Hi Hugo,
If you scale to the smaller pixel, then the rest of Fourier space is left
at zeros. Sometimes it is easier though: you have to rescale particles to
an even image size that represents a very similar angstrom/pixel value.
This problem would be much less relevant if you'd rescale the entire (much
larger) micrographs, but that would also mean re-scaling the picked
coordinates. Therefore, rescaling particles is easier, although the
discretization oof rescaling may sometimes present problems.
HTH,
Sjors
> Dear all,
>
> This is an interesting topic and I have some doubts.
>
> You are talking about rescale one data set but Can you rescale the
> bigger pixel to the smaller? I mean if you have two data sets, the first
> one is at 1 A/pix and the second one at 2 A/pix, Is possible to rescale
> 2 A/pix to 1 A/pix.
> Images from 2 A/pix might loose information and I guess the information
> should be duplicate or filled the gaps somehow. How does it work?
>
> Thank you
>
> Best
>
> Hugo
>
> --
> Hugo Muñoz Hernández, PhD student
>
> Centro de Investigaciones Biológicas CIB-CSIC
> Consejo Superior de Investigaciones Científicas
> C/ Ramiro de Maeztu, 9
> 28040 Madrid (Spain)
>
> http://www.cib.csic.es/es/grupo.php?idgrupo=47
>
> Tel: +34 91 8373112 ext 4436, Lab.B-47
>
>
>
> On 16/02/16 10:09, Sjors Scheres wrote:
>> Dear Arko,
>> You could rescale one data set to a pixel size as similar as possible as
>> the other one, and process the 2 data sets together. In that case be
>> alert
>> of classification into the original 2 data sets.
>> Alternatively, you could rescale and align the 2 unfil.mrc half-maps of
>> one data set on top of the half-maps from the other data set. Then, add
>> the half1 maps from both data sets together, as well as the half2 maps.
>> You can then perform postprocessing on the 2 summed half-maps to get
>> your
>> combined map.
>> HTH,
>> Sjors
>>
>>> Dear CCPEM-ers,
>>>
>>> I would like to have some advice on the optimal way to combine two data
>>> sets for single particle reconstruction in relion-should that be
>>> performed
>>> at the stage of 3D classification (averaging 3D classes?) or after 3D
>>> refinement (averaging the 3D volumes obtained in each case)? (in the
>>> later
>>> case how would one go about calculating 'gold standard' FSC?..Would it
>>> be
>>> advisable to average the final volumes obtained by separate processing
>>> of
>>> the two datasets?..Is there a possibility of combining the data sets
>>> from
>>> scratch? (how to bring the images onto a common scale in that case)?.
>>> Any
>>> inputs and/or practical advices will be greatly appreciated.
>>>
>>> Best regards,
>>>
>>> Arko
>>>
>>> --
>>> *Arka Chakraborty*
>>> *ibmb (Institut de Biologia Molecular de Barcelona)*
>>> *BARCELONA, SPAIN*
>>>
>>
>
> --
> Hugo Muñoz Hernández, PhD student
>
> Centro de Investigaciones Biológicas CIB-CSIC
> Consejo Superior de Investigaciones Científicas
> C/ Ramiro de Maeztu, 9
> 28040 Madrid (Spain)
>
> http://www.cib.csic.es/es/grupo.php?idgrupo=47
>
> Tel: +34 91 8373112 ext 4436, Lab.B-47
>
--
Sjors Scheres
MRC Laboratory of Molecular Biology
Francis Crick Avenue, Cambridge Biomedical Campus
Cambridge CB2 0QH, U.K.
tel: +44 (0)1223 267061
http://www2.mrc-lmb.cam.ac.uk/groups/scheres
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