If I have for example 5 to 10 samples of a few different developmental time periods that I want to compare gene expression, what should be my pick for accuracy? Splicing info is interesting but not a deal breaker.
-
Any need for antibodies, viral antigens, innovative diagnostic components and critical assay reagents, please visit here. -
Thanks in advance!Any need for antibodies, viral antigens, innovative diagnostic components and critical assay reagents, please visit here. -
Depends on your experiment and your situation! Do you have access to RNA-seq and/or microarray in house or will you outsource? Is there a bioinformatics group who can at least do the sequence alignment and read counting part of the analysis for you? Personally I can't see why I'd ever do microarray again because I can get RNA-seq done in house cheaply and easily, there's a pipeline to do the alignment, and I've analysed it before. That's before you consider the benefits of dynamic range, sensitivity etc. OTOH, the benefit of microarray is that you get nice easy CEL files back and the analysis is easy.
Take care of your experimental design... Replicates are important to estimate within-group variance. Don't bother doing paired end seq if you just want to measure gene level expression, single end is cheaper per read and so more cost effective. No need to go above 15-20M reads per sample unless you're really interested in low expressers, spend the money on more reps instead.Comment
-
Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing... -
The immune system’s power comes from its genetic diversity, allowing myriad threats to be neutralized through first recognizing foreign antigens. That diversity is also what makes the immune system so difficult to study. Recent advances in sequencing technology and computational biology, however, are giving researchers new tools to understand immune responses and immune-related diseases in greater detail.
This convergence of genetics, immunology, and computation...09-01-2026, 05:41 AM
Comment