Brief description of philosophy, commands, and functions of NMRPipe: Difference between revisions
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There are many softwares available today for processing NMR data and this task usually involves processing the time domain signal | There are many softwares available today for processing NMR data and this task usually involves processing the time domain signal a frequency domain spectrum using Fourier transform along with different mathematical functions (see section 1.4 of this article for brief description of commonly used functions) to adjust the spectrum. The NMRPipe data processing program is widely used in the scientific community and consists of a number of functions that are link together via UNIX pipes. A second program called ‘nmrDraw’ (part of the NMRPipe package) is used to visualize and inspect the processed NMR data. The nmrDraw program provides basic functions such as drawing contours, vertical or horizontal traces, peak picking, and integration. The NMR data processing methods described in this TWiki are the routine procedures commonly used in the NESG community. For more detailed information on the functionality of NMRPipe, please visit the web pages of NMRPipe. The general workflow of NMRPipe is as follows: | ||
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Step 6: Spectra format conversion to Sparky, CARA, XEASY or NMRViewJ | Step 6: Spectra format conversion to Sparky, CARA, XEASY or NMRViewJ | ||
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Revision as of 18:19, 4 December 2009
NMR Data Processing > Overview
Brief Description
There are many softwares available today for processing NMR data and this task usually involves processing the time domain signal a frequency domain spectrum using Fourier transform along with different mathematical functions (see section 1.4 of this article for brief description of commonly used functions) to adjust the spectrum. The NMRPipe data processing program is widely used in the scientific community and consists of a number of functions that are link together via UNIX pipes. A second program called ‘nmrDraw’ (part of the NMRPipe package) is used to visualize and inspect the processed NMR data. The nmrDraw program provides basic functions such as drawing contours, vertical or horizontal traces, peak picking, and integration. The NMR data processing methods described in this TWiki are the routine procedures commonly used in the NESG community. For more detailed information on the functionality of NMRPipe, please visit the web pages of NMRPipe. The general workflow of NMRPipe is as follows:
Step 1: Converting the data from spectrometer format to NMRPipe format
Step 2: Time domain data inspection using nmrDraw
Step 3: Trial processing for initial phasing and applying mathematical functions
Step 4: Inspection of the trial processed spectrum via nmrDraw
Step 5: Final processing
Step 6: Spectra format conversion to Sparky, CARA, XEASY or NMRViewJ
Software Information
NMRPipe (download information and user manual)
http://spin.niddk.nih.gov/NMRPipe/
Brief descriptions of specific functions are accessible via nmrPipe –
‘nmrPipe –help’ will list most functions
‘nmrPipe –fn GM –help’ will give description of the GM function.
Supported Platform
Linux (RedHat Linux/Fedora)
Mac OS X (10.3.4 and up)
SGI Irix (6.2 and up)
Sparc Solaris (2 and up)
Windows XP Pro with Microsoft Services for UNIX (SFU 3.5).
Commonly Used Processing Functions in NMRPipe
The processing functions describe here are the most commonly used for processing NMR spectra of protein. For the advance features, please visit the help pages of NMRPipe.
Solvent Suppression: removes residual solvent.
‘SOL’ solvent filter
‘POLY –time’ time-domain correction for solvent subtraction
Baseline correction: removes dc offsets and baseline imperfection due to tilting, bowing, or rolling.
‘CBF’ DC correction
‘POLY –auto’ automatically generate a polynomial baseline correction
Apodization: removes artifact and improve S/N
‘em –lb 1.0’ exponential line broadening
‘SP –off 0.5’ sine bell (offset by 90 degree, equivalent to cosine)
Zero fill the data: One can add zeros to the end of the fid so that there are more points in the final Fourier transformed spectrum. This will smooth the data and increase the resolution to some degree.
‘zf –auto’ round up the number of points to the nearest power of 2
‘zf –size 16384’ zero fills up to 16384 points
Linear prediction: instead of adding zeros, one can calculate additional points based on a mathematical analysis of the existing fid.
‘lp –fb’ uses default values and doubles the size of the fid to increase digital resolution.