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.
TDEseq – temporal gene expression patterns from multi-sample multi-stage
single-cell transcriptomics data
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[image: rna-seq]
A new statistical method called TDEseq is poised to revolutionize the way
we study temporal gene expression dynamics in single-cell RNA s...
1 day ago
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