Search our database of validated splicing mutations

Populate search field with a sample mutation (ATM), a sample mutation (TP53), or a pair of variants (natural, cryptic) in linkage disequalibrium

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A manuscript describing this resource is available through F1000Research (direct link to pdf) and is pending peer-review
Shirley BC, Mucaki EJ, Rogan PK. Pan-cancer repository of validated natural and cryptic mRNA splicing mutations [version 1; referees: awaiting peer review]. F1000Research 2018, 7:1908 (

Information Theory is proven to accurately predict the impact a mutation has on mRNA splicing, and has been used to interpret coding and non-coding mutations that alter mRNA splicing in both common and rare diseases (Caminsky et al., 2014; Burke et al., 2018; Dos Santos et al., 2018; Yang et al., 2017; Caminsky et al., 2016; Mucaki et al., 2016; Peterlongo et al., 2014; Mucaki et al., 2013; Mucaki et al., 2011; Rogan et al., 2003; Rogan et al., 1998; Rogan and Schneider, 1995). Mucaki et al. (2016) describes an information-theory based framework for the interpretation and prioritization of non-coding variants of uncertain significance, which has been applied in multiple studies involving novel variants in cancer patients (Burke et al., 2018; Dos Santos et al., 2018; Caminsky et al., 2016; Mucaki et al., 2016). The Information-Theory based software used in these studies is available in the bioinformatic suite MutationForecaster ( This resource includes the Shannon Pipeline (which can quickly analyze millions of variants for their impact on mRNA splicing; Shirley et al., 2013) and Veridical (which validates Shannon Pipeline output by analyzing RNAseq BAM files for mutated splicing in patients with the variant of interest; Viner et al., 2014 and Dorman et al., 2014).

The Cancer Genome Atlas (TCGA) provides genomic data from thousands of patients of 33 different types of cancer. Using the Shannon Pipeline and Veridical, we analyzed over 168 million variants from TCGA data set, and validated 351,423 variants for their direct impact on mRNA splicing. The user can query the resource for a mutation (or a range of coordinates containing mutations). This resource provides the user with the expected change in splice site strength caused by the variant of interest, and the observed mutant splicing event (i.e. sequencing reads which indicate cryptic site use). For some mutations, an image of the RNAseq data for the region of interest is provided. Expression levels of the gene containing the mutation can also be toggled for different tissues.

The following is a breakdown of all unique splicing mutations found in each TCGA tumor type (variants unique in a per-tissue basis; novel or < 1% of population [dbSNP150] are counted):

Tumor TypeTumor Description# Unique Variants
TCGA-ACCAdrenocortical Carcinoma783
TCGA-LAMLAcute Myeloid Leukemia12179
TCGA-BRCABladder Urothelial Carcinoma22046
TCGA-BLCABreast Invasive Carcinoma9832
TCGA-CESCCervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma18078
TCGA-COADColon Adenocarcinoma7777
TCGA-DLBCLymphoid Neoplasm Diffuse Large B-cell Lymphoma1798
TCGA-ESCAEsophageal Carcinoma7678
TCGA-GBMGlioblastoma Multiforme1108
TCGA-HNSCHead and Neck Squamous Cell Carcinoma2749
TCGA-KICHKidney Chromophobe25241
TCGA-KIRCKidney Renal Clear Cell Carcinoma5208
TCGA-KIRPKidney Renal Papillary Cell Carcinoma4707
TCGA-LGGBrain Lower Grade Glioma1344
TCGA-LIHCLiver Hepatocellular Carcinoma11234
TCGA-LUADLung Adenocarcinoma12702
TCGA-LUSCLung Squamous Cell Carcinoma2636
TCGA-OVOvarian Serous Cystadenocarcinoma85841
TCGA-PAADPancreatic Adenocarcinoma1497
TCGA-PCPGPheochromocytoma and Paraganglioma82
TCGA-PRADProstate Adenocarcinoma867
TCGA-READRectum Adenocarcinoma3464
TCGA-SKCMSkin Cutaneous Melanoma11548
TCGA-STADStomach Adenocarcinoma13404
TCGA-TGCTTesticular Germ Cell Tumors168
TCGA-THCAThyroid carcinoma55686
TCGA-UCECUterine Corpus Endometrial Carcinoma19936
TCGA-UCSUterine Carcinosarcoma3333
TCGA-UVMUveal Melanoma792