Mercurial > repos > galaxyp > maldi_quant_peak_detection
changeset 4:e9300ef37403 draft
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/MALDIquant commit ecdc3a64aa245d80dbc5487b2bf10a85a43adc6d
| author | galaxyp |
|---|---|
| date | Fri, 22 Mar 2019 08:26:23 -0400 |
| parents | 36d38d2cf88c |
| children | e66f552a3c47 |
| files | maldi_quant_peakdetection.xml |
| diffstat | 1 files changed, 43 insertions(+), 18 deletions(-) [+] |
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--- a/maldi_quant_peakdetection.xml Fri Feb 15 10:26:45 2019 -0500 +++ b/maldi_quant_peakdetection.xml Fri Mar 22 08:26:23 2019 -0400 @@ -1,4 +1,4 @@ -<tool id="maldi_quant_peak_detection" name="MALDIquant peak detection" version="@VERSION@.3"> +<tool id="maldi_quant_peak_detection" name="MALDIquant peak detection" version="@VERSION@.4"> <description> Peak detection, binning and filtering for mass-spectrometry imaging data </description> @@ -128,10 +128,12 @@ ## plot input file spectrum: #if $centroids: ## Choose random spectra for QC plots + print(length(peaks)) random_spectra = sample(1:length(peaks), 4, replace=FALSE) + random_spectra_name = pixelnames[random_spectra] par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(peaks[[random_sample]],sub="", main=paste0("spectrum ", random_sample))} + plot(peaks[[random_sample]],sub="", main=paste0("spectrum ", pixelnames[random_sample]))} title("Input spectra", outer=TRUE, line=0) #else @@ -139,7 +141,8 @@ random_spectra = sample(1:length(maldi_data), 4, replace=FALSE) par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(maldi_data[[random_sample]],sub="", main=paste0("spectrum ", random_sample))} + plot(maldi_data[[random_sample]],sub="", main=paste0("spectrum ", pixelnames[random_sample])) + } title("Input spectra", outer=TRUE, line=0) #end if @@ -223,7 +226,7 @@ par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ noise = estimateNoise(maldi_data[[random_sample]], method= "$method.methods_conditional.peak_method") - plot(maldi_data[[random_sample]], sub="", main=paste0("spectrum ", random_sample)) + plot(maldi_data[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample])) lines(noise[,1], noise[,2]*$method.methods_conditional.snr, col="blue") points(peaks[[random_sample]], col="green", pch=20)} title("S/N in blue and picked peaks in green", outer=TRUE, line=0) @@ -231,7 +234,7 @@ ## plot new spectrum par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", random_sample))} + plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample]))} title("Picked peaks", outer=TRUE, line=0) pixel_number = length(peaks) @@ -268,20 +271,20 @@ peaks = monoisotopicPeaks(peaks, minCor=$method.methods_conditional.minCor, tolerance=$method.methods_conditional.tolerance, - distance=$method.methods_conditional.distance, + distance=c($method.methods_conditional.distance), size=$method.methods_conditional.size) ## plot old spectrum with picked isotopes as green dots par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(picked_peaks[[random_sample]], sub="", main=paste0("spectrum ", random_sample)) + plot(picked_peaks[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample])) points(peaks[[random_sample]], col="green", pch=20)} title(paste0("Monoisotopic peaks in green"), outer=TRUE, line=0) par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", random_sample))} + plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample]))} title("Monoisotopic peaks", outer=TRUE, line=0) minmz = round(min(unlist(lapply(peaks,mass))), digits=4) @@ -365,7 +368,7 @@ ## QC plot and numbers par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", random_sample))} + plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample]))} title("Aligned spectra", outer=TRUE, line=0) minmz = round(min(unlist(lapply(peaks,mass))), digits=4) maxmz = round(max(unlist(lapply(peaks,mass))), digits=4) @@ -400,7 +403,7 @@ ## QC plot and numbers par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", random_sample))} + plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample]))} title("Binned spectra", outer=TRUE, line=0) minmz = round(min(unlist(lapply(peaks,mass))), digits=4) maxmz = round(max(unlist(lapply(peaks,mass))), digits=4) @@ -451,7 +454,7 @@ ##QC plot and numbers par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ - plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", random_sample))} + plot(peaks[[random_sample]], sub="", main=paste0("spectrum ", pixelnames[random_sample]))} title("Filtered spectra", outer=TRUE, line=0) minmz = round(min(unlist(lapply(peaks,mass))), digits=4) maxmz = round(max(unlist(lapply(peaks,mass))), digits=4) @@ -550,7 +553,7 @@ <conditional name="methods_conditional"> <param name="method" type="select" label="Select a method"> <option value="Peak_detection">Peak detection</option> - <option value="monoisotopic_peaks">Keep only monoisotopic peaks</option> + <option value="monoisotopic_peaks">Monoisotopic peaks</option> <option value="Align">Align Spectra (warping/phase correction)</option> <option value="Binning">Binning</option> <option value="Filtering">Filtering</option> @@ -571,11 +574,25 @@ </when> <when value="monoisotopic_peaks"> <param name="minCor" type="float" value="0.95" label="Minimal correlation" - help="Minimal correlation between the peak pattern generated by the model and the experimental peaks in the MassPeaks object to be recognized as isotopic pattern"/> - <param name="tolerance" type="float" label="Tolerance" value="0.00005" - help="Maximal relative deviation of a peak position (m/z) to be considered as identical: abs(((mass[i]+distance)-mass[i+1])/mass[i]) smaller than 'tolerance'. For 50ppm use 0.00005 or 50e-6" /> - <param name="distance" type="float" label="Distance" value="1.00235" help="Distance between two consecutive peaks in an isotopic pattern. 1.00235 is average distance for polypeptides."/> - <param name="size" type="integer" label="Size" value="3" help="Size (length) of isotopic pattern, longer patterns are prefered over shorter ones, min size is 2."/> + help="Minimal correlation between the peak pattern generated by the model and the experimental peaks in the MassPeaks object to be recognized as isotopic pattern."/> + <param name="tolerance" type="float" label="Tolerance" value="0.0001" + help="Maximal relative deviation of a peak position (m/z) to be considered as identical: abs(((mass[i]+distance)-mass[i+1])/mass[i]) smaller than 'tolerance'. For 100ppm use 0.0001" /> + <param name="distance" type="text" label="Distance" value="1.00235" help="Distance between two consecutive peaks in an isotopic pattern. 1.00235 is average distance for polypeptides. Multiple values can be used to find multiple charged pattern e.g. 1, 0.5 ,0.33"> + <sanitizer invalid_char=""> + <valid initial="string.digits"> + <add value="," /> + <add value=":" /> + <add value="." /> + </valid> + </sanitizer> + </param> + <param name="size" type="text" label="Size" value="3:10" help="Size (length) of isotopic pattern, longer patterns are prefered over shorter ones, min size is 2, a range can be used."> + <sanitizer invalid_char=""> + <valid initial="string.digits"> + <add value=":" /> + </valid> + </sanitizer> + </param> </when> <when value="Align"> @@ -614,7 +631,7 @@ <when value="Binning"> <param name="bin_tolerance" type="float" value="0.002" label="Tolerance" help="After the alignment the peak positions (mass) are very similar but not identical. The binning is needed to make similar peak mass values identical."/> - <param name="bin_method" display="radio" type="select" label="Bin creation rule" help="strict - creates bins never containing two or more peaks of the sampe sample. relaxed - allows multiple peaks of the same sample in one bin."> + <param name="bin_method" display="radio" type="select" label="Bin creation rule" help="strict - creates bins never containing two or more peaks of the same sample. relaxed - allows multiple peaks of the same sample in one bin."> <option value="strict" selected="True" >strict</option> <option value="relaxed" >relaxed</option> </param> @@ -673,6 +690,7 @@ <conditional name="methods_conditional"> <param name="method" value="monoisotopic_peaks"/> <param name="tolerance" value="0.0004"/> + <param name="size" value="3"/> </conditional> </repeat> <output name="plots" file="peakdetection2_QC.pdf" compare="sim_size"/> @@ -802,6 +820,13 @@ - Monoisotopic peaks: Keeps only the monoisotopic peaks + - Based on poisson model for isotopic patterns as decribed in (`Breen et al. <https://doi.org/10.1002/1522-2683(20000601)21:11%3C2243::AID-ELPS2243%3E3.0.CO;2-K>`_) + - Isotopic pattern can be characterized and recognized by + + - the similarity of the experimental pattern with the modelled pattern + - the distance between consecutive isotopic peaks. For polypeptides the average distance is 1.00235 (`Park et al. <https://pubs.acs.org/doi/abs/10.1021/ac800913b>`_). Multiply charged analytes have smaller distances between the peaks (e.g. z = 1 distance = ~1; z = 2: distance = ~0.5; z = 3: distance = ~0.3333) To search for differently charged isotopic pattern multiple distances can be applied - the order matters because the first distance that matches is reported (1, 0.5, 0.3333). + - the size (length) of the pattern, multiple values can be applied, longer patterns are prefered over shorter ones. + - Spectra alignment (warping): alignment for (re)calibration of m/z values.