[930d1e]: / GoogleCloud / quizes / Chapter8_Quizes.json

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[
{
"question": "A volcano plot:",
"type": "many_choice",
"shuffle_answers": true,
"answers": [
{
"answer": "compares p-value with fold change.",
"correct": true,
"feedback": "Correct. The volcano plot is used to identify statistically significant differences in protein levels."
},
{
"answer": "fold change versus mean expression.",
"correct": false,
"feedback": "Incorrect. An MA plot measures fold change vs. mean expression."
},
{
"answer": "Compares two conditions.",
"correct": true,
"feedback": "Correct. The left and right sides of the plot indicate the different conditions."
},
{
"answer": "is a clustering algorithm.",
"correct": false,
"feedback": "Incorrect. A volcano plot does not cluster data."
}
]
},
{
"question": "The fanning effect in an MA plot is caused by:",
"type": "many_choice",
"shuffle_answers": true,
"answers": [
{
"answer": "the fact that low expression features tend to be more variable in fold change than high expression features.",
"correct": true,
"feedback": "Correct."
},
{
"answer": "the fact that high expression features tend to be more variable in fold change than low expression features.",
"correct": false,
"feedback": "Incorrect."
},
{
"answer": "Most features show no expression.",
"correct": false,
"feedback": "Incorrect. The MA plot shows this observation to be true but it's not responsible for the fanning effect."
},
{
"answer": "outliers in the data.",
"correct": false,
"feedback": "Incorrect. Outliers might increase the rate of false positives but are not responsible for the fanning effect."
}
]
},
{
"question": "The following methods may be used following an omics analysis to confirm the biological significance of your results:",
"type": "many_choice",
"shuffle_answers": true,
"answers": [
{
"answer": "Pathway analysis",
"correct": true,
"feedback": "Correct. Pathway analysis will present your results from a biological network perspective, providing additional biological context to your results.."
},
{
"answer": "Meta-analysis",
"correct": true,
"feedback": "Correct. Properly comparing results across laboratories can increase the statistical power of your results."
},
{
"answer": "Experimental validation",
"correct": true,
"feedback": "Correct. Experimental validation of omics results ensures that you aren't observing computational artifacts from your data analysis."
},
{
"answer": "Logistic regression",
"correct": false,
"feedback": "Incorrect. While logistic regression and classification might be relevant to your research, it does not provide additional biological context to your results."
},
{
"answer": "PCA",
"correct": false,
"feedback": "Incorrect. While PCA can identify which features are likely driving patterns in your data, it does not give you a verified biological reason why."
},
{
"answer": "Machine learning",
"correct": false,
"feedback": "Incorrect. Sophisticated ML algorithms may have high accuracy when predicted results, but in and of themselves to not provide biological validation."
}
]
}
]