Host pathogen interaction long read transcriptome

Study ID Alternative Stable ID Type
EGAS00001006779 Other

Study Description

Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants ... (Show More)

Study Datasets 1 dataset.

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Dataset ID Description Technology Samples
Long-read (PacBio) RNA sequencing dataset of in vitro stimulated PBMC cells. 5 samples consisting of 1 RPMI control and 4 stimulus conditions (lipopolysaccharide (LPS), polyI-polyC, S. aureus and C. albicans) all originating from one donor. Files are raw BAM format files generated by Sequel 2 machine.
Sequel 5

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