SOLICITATION NOTICE
99 -- ANALYSIS SOFTWARE
- Notice Date
- 12/9/2003
- Notice Type
- Solicitation Notice
- Contracting Office
- Department of Health and Human Services, National Institutes of Health, National Institute of Allergy & Infectious Diseases/AMOB, 10401 Fernwood Drive, Suite 2NE70, MSC 4811, Bethesda, MD, 20817
- ZIP Code
- 20817
- Solicitation Number
- RML-RFQ-4010
- Response Due
- 12/22/2003
- Archive Date
- 1/6/2004
- Point of Contact
- Julienne Keiser, Purchasing Agent, Phone 406-363-9370, Fax 406-363-9376, - Lynda Kieres, Purchasing Agent, Phone 406-363-9210, Fax 406-363-9288,
- E-Mail Address
-
Jkeiser@niaid.nih.gov, lkieres@niaid.nih.gov
- Description
- This notice is a combined synopsis/solicitation for commercial items prepared in accordance with the format in Subpart 12.6, as supplemented with additional information included in this notice. This announcement constitutes the only solicitation, proposals are being requested and a written solicitation will not be issued. This solicitation is being issued as a request for quotations (RML-RFQ-4010). The solicitation documents and incorporated provisions and clauses are those in effect through Federal Acquisition Circular 2001-17, dated 10/20/03. This acquisition will be processed under FAR Part 12 ? Acquisition of Commercial Items, and is not a Small Business Set-Aside. The associated North American Industry Classification Systems (NAICS) Code for this procurement is 511210 and the size standard is $21.0. SCHEDULE: The Rocky Mountain Laboratories, Laboratory of Human Bacterial Pathogenesis (LHBP) proposes to procure a software program for the analysis of 2-D gel images derived from a variety of detection methods. It is mandatory that the software have the following capabilities: 1) Spot detection must have the potential to be carried out by an analysis wizard. The wizard must be capable of carrying out multiple detections under different parameters simultaneously. Spots on 2-D gels shall be detected using complex algorithms that can distinguish closely related spots. A cluster of spots difficult to differentiate must have the ability to be selected as an area of interest for further study. When manual or automatic changes occur, detection spots are automatically renumbered and the associated database is updated. When the user is examining the spots detected, the following features are required: zoom, contrast, brightness, and color. The user must be able to overlay multiple previously detected images to compare spots whether zoomed or native. The spot detection wizard must adjust to different gel running conditions, as well as, manual selection of spots. The spot detection aspect of this software must contain a manual or automatic feature to remove large noise particles from the final analysis. The ability to differentiate a true spot from a dust particle shall be critical. Software without this feature, but has an upgrade containing this feature, shall also be considered. 2) Spots that are detected must have the ability to be edited. The spot editing aspect to software must contain manual editing tools, as well as, spot drawing and erasing tools. There must exist the ability to manually add both single spots, or groups of spots from the original image or other images. From the spot detection function, each spot shall have a given contour representing the outermost limit to the spots resolution. This contour must be capable of being either increased or decreased manually. A contoured spot must be capable of splitting manually. All tools must have an undo function. The spot editing suite must contain a feature that monitors changes and applied filters to alert the user of any complications or clashes that might occur during analysis. Edited spots must be updated to the associated database. Gel images must have the ability to be manually warped to facilitate multiple image comparisons. After spots are edited, a spot editing merge function is necessary. 3) The background of each image must also have the ability to be edited based on a variety of standards. First, an adjustable mode of non-spot subtraction is necessary. Second, a lowest and average on boundary subtraction is required. Third, a manual mode for selection of a given area to be background, followed by subtraction. 4) Images that have had spots detected, undergone editing, and background subtraction must now be able to have those spots quantitated. Quantitation shall occur automatically after detection, and be updated as editing changes are made. The data shall be displayed as the quantity from a single spot on a given gel or multiple gels. From this comparison, multiple spot fields shall be displayed simultaneously highlighting differences. As a function of quantitation, spots should be annotated. It is also necessary to either show or hide the spot numbers to facilitate viewing. All of these functions must have the ability to be manipulated as tabs within the viewing window so only the tabs of interest are present, when you need them. 5) Individual images that have undergone the above analysis must be capable of being compared to each other. Primarily this function must have a highly accurate automated matching system. Manual matching methods are also required: overlay matching, dual window matching, and montage matching. Whether automated or manual, the matching parameters must be adjustable by the user. The user shall also have the ability to select a reference gel that can be used in multiple comparison experiments. After image comparison, the software must have the ability to add new spots to the reference gel, which shall instantaneously generate new measurements for the reference gel data and the matched gel data. Matching suite must have the ability to view match vectors. Individual images within matches shall be capable of being edited and warped. 6) The software shall calibrate both the MW and pI of a given 2-D gel. This generated ladder must have flexible placement, multiple curve fitting options, and user defined units. This ladder shall have the ability to be linked to the reference image so that all gels compared to the reference become automatically calibrated. This feature shall have the ability to normalize spots with a manually set normalization value. Normalization shall occur to single or multiple spots, group average or collective volume. 7) After matching an unlimited set of gels into groups, based on some threshold of similarity, those matched groups shall be capable of being averaged into representative images of groups of gel images. Gel images shall be added or removed from the group of gels that compose an average gel image while automatically updating the database and averaged image. The deviation of matched spots between images must be expressed as coefficient of variation, standard error of mean, and percentage of SEM. 8) The data must be visualized easily and under a variety of use selected conditions. Images shall have the potential to be viewed individually or as a montage. Simultaneous visualization of histograms, expression tables, difference maps, saturation maps, 3D image, profile, and zoomed windows are necessary. These images and tables should be linked dynamically so changes made to one area are reflected in the appropriate other areas. The number of matches for each reference spot, versus all of the gels displayed with a comparison, shall be made available in the form of a separate window. This must be organized into a user friendly and hardware friendly package. 9) The user shall have the ability to match image pixel values to known optical densities. The calibration curve generated from these values shall be viewed by the user. The software, as a means to self calibrate intensity between hardware shall include various curve-fitting algorithms. 10) These analyses shall generate considerable amounts of data, which must be navigated with ease. Viewing data as a tree structure shall be the best configuration. From this file navigation system, experiments shall be created by moving files. Created experiments must be capable of handling an unlimited number of images per experiment. Files shall be dynamically linked to open experiments so that changes or experiments in process are automatically updated. Batch processing of multiple files shall also be processed by simply selecting the desired files, and clicking the desired function. 11) The 2-D analysis software shall interact and query federated databases via the internet, and be integrated with an automated web page builder. 12) The images and data must be easily imported and exported through a windows based operating system. Images and data shall be copied to the windows clipboard as well as other formats. Tables shall be exported as .csv files or direct to Microsoft Excel. Images must have the ability to be exported as either .bmp or .jpeg files. Reports generated from the data analysis shall be exported as RTF or HTML formats. Entire experiments shall be exported in XML formats. Software shall export pick lists to variety spot pickers such as the Ettan, ProPic, GelPix, Proteineer sp, KBiosystems, and Proxcision. Protein spots that have been picked shall be flagged on the respective gel image to show their selection. 13) The 2-D analysis software shall support multiple image file formats such as .tif, .tiff, .gel, and .img. Both 8 and 16 bit grayscale images of any size shall be accepted. The software shall have an auto recovery feature in case of system failure. Original images shall remain unchanged and stored as separate files, while the edited, merged and averaged files compose a separate file. The user shall have the ability to create an analysis template with defined parameters that can be used to perform repeated identical analyses. The user shall perform all of the above analyses using images with inverted intensity. The following are required options: the ability to customize the display, printing options, change the order of analysis, and reorder the tables generated during an analysis. All features described should be available through, pull down menus, and a user definable tool bar. The software shall have a built-in help feature, as well as, tutorial images, cues and warning dialogs. The user shall be capable of incorporating shortcut keys to the main window. Images shall be annotated using free floating or spot anchored text. 14) The 2-D analysis software package shall include a statistical and data mining suite, to facilitate data query and analysis. The user shall be capable of querying any aspect of data in the database using natural language, and not proprietary database jargon. Queries shall be saved enabling repeat queries to be performed on new data sets. The user must be able to design expression queries with a graphical query design system, which will facilitate identifying design expression patterns within the database. This aspect of the software shall identify up-regulated, down-regulated, and unique spots for a given analysis. The data mining feature shall facilitate the creation of batch queries for batch processing, so experiments can be carried out without the user interaction. The software must also be capable of feeding the output of one query into the input of the next query, for drill-down analysis. The user must also be able to compare gels and sets of gels (without limit) for significant differences. The following statistical tests shall be required: paired t-test, variance ratio test, Kolmogorov-Smirnov test, Dunnett?s, and Kruskall-Wallis test. The data mining feature shall facilitate the analysis of large numbers of gel images or groups of spots, while rapidly identifying interesting parameters. The software shall perform principle component and correspondence analysis. When analyzing spot clusters, the software shall be capable of identifying groups of similar spots or gels, as well as, outliers, creating the k-medians of the hierarchical clustering. The software shall keep track of these analyses with automatic saving and organization by dataset. The software shall be licensed to enable it to be entirely or partially installed on an additional computer for editing. There shall be a security login required to view all data. FOB Point shall be Destination, Hamilton, MT. Delivery location is Rocky Mountain Laboratories, 903 S. 4th Street, Hamilton, MT. The following FAR provisions and clauses apply to this acquisition: As of October 1, 2003, All Vendor/Contractor (s) must be registered in the Central Contractor Registration System, in order to do business with the Federal Government. Lack of registration in the CCR will make an offeror ineligible for award. http://www.ccr.gov., 52.212-1 Instructions to Offerors?Commercial; Offerors must include with their offer a completed copy of the provisions at FAR 52.212-3 Offerors Representations and Certifications?Commercial Items. FAR 52.212-2 Evaluation?Commercial Items; FAR 52-212-4 Contract Terms and Conditions?Commercial Items; FAR 52-212-5 Contract Terms and Conditions Required to Implement Statues or Executive Orders?Commercial Items. This proposal will be evaluated based on technical information, price, and delivery. Offers may be mailed or faxed to the POC indicated above (Fax - 406-363-9376). Offers must be submitted not later than 4:30 PM (MDST), 12/22/03. Copies of the above-referenced clauses are available upon request, either by telephone or fax. All responsible sources may submit an offer that will be considered by this Agency.
- Place of Performance
- Address: Rocky Mountain Laboratories, 903 S. 4th Street, Hamilton, MT
- Zip Code: 59840
- Country: USA
- Zip Code: 59840
- Record
- SN00483931-W 20031211/031209211810 (fbodaily.com)
- Source
-
FedBizOpps.gov Link to This Notice
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