Welcome to the homologous series detection tool of Eawag Dübendorf. This online tool allows you to both detect and interactively explore signal patterns in liquid-chromatography (LC) mass spectrometry (MS) data that can be caused by the presence of homologous series compounds in a LC-MS measurement. Such signal patterns appear as signal series with almost constant MS mass differences and smooth changes in the LC retention time. Read the below instructions carefully to get the most of the tool and to avoid false or no results.
To use this tool, you must upload your LC-MS data as a .csv formatted file (left-handed sidebar). In such a file, each row represents a distinct (i.e., picked) LC-MS signal peak. In turn, the three columns in such a file represent the mass-to-charge ratio (m/z), the measured intensity and the retention time (RT) of each peak, respectively. Note that intensities are not involved in the detection procedure; dummy values are thus allowed; the column must however not be missing. Please compare with the provided example peaklist.
In addition, at least five parameters must be specified prior to running the algorithm:
The below depiction further illustrates these parameters for the homologous series of a surfactant (blue notation), containing six homologues and their LC-MS signal peaks (numbered in red). As illustrated, algorithm search windows to assort peaks into series are set relative to each preceding peak in a series, within the specified parameters.
Kindly note that calculations which consume more than two minutes of our server time will be aborted. It is likely that, e.g., too lose parameter restrictions were set in such a case, that the peak lists are too long or that the retention time of the uploaded .csv-file is given in minutes whereas the parameters minRT and maxRT are set in seconds.
enviHomolog web is a non-commercial software workflow distributed by Eawag Dübendorf. enviHomolog web is used at own risk. Neither the authors nor the distributor is liable to any hard- or software damages, data losses and false inferences caused by using enviHomolog web or any associated software parts. All warranties concerning the use of this software are disclaimed. Technical support for the program usage is not mandatory. Publications using enviHomolog web are obliged to cite enviHomolog web correctly. We try but do not warrant that the enviHomolog web files available are or will be free of infections or viruses, worms, Trojan horses or other code that manifest contaminating or destructive properties. The user is responsible for implementing sufficient procedures and checkpoints to satisfy the particular requirements for accuracy of data and data input and output.
Interaction with graph area through mousewheel, single click and double click:
Interaction with density graph area through single click, drag and double click:
You must upload your LC-MS data as a .csv formatted file. In such a file, each row represents a distinct (i.e., picked) LC-MS signal peak. In turn, the three columns in such a file represent the mass-to-charge ratio (m/z), the measured intensity and the retention time (RT) of each peak, respectively. Note that intensities are not involved in the detection procedure; dummy values are thus allowed; the column must however not be missing. Please compare with the below provided example peaklist.
envihomolog, non-target R package: firstname.lastname@example.org
envihomolog web app: email@example.com
2016 Eawag www.eawag.ch, Dübendorf: Martin Loos, Heinz Singer, Christian Gerber.
Special thanks for support to Chris, Felix, Pesche and Max from www.netstyle.ch.
The results are stored in csv files listed below:
Loos, M., Singer, H. (2017). Nontargeted homologue series extraction from hyphenated high resolution mass spectrometry data, Journal of Cheminformatics 9(1), 12.