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+---
+layout: minimal
+authors:
+ - "[cbenoit](www.linkedin.com/in/clement-benoit)"
+date: 2024-02-15
+---
+
+# Experimental design in the context of next generation sequencing
+
+## Introduction
+
+Coming from a biotechnology background, I was sensitized to the problems of experimental design. I then spent a few years as a bioinformatician, leaving this task to my platform colleagues.
+
+As a bioinformatician, you focus on producing quality pipelines and algorithms for processing sequencer output.
+But we sometimes forget that, without good experimental design, we run the risk of being unable to draw conclusions,
+or even of unwittingly producing false positives.
+
+Here's a brief overview of the main considerations for experience designers.
+
+## Next generation sequencing specificities
+
+We need to bear in mind that everything starts with biological material, from which we want to extract informative biological sequences, to answer a precise question.
+The difficulty lies in extracting useful information without confusing it with other factors: background noise, bias...
+
+The sample is first taken from its environment, by which it will have been impacted.
+The interaction of the biological material with its environment,
+as well as the sampling carried out, already constitute a first source of variance.
+
+# Methodology
+
+1. **Clearly define the question posed and the technology chosen to answer it.**
+2. **Control the experimental variables**
+Variables to control can include sample preparation techniques, sequencing parameters and environmental conditions. Ensure that the impact of this factors
+on your data is minimized and controled to isolate the impact of the specific variables of interest, enhancing ythe reliability of the results.
+3. **Randomization techniques**
+4. **Replication Strategies**
+
+
+
+
+{/* [^1], [^2], [^3] */}
+
+{/* [^1]: Doe, J., & Smith, A. (Year). *Title of the Publication*. **Journal Name**, Volume(Issue), Page Range. [DOI](https://doi.org/xxxx) */}
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