30-40 samples total.
Two groups- patients and controls (paired by gender and age)
Group sizes are ~50\50%
To avoid batch effects, cell samples were randomized to sets (in accordance to extraction groups) and matched samples were kept in the same set.
The same for growth conditions
We want to examine differences in gene expression (and regulation) between these two groups.
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How many groups in the experiment? How many samples per group? Are they paired samples (i.e. pre and post treatment?) What's the actual experimental setup? What question are you trying to answer? Where your samples RNA extracted on the same day? Libraries prepped on the same day? With the same reagents? What possible batch effects are there in your setup?
Very hard to advise on anything other than to argue that biological replicates are important and technical replication largely unecessary.
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Human Fibroblasts
Hi all,
Wanted to ask for suggestions-comments-opinions regarding this experiment;
We are planning to sequence total RNA from 30 samples of human fibroblasts (literature points out that this type of cells are quite noisy).
We are looking for DE genes, splicing variants and even novel isoforms.
For that, total RNA will be extracted using the mirNeasy kit and then divided to two sequencing assays;
1. Transcriptome sequencing, library construction by Illumina TruSeq stranded Total RNA library (RiboZero Gold rRNA removal). Run: NovaSeq 2X150bp, 60M reads per sample (=30M paired read per sample)
2. smRNA sequencing, library construction using Illumina TruSeq small RNA library construction. Run : Hiseq 2500 rapid run mode, 1X50bp, 125M reads per lane (10-12 samples per lane).
There will be no biological replicates due to passage limitations.
After a few considerations, we have decided not to sequence technical repeats.
We are aware that 60M reads per sample may not be sufficient for novel isoforms, but budget limitations exist.
Many Thanks,
Mark
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Innovations in next-generation sequencing technologies and techniques are driving more precise and comprehensive exploration of complex biological systems. Current advancements include improved accessibility for long-read sequencing and significant progress in single-cell and 3D genomics. This article explores some of the most impactful developments in the field over the past year.
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