span>Lipidomic landscape of circulating extracellular vesicles isolated from adolescents exposed to<\/span> ethanol intoxication<\/b>: a sex difference study.<\/span> <\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a>.<\/span><\/li>\n<\/ol>\n<\/li>\n<\/ol>\n
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            D) Metabolic diseases tools<\/b><\/span><\/h3>\n

            Open tools for the analysis of metabolic disease omics data:<\/b><\/span><\/p>\n

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            1. MetaFun-NAFLD<\/b>: <\/span><\/span>Hepatic steatosis and steatohepatitis<\/b>: a functional meta-analysis of sex-based differences in transcriptomic studies. <\/span><\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
            2. MetaFun-HFD<\/b><\/span>:<\/span> Integrated transcriptomic landscape of the effects of anti-steatotic treatments in mouse models of <\/span>fatty liver disease<\/b>.<\/span><\/span> Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n
            3. MetaFun-HKG<\/b>: <\/span><\/span>Deciphering the sex bias in <\/span>housekeeping gene expression in adipose tissue<\/b>.\u00a0 <\/span><\/span>Webtool<\/span><\/a>. <\/span>Publication<\/span><\/a><\/li>\n<\/ol>\n
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              E) Sex differences tools<\/b><\/span><\/h3>\n

              Tools to identify and understand the molecular mechanisms underlying sex differences in biomedical studies:<\/b><\/span><\/p>\n

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              1. Brain diseases:\u00a0\u00a0<\/b><\/span>\n