# US 2014/0156612 A1 · Preparing lc/ms data for cloud and/or parallel image computing

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- Number: US 2014/0156612 A1
- Document ID: US20140156612A1
- Status: Published application
- Kind: A1
- Application number: 13/889,199
- Filed: 2013-05-07
- Published: 2014-06-05
- Earliest claimed: 2012-05-07
- Assignees: Infoclinika, Inc.
- Applicants: Infoclinika, Inc.
- Inventors: Andrey Yur'yevich Bondarenko
- Web page: https://patentgrep.com/patent/US20140156612A1

## CPC

- G06F 16/56: having vectorial format
- G06F 16/1744: {using compression, e.g. sparse files}
- H01J 49/0036: {Step by step routines describing the handling of the data generated during a measurement}
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- H01J: ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS (spark-gaps H01T; electric arc lamps H05B31/00; particle accelerators H05H)

## Abstract

Functionality is described for data management and querying LC/MS spectrometry data, therefore making it easier to store, retrieve, transfer, and process the mass spectrometry data. The functionality transforms a plurality of raw LC/MS files obtained from a biological experiment into a set of LC/MS images on a common M/Z and RT grid compatible for image processing (e.g., time alignment, peak detection and quantification, differential analysis, etc.). The functionality then spits large LC/MS images into smaller chunks, therefore making easier parallel querying and processing using cloud or high performance computing systems.

## Claims

### Claim 1

A method for managing experimental data, comprising:
unifying raw LC/MS data generated from different formats to create LC/MS images;
chunking the LC/MS images to facilitate parallel processing; and
compressing chunked LC/MS images to facilitate storage.

### Claim 2 (depends on 1)

The method of claim 1, wherein unifying includes calculating a global RT grid or both a global RT grid and a global M/Z grid.

### Claim 3 (depends on 2)

The method of claim 2, wherein calculating a global M/Z grid includes searching for mass scans within selected raw LC/MS files that have the highest number of M/Z and intensity value pairs, and calculating a delta M/Z value by calculating a difference between next and previous adjacent M/Z measurements with non-zero intensities.

### Claim 4 (depends on 3)

The method of claim 3, wherein calculating a global M/Z grid includes fitting a polynomial regression function for the M/Z, delta M/Z pairs, and estimating coefficients of the polynomial regression function.

### Claim 5 (depends on 4)

The method of claim 4, wherein elements of global M/Z grid vector are prepared to be calculated recursively using a polynomial regression model.

### Claim 6 (depends on 2)

The method of claim 2, wherein calculating a global RT grid includes determining retention grid step size by calculating mean or median from instrument sampling rate, and wherein elements of a global RT grid vector are calculated using a sum of two summands, one summand being a minimum retention time value from a specified RT range and the other summand being a product of a retention time step size and an index into the global RT grid vector.

### Claim 7 (depends on 2)

The method of claim 2, wherein unifying further includes interpolating mass scans into the global M/Z grid forming the LC/MS images with a two-dimensional intensity matrix.

### Claim 8 (depends on 7)

The method of claim 7, wherein interpolating includes transforming raw intensity values from the mass scans using linear interpolation into a new intensity vector corresponding to the global M/Z grid.

### Claim 9 (depends on 8)

The method of claim 8, wherein transforming includes reading mass scans sequentially from raw LC/MS files and streaming interpolated intensity vectors to a temporary file.

### Claim 10 (depends on 2)

The method of claim 2, wherein unifying further includes iterating through rows of LC/MS images and interpolating them into a calculated RT grid using linear interpolation.

### Claim 11

A system, comprising:
format-unifying hardware suitable for unifying raw LC/MS data generated from different formats to create LC/MS images, the unifying hardware being further suitable for calculating a global RT grid and a global M/Z grid;
chunking hardware capable of chunking the LC/MS images to facilitate parallel processing; and
compression hardware having the capacity to compress chunked LC/MS images to facilitate storage.

### Claim 12

A computer-readable medium, which is tangible, having stored thereon computer-executable instructions for implementing a method for managing experimental data, comprising:
unifying raw LC/MS data generated from different formats to create LC/MS images;
chunking the LC/MS images to facilitate parallel processing; and
compressing chunked LC/MS images to facilitate storage.

### Claim 13 (depends on 12)

The method of claim 12, wherein unifying includes calculating a global RT grid or a global M/Z grid or both.

### Claim 14 (depends on 13)

The method of claim 13, wherein calculating a global M/Z grid includes searching for mass scans within selected raw LC/MS files that have the highest number of M/Z and intensity value pairs, and calculating a delta M/Z value by calculating a difference between next and previous adjacent M/Z measurements with non-zero intensities.

### Claim 15 (depends on 14)

The method of claim 14, wherein calculating a global M/Z grid includes fitting a polynomial regression function for the M/Z, delta M/Z pairs, and estimating coefficients of the polynomial regression function.

### Claim 16 (depends on 15)

The method of claim 15, wherein elements of global M/Z grid vector are prepared to be calculated recursively using a polynomial regression model.

### Claim 17 (depends on 13)

The method of claim 13, wherein calculating a global RT grid includes determining retention grid step size by calculating mean or median from instrument sampling rate, and wherein elements of a global RT grid vector are calculated using a sum of two summands, one summand being a minimum retention time value from a specified RT range and the other summand being a product of a retention time step size and an index into the global RT grid vector.

### Claim 18 (depends on 13)

The method of claim 13, wherein unifying further includes interpolating mass scans into the global M/Z grid forming the LC/MS images with a two-dimensional intensity matrix.

### Claim 19 (depends on 18)

The method of claim 18, wherein interpolating includes transforming raw intensity values from the mass scans using linear interpolation into a new intensity vector corresponding to the global M/Z grid.

### Claim 20 (depends on 19)

The method of claim 19, wherein transforming includes reading mass scans sequentially from raw LC/MS files and streaming interpolated intensity vectors to a temporary file.

### Claim 21 (depends on 13)

The method of claim 13, wherein unifying further includes iterating through rows of LC/MS images and interpolating them into a calculated RT grid using linear interpolation.