R value: Difference between revisions
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As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60. | As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60. | ||
However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name= | However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name="Karplus">PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal when data quality is limiting model improvement <ref name="Karplus" />. | ||
One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid. | One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid. |