questions regarding phenix.table_one
Dear all, I’m using phenix.table_one to prepare the statistics to include in the paper, and came up with a question regarding the number of reflections being reported. For example, one of the structures has the following statistics: Unique reflections: 70764 (7064) Reflections used in refinement: 70731 (7019) Reflections used for Rfree : 3523 (371) Clearly 70731+3523 is greater than 70764. So I’m puzzled here. I guess “Reflections used in refinement” number actually equals to the sum of "Reflections used for Rfree”+”Reflections used for Rwork”. If this is true then I would just do a simple calculation myself to get the ”Reflections used for Rwork”. Another question is I’m seeing “Reflections used in refinement” always a little smaller than “Unique reflections”. I guess it’s because there’s an outlier rejection in certain step but not sure. I’d be grateful for any clarification. thanks ! Regards, Wei
Hello Wei, this looks puzzling indeed.. Would you mind sharing files off list for our internal investigation of this issue? Needless to say we won't share your files with anyone outside the Phenix developers team. Pavel
Dear all,
I’m using phenix.table_one to prepare the statistics to include in the paper, and came up with a question regarding the number of reflections being reported. For example, one of the structures has the following statistics:
Unique reflections: 70764 (7064) Reflections used in refinement: 70731 (7019) Reflections used for Rfree : 3523 (371)
Clearly 70731+3523 is greater than 70764. So I’m puzzled here. I guess “Reflections used in refinement” number actually equals to the sum of "Reflections used for Rfree”+”Reflections used for Rwork”. If this is true then I would just do a simple calculation myself to get the ”Reflections used for Rwork”.
Another question is I’m seeing “Reflections used in refinement” always a little smaller than “Unique reflections”. I guess it’s because there’s an outlier rejection in certain step but not sure.
I’d be grateful for any clarification. thanks !
Regards,
Wei
participants (2)
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Pavel Afonine
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Wei Wang