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- Before You Start
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Before You Start
Contact the GHTF to schedule a consultation about experimental design. Below are a number of commonly asked questions to help you begin planning your experiment. Please consult with us to let us know the time frame of your experiment and to give you an idea of our current workload.
How to calculate expected coverage from a next gen sequencing experiment.
Currently a good library will give 180 to 200 million reads per lane on the HiSeq 2000 with the version 3 chemistry. Thus to calculate expected coverage you multiply the number of reads by the number of cycles run. For example, if a paired end 100 cycle run is done the expected number of reads is 100,000,000 reads x 100 cycles x 2 ends = 20,000,000,000 or 20 GB
However, only about 90% of reads typically map to a reference genome.
Suggestions for making next gen sequencing libraries
Our first choice for making RNA-Seq libraries is the Epicentre ScriptSeq kit. The advantage to this kit is that it uses ribosomal RNA depletion, random priming and maintains the transcribed strand information. However, a minimum of 5 ug of total RNA is required for the initial rRNA removal. Also, if you are using RNA isolated from cultured cells which have mycoplasma contamination the mycoplasma RNA will show up in your library and sequence data. Library kits using oligo-dT priming rather than random priming are also available. NOTE you MUST DNase treat your RNA! If you don't DNase treat your RNA roughly 20% of your library may be mitochondrial DNA.
For paired end genomic DNA libraries we recommend the NuGen Encore NGS System, the Bioo Scientific NextFlex DNA Sequencing Library Prep kit or the Illumina TruSeq kit. These have given good sequenciing results in the GHTF.
For whole exome libraries, the Agilent, Roche (Nimblegen) and Illumina TruSeq all work well. However, Agilent and Roche whole exome kits are much cheaper than the Illumina TruSeq whole exome kit.
- Can you suggest any good references in preparing for a second generation sequencing or microarray experiment?
- Applications of next-generation sequencing
- RNA-Seq: a revolutionary tool for transcriptomics
- Advancing RNA-Seq analysis
- Next-generation sequencing transforms today's biology
- Next-Generation Sequencing: From Basic Research to Diagnostics
- Sequencing technologies — the next generation
- Characterizing and Measuring Sequence Bias
- Evaluation of next generation sequencing platforms for population targeted sequencing studies
- Expression Profiling - Best Practices for Data Generation and Interpretation in Clinical Trials.
- The Use and Analysis of Microarray Data.
- Multiple-laboratory comparison of microarray platforms
- Independence and reproducibility across microarray platforms
- Standardizing global gene expression analysis between laboratories and across platforms
- What experimental variables may affect my second generation sequencing or microarray experiments?
- Sample collection and nucleic acid isolation. All variables that you do not want to study should remain the same. In other words, samples should be collected at the same time of day, the same amount of time after watering or feeding.
- DNA and RNA concentration and quality should be checked on a reliable spec. We have a NanoDrop Spectrophotometer available to read low volumes. Make sure the amount of starting material is the same for every library or chip in the experiment. We also have a Qubit fluorometer for quantifying low concentrations of nucleic acids. For next generation sequencing library quantification we recommend Q-PCR quantification with the KAPA Library Quant Kit.
- Using different technicians, equipment and a variety of reagent lots may also affect your results.
- How many replicates should I use in my experiment?
To be able to use standard T-tests, you should have at least 3 replicates. ANOVA would need 5 replicates. The more replicates you have the lower the False Discovery Rate (FDR).