lncExplore Tutorial:
  1. Overview
  2. In lncExplore you can browse or search
  3. The Framework of lncExplore construction
  4. The comparison of lncExplore with other lncRNAs-related database
     Search Menu
     Disease specificity
     Clinical Analysis
     Enhancer RNA
     ceRNA Network
  6. The list of the RNA-seq datasets


Over the past few years, with the rapid growth of deep-sequencing technology and the development of computational prediction algorithms, a large number of lncRNAs have been identified in various types of human cancers. Functional annotations for lncRNAs data have become an important task for biological and clinical researchers.

In this study, we used transcriptome sequencing to identify potential functions of lncRNAs from 5034 TCGA RNA-sequencing datasets covering 24 cancers. The lncExplore database provides distinctive features including: (1) novel lncRNAs verified by both coding potential and translation efficiency scores, (2) genome annotations of lncRNAs, such as their cis-regulatory information and related GO terms, (3) regulatory annotations as eRNAs or ceRNAs, (4) real-time expression correlation between lncRNA and any RNA of interest.

Beside the knowledge of molecular biology level, we also present pan-cancer analysis for lncRNAs expression comparison across 24 human cancers. By integrating clinical information and disease specificity score, lncRNAs become potential biomarkers for specific cancer types, with support from survival curve analysis. The lncExplore database is to our knowledge the first lncRNA annotation database that provides disease-specific expression profiles, eRNA/ceRNA annotations, and pan-cancer analysis with clinical evidence.

In lncExplore you can browse or search:

  1. Novel lncRNAs predicted from TCGA RNA-sequencing datasets

  2. Basic genome annotation: location, sequence, gene ontology and in silico predicted targeted coding gene

  3. Regulatory annotations: enhancer RNAs and competing endogenous RNAs (miRNA binding sites in lncRNAs)

  4. Pan-cancer analysis for lncRNAs expression comparison across 24 human cancers

  5. lncRNAs-disease association: disease specificity score and clinical survival analysis

The Framework of lncExplore construction

Identify novel lncRNAs from RNA-seq datasets across 24 human cancers

Comprehensive annotation of lncRNA from different aspects including expression profile, gene ontology enrichment analysis, disease specificity score, potential regulatory role (eRNAs, and ceRNAs), and survival curve analysis

The comparison of lncExplore with other lncRNAs-related database:

Abbreviation: NA, not Available
Table1. The Comparison of lncExplore with available lncRNA bioinformatic resources


  1. Search Menu

    Search results -- sequence annotations:
    Step 1: Select ID type (ENSEMBL ID, lncExploree ID, or Gene Symbol) and Input your lncRNAs IDs
    Step 2: lncRNA annotation:

    Basic information: sequence, coding potential, disease specificity score
    Cis-regulatory: We searched coding genes 10k/100k upstream and downstream of lncRNA as the cis target gene
    Gene-Ontology: biological process (from Cis-regulatory 100k population), molecular function, cellular component. The GO results included p-value, q-value (fdr), fold enrichment and significant. Significant: the number of genes annotated with the term.

  2. Expression
    Search results -- lncRNAs expression profile:
    Step 1: Select ID type (ENSEMBL ID, lncExploree ID, or Gene Symbol) and Input your lncRNAs IDs
    Step 2: A bar chart and a box plot will visualize the expression profiles of lncRNAs across different cancers
    Search results: comparison between two RNA transcripts:
    Step 1: Select ID type (ENSEMBL ID, lncExplore ID, and Gene Symbol) and Input your lncRNAs IDs.
    Step 2: A bar chart and a box plot will visualize the expression profiles of lncRNAs across different cancers.
    Step 3: A Pearson correlation coefficient will measure the strength of a linear association between two transcripts.
    Search results: Compare the Expression of Pairwise Datasets:
    SStep1: Select disease name and enter gene IDs (Eensembl ID, gene symbol or lncExplore ID).
    Step2: The scatter plot will visualize the pairwise comparison results.

  3. Disease specificity
    Search results -- disease specificity score:

    Step 1: Search Disease Specificity using genomic coordinate and the region of Disease Specificity Score

    Step 2: This score reflects expression preferentially of the lncRNA contributed to a particular tissue. The score varies from 0 to 1. A score close to 1.0 indicates that lncRNA signature is restricted to specific tissues or cell lines and provides an important clue about biomarker candidate.

  4. Clinical Analysis
    Search results -- survival curve analysis:

    Step 1: Choose the specific disease, gene identifier ( Ensembl ID, gene symbol or lncExplore ID) and quartile value.
    Step 2: Clinical information and lncRNA expression values will be integrated into a survival curve analysis. This provides useful information for evaluating the potential of the lncRNA as a biomarker.

  5. Enhancer RNA
    Search results -- eRNA annotation:

    Step 1: Search Enhancer RNA using genomic coordinate or adjacent known transcripts
    Step 2: A list of genome-wide identified eRNAs will be provided based on the genomic information of the enhancer regions from VISTA database and ENSEMBL.

  6. ceRNA Network
    Search results -- ceRNA annotation:

    Step 1: Enter a transcript identifier or miRNA identifier, for instance, has-miR-100-30 for browsing which microRNAs have interaction with ncT0114002055.
    Step 2: A list of precompiled interactions of miRNA and lncRNAs predicted by TargetScan will be provided.

The list of the RNA-seq datasets

Abbreviation Full Names Samples
ACC Adrenocortical carcinoma 79
BLCA Bladder Urothelial Carcinoma 181
BRCA Breast invasive carcinoma 233
CESC Cervical squamous cell carcinoma and endocervical adenocarcinoma 253
COAD Colon adenocarcinoma 277
DLBC Lymphoid Neoplasm Diffuse Large B-cell Lymphoma 43
GBM Glioblastoma multiforme 167
HNSC Head and Neck squamous cell carcinoma 285
KICH Kidney Chromophobe 66
KIRC Kidney renal clear cell carcinoma 448
KIRP Kidney renal papillary cell carcinoma 225
LGG Lower Grade Glioma 347
LIHC Liver hepatocellular carcinoma 208
LUAD Lung adenocarcinoma 432
LUSC Lung squamous cell carcinoma 482
PAAD Pancreatic adenocarcinoma 123
PCPG Pheochromocytoma and Paraganglioma 184
PRAD Prostate adenocarcinoma 167
READ Rectum adenocarcinoma 164
SARC Sarcoma 183
SKCM Skin Cutaneous Melanoma 125
THCA Thyroid carcinoma 133
UCS Uterine Carcinosarcoma 57
UCEC Uterine Corpus Endometrial Carcinoma 172