Illumina provides some nice software (called CASAVA) that is typically run at the default settings by Core labs and sequencing outsourcing companies. This software gives high-quality genome alignments and pretty good SNP calls - useful for many purposes. However, real-world research needs are often not satisfied with default automated bioinformatics analysis. Narrowing down hundreds of thousands of SNP calls to the few real disease-related mutations is difficult hands-on work for skilled bioinformaticians. Today in my lab group, we are fighting with false-negatives: SNPs that were present but not called in the germ line sample, leading to false identification of mutations unique to the tumor. It looks like we will have to re-run the SNP detection software many times with small changes in various parameters to optimize specificity vs. sensitivity in each sample. Investigators may sub-contract this type of work to the lab that does the sequencing, they may have skilled bioinformaticians in their lab group, or they may hire bioinformatics consultants. In any case, $1K of sequence data may cost more than $10K for analysis.
Gene signatures from tissue-resident T cells as a predictive tool for
melanoma patients
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[image: rna-seq]
An extensive analytical study conducted at the Terasaki Institute for
Biomedical Innovation (TIBI) has revealed an association between fa...
22 hours ago
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