WO2001067370A2 - Virtual gel profiling system - Google Patents

Abstract

A computerized system analyzing profiles of biological sample signals created on a gel. The system reads signals from the gel, refine and normalize the signals, quantify the intensity of the signals, organize such gel signal information with other information on the corresponding samples into profiles. The profiles created are stored in a suitable database. A pipeline links the database and the profiling system which allows efficient retrieval and update of the profile data. The computerized system is used to qualitatively and quantitatively characterize the biological states of input samples. Gel signals analyzed include signals of nucleic acids or proteins derived from a plurality of samples.

Description

Virtual Gel Profiling System

FIELD OF THE INVENTION

The present invention relates in general to a computerized system

analyzing profiles of biological sample signals created on a gel. More

specifically, it relates to a computerized system that is capable of reading,

refining, quantifying, comparing, organizing, storing and retrieving gel

signals of biological substances such as nucleic acids or proteins derived

from a plurality of samples of various origins, to qualitatively and

quantitatively characterize the biological states of such samples.

BACKGROUND OF THE INVENTION

The advancement of molecular biology techniques in the last few

decades has made it possible to elucidate a living organism's physiological

states in terms of the molecular composition of its tissues and cells. That

is, for example, a certain disease state can be characterized by a set of

regulatory and structural proteins expressed at certain levels and the

corresponding set of genes turned on, while the normal state is

characterized by a different set of proteins expressed at different levels

with the correspondingly different set of genes turned on. To take an

accurate "snap shot, " the existing protein, deoxyribonucleic acid (DNA)

and ribonucleic acid (RNA) species in the tissue or cell need to be

identified, and their amount need to be quantified. The separation of these macromolecules is achieved by molecular sieving in conjunction

with charge separation. Agarose and cross-linked polymer of acrylamide

are commonly used for this purpose. The evolution of such gel separation

systems results in today's high throughput and high resolution in the

5 identification of protein and nucleic acid fragments, as evidenced by the

performance of nucleic acid sequencing gels.

Such advancement, in the meantime, creates a pressing need to

develop comparable gel reading and analysis systems that can accurately

extract and analyze the signals produced on the gel, particularly in the

10 context of quantitative studies on biological states by taking "snap shots"

or "profiling" the molecular components in tissues or cells. To effectively

generate comprehensive profiles of various biological states based on a

gel system, overall high throughput, high resolution and high flexibility

must be achieved by a gel profiling system.

i s Numerous commercial programs are available today to process gel

images created by a gel scanner. However, these programs have a

number of defects that render them insufficient for many profiling studies.

Adjusting for the background is often done in an ad-hoc fashion, without

reliable standards. The distortion of lanes in a DNA or RNA gel can

0 severely reduce the accuracy in reading band signals. There is no

mechanism to safeguard against artifacts in one lane comparing to other

lanes. The existing problems like these make it difficult to establish accurate biological profiles based on the signals on the gel. In addition,

such programs when used in gene expression studies, for example, build

only limited profiles from data gathered beforehand. The disconnection

between data generation (e.g. gel electrophoresis), data processing(e.g.

gel scanning, gel reading), and data analysis (e.g . profile computing) on

the one hand and data organizing and storage (e.g . profile database) on

the other hand is a serious barrier to effective profiling studies.

Furthermore, the lack of intelligent, user-interactive monitoring and

controlling systems in such studies has led to non-coordinated, manual

work which threatens the consistency of the results and creates

additional difficulties in interpreting them.

SUMMARY OF THE INVENTION

To resolve the above problems, the present invention is directed to

a computerized system for processing gel signals and establishing

biological profiles for samples of different origins. In particular, the

present invention relates to a set of improved methods and processes for:

( 1 ) reading and refining gel signals; (2) constructing profiles directly from

the refined signals; (3) storing such profile information into a connected

database to allow for interactive and timely retrieval; and (4) monitoring

and controlling such profile analyses by accepting the user's input in real

time. Briefly summarized, the computerized gel profiling system

comprises a number of elements according to the present invention. A

gel separating system identifies and separates macromolecules, e.g., a

polyacrylamide gel electrophoresis (PAGE) system that separates

deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) fragments. A gel

scanner is provided to generate gel images. A computerized image

processing system processes these images through a series of steps to

extract and refine the signals. And, a selector facilitates the selection of

sample signals of interest. Finally, a profile compiler is provided to

construct profiles for any selected sample signals. A database connector

then provides support for information storage and retrieval.

In accordance with one aspect of the present invention, the

computerized image processing system begins with an image reader that

reads and identifies sample signals presented by the gel image, e.g., lanes

and bands on a PAGE gel, and that records the lane and band information,

preferably in a file. A trace generator then creates a trace for each lane

based upon this lane and band information, and this trace is in turn

aligned with all other traces. The background signals are then subtracted

from the aligned traces. Additionally, signals in each lane are normalized

to allow for cross-lane comparison. Finally, the intensity value of each

band is read and recorded according to the aligned, background-adjusted

and normalized traces. In the meantime, a gel simulator is used to construct virtual lane and band images from these aligned, background-

adjusted, and normalized traces.

In accordance with another aspect of the present invention, the

selector generates a set of selected signals in one of the two ways: (1 )

the user identifies sample signals directly; and (2) the selector highlights

the sample signals on the gel image satisfying a pre-configured criteria,

which is derived from the sample information accessible through the

database connector.

In accordance with yet another aspect of the present invention, the

profile compiler is capable of constructing biological profiles in one of the

two ways defined. First, it can create a corresponding profile by

organizing the intensity values for all detectable signals according to one

of the three formats supported by the gel profiling system. Alternatively,

it can create a corresponding profile by organizing the intensity values for

selected signals, e.g. bands selected by the user, according to one of the

three formats supported by the gel profiling system. The three supported

formats are ( 1 ) text file, (2) tabular form, and (3) an appropriate data

structure registered in a connected database.

In accordance with a fourth aspect of the present invention, the

database connector provides a channel through which the profile information is exported to a connected database, using a set of database

write methods to update relevant fields in the database. In parallel, the

sample information is retrieved through the database connector from a

connected database, using a set of database read methods for each

corresponding field in the database.

In accordance with a fifth aspect of the present invention, the

computerized gel profiling system further comprises a graphical interface

that permits the user to monitor and control the activities of the system.

This graphical interface includes three different windows or viewers. An

image viewer allows the user to view the original images. In this viewer,

the user can magnify the images as needed, and can circle or box a band

of interest to select it. A virtual gel viewer allows the user to view the

simulated gel images constructed based on the processed original images.

This viewer enables zooming in/out and scrolling up/down for optimal

viewing. And a trace viewer allows the user to view the traces of all the

lanes, which are drawn based on the processed original image. This

viewer similarly enables zooming and scrolling.

In accordance with a sixth aspect of the present invention, the

graphical interface further includes a profile editor. This editor allows the

user to adjust the boundaries of a band while computing its intensity

value to be included in a profile. In addition, the user can modify intensity values of a band within a profile, and the user can also delete a profile

altogether through use of this profile editor. Lastly, this editor takes the

user's input to establish a threshold value for determining differential

profiles, which are profiles containing differential intensity values It then

uses this threshold value to identify those profiles that are distinguishable

from others by the differential criteria.

The present invention, therefore, brings significant improvements in

biological profiling studies based on a gel system The gel profiling

system in accordance with the present invention achieves high

throughput, high resolution, high reliability and high flexibility.

Further features, objects, and advantages of the present invention

are apparent in the drawings and in the detailed description that follows.

The features of novelties that characterized this invention are pointed out

in the claims annexed to and forming a part of this specification.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a block diagram presenting a general overview of a Gel

Profiling System 1 20 designed in accordance with the present invention;

Fig. 2 is a block diagram of the elements and processes in the

Computerized Image Processing System 1 04 in Fig. 1 ; Fig. 3 is an illustration of band counts in each lane computed by

the Band Counter 206 in Fig . 2;

Fig . 4(a) , 4(b), and 4(c) are illustrations of traces in the Trace

Viewer 702 in Fig . 7: Fig . 4(a) illustrates raw traces, Fig . 4(b) illustrates

aligned traces, and Fig . 4(c) illustrates aligned, background-adjusted, and

normalized traces;

Fig . 5 is an illustration demonstrating a normalizing reference trace

in the Trace Viewer 702 in Fig . 7;

Fig . 6 is a screen shot of a display of the Virtual Gel Viewer 704 in

Fig. 7;

Fig . 7 is a block diagram presenting various components and their

interactions in the Graphical Interface 1 06 in Fig . 1 ;

Fig . 8 is a block diagram of the processes and their relationships

within the Trace Viewer 702 in Fig. 7;

Fig . 9 is a block diagram of the processes and their relationships

within the Virtual Gel Viewer 704 in Fig . 7;

Fig. 1 0 is an illustration of an original gel image presented by the

Image Viewer 706 in Fig. 7;

Fig . 1 1 is a block diagram of the components and operations within

the Profile Editor 708 in Fig. 7;

Fig . 1 2 is a screen shot of a display of the Profile Editor 708 in Fig .

7; Fig. 1 3 is a block diagram of elements and processes in the

Selector 1 08 in Fig. 1 ;

Fig. 1 4 is a block diagram of the elements and processes in the

Profile Compiler 1 10 in Fig. 1 ; and

Fig. 1 5 is a block diagram illustrating the two-way data flow within

the Database Connector 1 1 2 in Fig . 1 .

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Fig. 1 presents an overview of a Gel Profiling System 1 20 designed

in accordance with the teachings of the present invention, and

constituting a preferred embodiment of the invention. Referring to Fig. 1 ,

a Gel Separation System 1 00 separates and thus identifies biologically

active macromolecules from a set of samples of various origins. These

samples can be prepared in many different ways and for different

purposes. They can be normal or diseased tissue samples, body fluids

taken from patients at various progression stages of a particular disease,

cultured cells treated with various inhibitory or stimulatory agents as to a

specific cellular activity, or nucleic extracts of certain cell types

throughout the developmental stages of a test animal, etc. In the case of

DNA and RNA fragments, for example, the Gel Separation System 1 00

may be an electrophoresis system (not shown), according to one

preferred embodiment of this invention. After a set of samples is separated by the system 1 00, the gel is

then put through a Scanner 1 02, which generates a gel image. The

preferred format of the gel image is a compressed (with no loss of

information)TIFF file or a JPEG file. This image file then is sent to an

Image Processing System 1 04, which extracts and refines the molecular

signals contained in the gel through a series of processing steps.

The Image Processing System 1 04 is connected to a Selector 1 08,

which selects signals of interest for the construction of profiles. The

profiles are then built by a Profile Compiler 1 1 0, which accepts the input

form the Selector 108 and which outputs profile information to a

Database Connector 1 1 2. The Database Connector 1 1 2 serves as a

channel, or two-way communication pipeline, between the Gel Profiling

System 1 20 and a connected Database 1 30. The Database 1 30 manages

and stores relevant information of the biological samples run on the gel,

along with other background information that is needed to aid one in

interpreting the profile information generated by the system 1 20. The

Database 1 30 may be a typical genomics or proteomics database or

knowledge base system, in accordance with the needs and resources of a

particular profiling project. The communication between the Database

Connector 1 1 2 and the Database 1 30 is two-way because the Database

Connector 1 1 2 transfers the profile information from the Profile Compiler

1 10 to the Database 1 30, while in the meantime, other relevant information of each sample run on the gel are retrieved from the Database

1 30 and made available to the system 1 20.

The Image Processing System 1 04 also directly connects to and

interacts with the Profile Compiler 1 1 0, as is illustrated in Fig . 1 . The

system 1 04 computes the intensity values of the signals of interest, and

thereby provides the basis for profile construction. In addition, the

Graphical Interface 1 06 directly connects to the Image Processing System

1 04. The Graphical Interface 1 06 provides the user with a mechanism to

control and to monitor the activities of the Gel Profiling System 1 20, and

it provides a number of synchronized window viewers. The detail

working of the Graphical Interface 1 06 is discussed later. Aside from the

Image Processing System 1 04, the other modules such as the Selector

1 08, the Profile Compiler 1 1 0 and the Database Connector 1 1 2 are also

tied in with the Graphical Interface 1 06, to present the system state and

to accept the user's input, as demonstrated in Fig . 1 . An additional

connection between the Selector 108 and the Database Connector 1 1 2

allows the Selector 1 08 to incorporate relevant biological background

information on the samples in identifying sample signals to be included in

the selected set.

The Image Processing System 1 04 includes a series of modules and

processes as illustrated in Fig . 2. An Image Reader 200 reads signals from a gel image and records the resulting signal information, preferably in

a file. For nucleic acid samples, for example, the Image Reader 200

identifies the lanes and bands of DNA or RNA fragments, and creates data

files to store data representing the lanes and bands, respectively. The

5 band data includes pixel values, and the x, y coordinates of each band .

The lane data includes coordinates for a given number of points at a

predetermined interval along the length of each lane. In addition,

information defining the marker bands is similarly extracted and stored in

a designated file. This information, including the position of each marker

i o band and its size with respect to the number of bases, is then directed to

a Band Size Calibrator 204, which calculates the number of bases and

thus calibrates the size of each sample band according to the

corresponding marker bands. In the meantime, the information in the lane

data file and the band data file are sent to a Band Counter 206 and a

15 Trace Generator 202. The Band Counter 206 counts the number of

identifiable bands in each lane, as is shown in Fig . 3. The lanes 302 and

304 are marker lanes, and 300 is a size measure with respect to the

number of bases according to the marker band information . The lanes

31 0, 31 2, 31 4, 31 6, 31 8, 320, 322 and 324 are sample lanes with

0 bands identified through the Image Reader 200. The number of bands in

each sample lane is then counted . The Trace Generator 202 creates a

trace for each lane in the gel image. Each trace is a two-dimensional curve, where the X axis represents the gel shift and the Y axis represents

the intensity at each X position, as curve 402 illustrated in Fig. 4(a).

These raw traces in Fig. 4(a) are then aligned in an Aligning module 208

to correct for vertical distortions in the gel, which results in the aligned

traces, such as curves 41 2, 414 and 41 6 presented in Fig. 4(b). The

background noise is then subtracted from each of the aligned traces by

means of a Background Subtraction module 21 0 to produce aligned,

background-adjusted traces. To allow for cross-lane comparisons, a

reference trace is then built in a Normalization module 21 2 by taking the

average intensity values on the Y axis of all traces over the entire length

of each lane on the X axis. Fig. 5 demonstrates an example of a reference

trace, curve 502. Each aligned, background-adjusted trace is then

normalized against the reference trace, which creates aligned,

background-adjusted and normalized traces, such as curves 422, 424 and

426 shown in Fig. 4(c) . The information on these aligned, background-

adjusted and normalized traces is subsequently used by an Intensity

Computing module 21 6 to compute an intensity score 220 for each band

by taking the area underneath the peak corresponding to the band. In

parallel, a Gel Simulator 214 uses the aligned, background-adjusted and

normalized traces to create virtual lanes and bands which are displayed in

the Virtual Gel Viewer 704 in the Graphical Interface 1 06, as is shown in

Fig. 6. The Image Processing System 1 04 uses the following pairwise

alignment algorithm for aligning the traces. Each lane is aligned against a

reference lane. The first lane is usually used as the alignment reference

lane. The reference trace (the trace of the alignment reference lane) is

5 kept fixed during the alignment process. In aligning a trace, its X-

dimension is incrementally reshaped so that eventually the peaks

(representing band features) over Y-dimension match those on the

reference trace. During the alignment process, the Aligning module 208

keeps track of (1 ) the incrementally changed trace and (2) the mapping

io function that can be used to transform the X-coordinates from the original

trace to the new X-coordinates after the alignment. During phase I of the

alignment, a starting point is first selected near the center of the

reference trace. Then, through exhaustive shifting, enlarging, and/or

shrinking the X axis, the point on the trace being aligned that corresponds

i s to the starting point is identified. This corresponding point is defined by

taking the minimum of the cost computed from intensity differences and

first derivative value differences in a window around the alignment

starting point. During phase II of the alignment, the alignment is extended

in both directions by minimizing the alignment cost in a sliding window

o that is moved incrementally in two directions towards the start and the

end of the trace, respectively. The alignment algorithm is implemented in

Java in the preferred embodiment of this invention. In the Image Processing System 1 04, the Gel Simulator 21 4

creates virtual lanes and bands which are displayed in the Virtual Viewer

704 within the Graphical Interface 1 06. As mentioned above, the

Graphical Interface 1 06 consists of a number of windows with different

displays . Referring to Fig . 7, the whole interface system 1 06 represented

by the dashed block has four main components : ( 1 ) a Trace Viewer 702,

(2) a Virtual Gel Viewer 704, and (3) an Original Image Viewer 706,

which are interconnected with each other; and (4) a Profile Editor 708

which is connected to the Virtual Gel Viewer 706.

The first element, the Trace Viewer 702, displays traces derived

from a gel image, as shown in Figs 4(a) - 4(c) . Raw traces (402, 404

and 406), aligned traces (41 2, 41 4 and 41 6) , and aligned, background-

adjusted, normalized traces (422, 424 and 426) are illustratively shown in

Fig . 4(a) , 4(b), and 4(c), respectively. Referring to Fig . 8, the Trace

Viewer 702 has built-in scrolling and zooming capabilities, introduced by a

Scrolling module 800 and a Zooming module 802, respectively. In

addition, portions of the traces can be highlighted through a Highlighting

module 804 according to the user's selection, to enable subsequent

analysis. The shaded areas 432 and 434 in Fig . 4(c) demonstrate

highlighted parts of certain traces. The Trace Viewer 702 thus provides a

dynamic and responsive representation of traces. The second element, the Virtual Gel Viewer 704, displays simulated

bands and lanes which are straightened and calibrated through the series

of processes in the Image Processing System 1 04, as discussed above.

Referring to Fig. 9, the central unit of the Virtual Gel Viewer 704 is a

Painting module 900, which paints simulated lane and band images in this

window based on the aligned, background-adjusted and normalized

traces. Scrolling 902 and Zooming 904 are also enabled in this viewer.

Fig. 6 is a screen shot of the Virtual Gel Viewer 704, where two scrolling

bars (602 and 604) and buttons for zooming (606 and 608) are shown.

The fragment size measure 61 0 is constructed from the marker lane

information extracted by the Image Reader 200 within the Image

Processing System 104. Additional buttons on the bottom represent

ancillary functions of the viewer for, e.g., adjusting the brightness, saving

the file, etc.

The third element, the Image Viewer 706, displays the original gel

images generated by the Scanner 1 02. Fig. 1 0 presents an example of

such an original gel image. The lanes 1 002 and 1 01 2 are marker lanes,

and lanes 1 004, 1 006, 1 008 and 1 01 0 are sample lanes. A horizontal

scrolling bar 1 020 and a vertical scrolling bar 1 030 are included. The

user can click on a band of interest to select it. For example, clicking on

the band 1 050 will include that band in the subsequent profile analysis. To facilitate precise band selection, the user can use a magnifying

function of the Image Viewer 706 to enlarge the image.

The fourth element, the Profile Editor 708, allows the user to edit

the profiles. As shown in Fig. 1 1 , the user selects the band for which the

profile is to be edited, the band boundary position is then adjusted as

desired in a Boundary Adjustment module 1 1 00. The intensity value of

the band can be modified through a Intensity Modification module 1 1 02.

Finally, a profile can be deleted as needed in a Profile Deletion module

1 1 04. The edited profiles are then sent to a Comparative Filter 1 1 08

which identifies profiles with differential patterns. This is accomplished

by using the threshold number (control value) input by the user in a

Differential Threshold Input module 1 106. For example, given a set of

profiles containing the intensity values of five samples and one control, if

the user inputs " 1 0" as the threshold number, the Comparative Filter

1 1 08 will then go through each profile and identify the ones containing an

intensity value that is more than 1 0 units different than the control. Fig.

1 2 is a screen shot produced by the Profile Editor 708 according to a

preferred embodiment of this invention. The identifier of a selected band

is input into the text field 1 202 to initialize profile editing. The user enters

the threshold number into the text field 1 204. In the preferred embodiment of this invention, the displays

presented by the Image Viewer 706, the Trace Viewer 702 and the

Virtual Gel Viewer 704 are simultaneous and synchronized. As shown in

Fig. 7, two-way communications exist between all three viewers.

Highlighting a certain portion of the lanes in the Trace Viewer 702 will

automatically highlight the same portion of the lanes in the Virtual Gel

Viewer 704. Likewise, marking certain bands in the Image Viewer 706

will automatically mark the same bands in the Virtual Gel Viewer 704 as

being selected. The Image Processing System 104 directly interacts with

each of the three viewers in its series of image processing steps, from

extracting the raw data (Image Reader 200), creating the traces (Trace

Generator 202), aligning the traces (Aligning), adjusting the background

noise for all traces(Background Subtraction 210), and normalizing each

trace with respect to a reference trace (Normalization 21 2), to eventually

constructing the virtual images (Gel Simulator 21 4) . The profile analysis

is also tied in with all three viewers, which is reflected by the two-way

connections shown in Fig. 7 between the Profile Compiler 1 1 0 and each

of the viewers. The details of the Profile Compiler 1 1 0 will be described

below. The Profile Editor 708 in the Graphical Interface 1 06 interacts

with the Virtual Gel Viewer 704 directly, as mentioned above.

Additionally, it connects to the Database Connector 1 1 2 and the Selector 1 08 to enable the finalized profile information for the selected sample

bands to be recorded in the connected Database 1 30.

Referring to Fig. 1 3, the Selector 1 08 has two modes: ( 1 ) selection

based upon the user's input through the Graphical Interface 1 06, which is

done within a User Selection module 1 300; and (2) automatic selection

based upon a preconfigured criteria, which is done within a System

Selection module 1 302. The preconfigured criteria is established based

upon sample information 1 31 0, which is imported from the connected

Database 1 30 through the Database Connector 1 1 2. Selected sets of

bands 1 31 2 are then sent to the Profile Compiler 1 1 0 which creates the

profiles.

Referring to Fig . 1 4, the Profile Compiler 1 1 0 takes three pieces of

information: ( 1 ) selected sets of bands 1 31 0 from either the User

Selection 1 300 or the System Selection 1 302, (2) sample information

1 31 0 retrieved from the Database 1 30, and (3) band intensity score 220

calculated in the Image Processing System 1 04. Using this information,

the Profile Compiler 1 1 0 builds profiles within its central Build Profile

module 1 400. According to a preferred embodiment of this invention, a

typical profile 1 402 contains the relevant sample information such as

tissue type, disease progression state, patient age, gender, treatment

regime, etc., and the intensity scores for a set of selected samples that are being tested. This information is organized into one of three formats,

according to the user's preference: (1) textual format 1408, (2) table

format 1406; or (3) a data structure format 1404 that is acceptable to

the connected Database 130 through the Database Connector 112. Fig.

14 illustrates the data flow between the Profile Compiler 110, the

Database Connector 112, and the Database 130. Data originates from

the Database Connector 112, sample information 1310 is then derived

and constructed, the profiles are subsequently built in one of the above

three formats (1404, 1406 or 1408) within the Build Profile module

1400, which are eventually sent back to the Database Connector 112.

Referring to Fig.15, the Database Connector 112 includes

communication channels in two directions: an Importer 1500 and an

Exporter 1502. The sample information 1310 is retrieved from the

connected Database 130 through the Importer 1500, while the profile

information 1402 (in the various formats, 1404, 1406 or 1408) is sent to

the Database 130 through the Exporter 1502. The Importer 1500 uses

computer programs to read data from the Database 130, which includes a

set of database retrieving functions, one for each of the fields for which

data is needed. The Exporter 1502 uses computer programs to write data

into the Database 130, which includes database insert or update

functions for profiles in each of the three formats, textual 1408, tabular

1406 or data structure 1404. It also includes such functions for any other fields for which data needs to be updated as a result of analysis

runs by the Gel Profiling System 1 20.

In summary, the main characteristics of the gel profiling system in

accordance with the present invention are as follows.

( 1 ) The gel profiling system uses a gel separation system to

separate biologically active macromolecules. Such a separation system

includes, but not limited to a polyacrylamide gel electrophoresis (PAGE)

system or agarose gel system to separate nucleic acids molecules (DNA

and RNA), and 1 -dimensional or 2-dimensional protein denaturing sodium

dodecyl sulfate (SDS) gel system (e.g . SDS-PAGE) to separate protein

molecules and the like.

(2) The gel profiling system uses a scanner to scan the gels

produced by the separating system and generate image files, such as

TIFF, JPEG images.

(3) The gel profiling system uses a computerized image processing

system to extract, refine and analyze signals carried on each gel .

(4) In an image processing system for nucleic acid fragment

analysis, an image reader first identifies lanes and bands on the gel, including the marker lanes and marker bands, and record those data.

Then a band counter uses those data to count the number of bands in

each lane, and a band size calibrator calibrates the size of each band with

respect to the number of bases in the fragment according to the marker

5 bands information.

(5) In an image processing system for nucleic acid fragment

analysis, a trace generator builds a trace for each lanes on the gel based

on the lane and band data from the image reader. All traces are

subsequently aligned using a pairwise alignment algorithm which

io designates a reference lane and incrementally align each trace against the

trace of the reference lane. The aligned traces are then adjusted to

subtract the background noise. The resulting aligned, background-

adjusted traces are subjected to normalization according to a normalizing

reference trace. This is to allow for cross-lane comparison. The

i s normalizing reference trace is created by taking the average intensity

values on the Y axis of all traces in a gel image over the length of each

lane on the X axis.

(6) In an image processing system for nucleic acid fragment

analysis, the intensity score for each band is computed based on the

0 aligned, background-adjusted and normalized trace by taking the area

underneath the peak corresponding to the band . (7) In an image processing system for nucleic acid fragment

analysis, a gel simulator uses the data of the aligned, background-

adjusted and normalized traces to create virtual lanes and bands . The

intensity value of each peak (band) on the Y axis determines the intensity

5 of the simulated band . The virtual images are displayed in a virtual gel

viewer within the graphical interface in the gel profiling system .

(8) The gel profiling system uses a selector to establish a set of

selected sample signals for profiling analysis. The selector works in two

modes. In the first mode, it allows the user to identify sample signals (e.g .

i o bands) to be included in the set. In the second mode, it automatically

highlights the sample signals that satisfies a preconfigured criteria in the

system . The preconfigured criteria is established based on the sample

information retrieved from the connected database.

(9) The gel profiling system uses a profile compiler to create

i s profiles. For nucleic acid profiling analysis, a profile consists lane

numbers, band pixel coordinates, intensity scores and related information

on any qualifying attributes of samples corresponding to each band .

Three profile formats are used in the profile compiler: textual, tabular or a

data structure recognizable by the connected database. The profile

20 compiler works in two modes. In the first mode, the intensity scores for

all detectable signals in a gel image are compiled into one of the above three valid formats along with the sample information . In the second

mode, the intensity scores for the selected sample signals (as determined

by the selector) are compiled into one of the above three valid formats

along with the sample information.

5 ( 1 0) The gel profiling system uses a database connector to

communicate with a connected biological database or knowledge. This

database system stores background information on all samples run on the

gel, and information about known genes, proteins, and certain diseases as

in a typical genomics or proteomics database. The database connector

i o provides communications in two directions : an importer retrieves sample

information from the database, and an exporter sends the profile

information to the database. Each of the two modules consists of a

respective set of computer programs for accessing the database.

( 1 1 ) The gel profiling system has a graphical interface allowing the

i s user to monitor and control processes in the system . The graphical

interface has three windows, a trace viewer, a virtual gel viewer and an

original image viewer, which display in synch, the traces, the virtual lanes

and bands, and the original gel images, respectively. Additionally, a profile

editor provides a control panel for profile editing . The profile editor

0 directly interacts with each of the three viewers in its operation . ( 1 2) In the graphical interface, the trace viewer displays traces of

all lanes . Zooming and scrolling are supported in this viewer. The trace

viewer has a characteristic sliding window that highlights portions of

traces for cross-lane comparisons .

( 1 3) In the graphical interface, the virtual gel viewer displays virtual

lane and band images created by the gel simulator. Zooming and scrolling

are also supported in this viewer.

( 1 4) In the graphical interface, the image viewer displays the

original gel images . The user can select certain bands by properly

marking them in this viewer. Zooming and scrolling are supported in this

viewer.

Although the preferred embodiment of the present invention has

been described and illustrated in detail, it is to be understood that the

same is by way of illustration and example only, and is not to be taken by

way of limitation . The feature of novelty which characterize the present

invention as well as its scope are defined and limited only by the terms of

the claims appended to and forming a part of this specification.

Claims

WHAT IS CLAIMED IS:

1 . A computerized gel profiling system comprising :

a separating system capable of producing gels carrying macro-

molecules such as nucleic acids, proteins or polypeptides separated

according to their differential properties, such macromolecules being

derived from a set of biological samples;

a scanner capable of generating computerized image files from said

gels;

a computerized system for processing said images to properly

identify signals and calculate intensities of said signals;

a selector for selecting signals based on a user's input or a set of

preconfigured criteria for said set of biological samples;

a profile compiler for compiling into a desired format the numerical

intensity scores of selected signals identified by said selector, and a

plurality of attributes of said biology samples, thus generating a profile;

and

a database connector for exporting said profile into a biomedical

database or knowledge base and retrieving desired information on said set

of biological samples;

wherein said biomedical database or knowledge base optionally

captures clinical patient information, biological sample information or

genetic information at molecular level, which may include genomics sequence information or proteomics sequence, structure and function

information.

2. A profiling system as set forth in claim 1 wherein said profiling

system further comprises a graphical interface allowing the user to

monitor and control the activities of gel reading and profile constructing.

3. A profiling system as set forth in claim 1 wherein said signals

further comprise nucleic acid lane and band signals.

4. A profiling system as set forth in claim 3 wherein said

computerized system for processing further comprises:

an image reader to identify said lane signals and band signals and

record information generated on such signals in a file;

a trace generator to create traces for said lanes;

means for aligning said traces to build aligned traces;

means for background subtraction on said aligned traces to build

aligned, background-adjusted traces;

means for normalizing signals in each lane for cross-lane

comparison to build aligned, background-adjusted and normalized traces;

and a gel simulator for generating virtual lane and band images from

said aligned, background-adjusted and normalized traces .

5. The system in claim 4 wherein said aligning means further

comprises the steps of :

( 1 ) designating a reference lane;

(2) selecting a starting point on the reference lane;

(3) aligning a given trace against the reference trace by:

(a) determining an alignment cost by computing the intensity

differences and first derivative value differences in a window around the

alignment starting point,

(b) taking the minimum of said cost by exhaustive shifting,

enlarging or shrinking the X axis,

(c) determining the X-axis coordinate of the point on the

given trace that corresponds to the alignment starting point according to

said minimum cost,

(d) incrementally sliding said window in two directions

towards the start and the end of the given trace, and

(e) taking the minimum of the alignment cost in the sliding

window to extend alignment to both directions; and

(4) repeating step (3) until all traces are aligned .

6. The system in claim 4 wherein the means for normalization further

comprises:

determining a normalizing reference trace by taking the average

intensity values on the Y axis of all traces over the entire length of each

lane on the X axis; and

adjusting each trace according to said normalizing reference trace

by subtracting the Y-axis values on the reference trace from its Y axis

values over the entire length of its X axis.

7. A profiling system as set forth in claim 4 wherein said

computerized system for processing further comprises a counter for

counting the number of bands in each lane.

8. A profiling system as set forth in claim 4 wherein said

computerized system for processing further comprises a calibrator for

calibrating base pair size estimates based on a marker lane.

9. A profiling system as set forth in claim 1 wherein said selector

further comprises:

means for the user to identify signals desired to be included in a

selected set; wherein said criteria may be derived from the information of said

biological samples stored in a database.

1 0 A profiling system as set forth in claim 1 wherein said profile

compiler further comprises:

means to organize the intensity scores for all detectable signals into

a desired format and create a corresponding profile;

wherein said desired format can be of a tabular form, in a text file,

or in any data structure that is recognizable by said connected database

1 1 A profiling system as set forth in claim 1 0 wherein said profile

includes lane numbers, band pixel coordinates, intensity scores and other

optional information on a corresponding set of biological samples.

1 2. A profiling system as set forth in claim 1 wherein said selector

further comprises:

means for automatically highlighting signals satisfying a criteria

preconfigured in the profiling system;

wherein said criteria may be derived from the information of said

biological samples stored in a database.

1 3. A profiling system as set forth in claim 1 wherein said profile

compiler further comprises- means to organize the intensity scores for all selected signals as

determined by the selector into a desired format and create a

corresponding profile;

wherein said desired format can be of a tabular form, in a text file,

or in any data structure that is recognizable by said connected database.

1 4. A profiling system as set forth in claim 1 3 wherein said profile

includes lane numbers, band pixel coordinates, intensity scores and other

optional information on a corresponding set of biological samples .

1 5. A profiling system as set forth in claim 1 wherein said graphical

interface further comprises:

a trace viewer allowing the user to zoom in/out and scroll up/down

when viewing the traces, and highlight areas of interest along the traces;

a virtual gel viewer allowing the user to zoom in/out and scroll

up/down when viewing the simulated gel images; and

an image viewer allowing the user to view the original images,

magnify said original images for precise band selection, and mark selected

bands.

1 6. The system in claim 1 5 wherein said trace viewer further comprises

an adjustable slider for comparative numerical analysis of intensity scores

cross various lanes; and

the selected portion of the traces is automatically highlighted to

facilitate such comparison.

1 7. The system in claim 1 5 wherein said trace viewer further comprises

a display for computed differences with respect to a reference trace.

1 8. A profiling system as set forth in claim 1 5 further comprises a

profile editor comprising:

means for adjusting boundaries for a band included in a profile;

means for modifying intensity scores of said band in said profile;

means for deleting said profile; and

means for identifying profiles with differential values based on a

threshold number input by the user.

1 9. A profiling system as set forth in claim 1 5 which further comprises

means for simultaneous and synchronized displays in the image viewer

window, the virtual gel viewer window and the trace viewer window.

20. A profiling system as set forth in claim 1 , wherein said database

connector comprises: means for exporting said profile to a connected database, said

means comprising a set of database write methods for each of the fields

to be updated; and

means for importing optional information on the set of biological

samples, said means comprising a set of database retrieving methods for

each of the related attributes.