• Upcoming Opus 23 In-Person Seminar

    Because of media obligations associated with the re-release of Dr. D’Adamo’s first book, there is a schedule conflict with the January 7-8 seminar date. The seminar will be rescheduled for a later date.  Please check back for further news and details.

    If you are even thinking about doing this sign up.Opus 23 has been a game changer for my patients who have had ‘mysterious’ problems that, after seeing many integrative practitioners, still were not better until Opus 23 ‘sang’ the perfect healing words. –Robert Lang, MD

    Dr. D’Adamo periodically does these for those practitioners who prefer a more hands-on approach to learning Opus 23 (vs. the wonderful 5 hour webinars done by Drs. Greenfield).

    Dr. D’Adamo writes:

    ‘Attendees work in 2-3 person pods under the direct supervision of one of my COE wunderkids. You also get a healthy dose of me lecturing on stuff: In this case a heavy focus on the new ‘Utopia’ module that allows you to mash up client genomic and microbiome data. Attendance is purposely kept to 10-12, to insure an intimate learning environment. You get lunch and I typically spring for dinner at a nice restaurant.’

    If you are interested in this type of hands-on training, contact Carol Agostino at carol@dadamo.com (203 761-0042) for full details.

  • Utopia: Spectrum, visual community organization

    SPECTRUM: Visual community organization

    Utopia logo

    SPECTRUM provides a visual representation of the taxonomic data at both the genus and phylum levels. The app demonstrates the weight, influence and diversity of your client’s microbiome in two helpful display formats, each of which are clickable for a deeper look and easy report curation.

    Navigating  SPECTRUM

    Spectrum logo

    From the Utopia drop down menu, hover over ‘analytics’ until a second list appears, then select SPECTRUM.  Phyla and genus are displayed in pie chart format, which is accompanied by the spectrum profiler found below.

    The pie charts follow the color-coding conventions found in OPUS23 indicating beneficial, neutral as well as pathogenic organisms. Click on any desired section to open up its information pop—up window for detailed information including taxonomy, an overview of known disease or health benefit associations, descendants and metabolomics. Click ‘add/ curate’ to include it in your client’s report.

    Spectrum pie charts

    The spectrum profiler demonstrates the trends in your client’s biome diversity in a graphical format. Clicking on any of the category headings will open a pop-up window listing the organisms found in your client’s sample. Each genus listed is also clickable, opening a pop-up window for detailed information, including taxonomy, an overview of known disease or health benefit associations, descendants and metabolomics. Click ‘add/ curate’ to include it in your client’s report.

    Screenshot of Spectrum Profiler

    Metabolomics is a powerful addition to the spectrum profiler that provides a comprehensive list of metabolites associated with GI biome species. A list of all metabolites active in your client is included. Click on an individual metabolite for detailed information, including genera that are enhanced, inhibited, and those which generate the metabolite as an end product. Click on the Metabolomics link to open a pop-up with all active and inactive genera.

  • Utopia: Loam, a fertile soil

    Announcing the launch of Utopia, the suite of apps within Opus 23 that analyzes and reports on sequential data from uBiome tests. uBiome is the world’s first sequencing-based clinical microbiome screening test, giving the user insight into the bacterial population of multiple body areas. Utopia recognizes all bacteria found by uBiome, but is specifically interested in the gut bacteria and its interaction with the client’s own genomic DNA. Utopia is free for existing clients: Once you have uploaded 23andMe raw data for your client, you can add as many uBiome tests as you want for that client without additional charge. Utopia will then give you access to multiple apps to analyze the data and reference it to the client’s genomic data where appropriate.

    Utopia logo

    LOAM: Adaptable taxon data

    LOAM is a highly flexible search and sort tool that allows you to easily navigate through your client’s Ubiome results by taxon. LOAM allows you to filter taxonomic data based upon several useful parameters as well as sort the filtered results. It is similar to the ARGONAUT app in Opus 23.


    Navigating LOAM

    From the Utopia drop down menu, hover over ‘analytics’ until a second list appears, then select LOAM. You will then be presented with the default table which shows ‘everything’ and is sorted by ‘repute’ or ‘interpretation’.

    At the bottom of the window is a jump screen that allows you to move from one screen to the next. You can control how many rows to display be selecting an option from the ‘Show’ pull down menu. The default is 15.

    Loam Screenshot

    Filtering and sorting results

    LOAM allows you to parse the taxon data based upon desired treatment goals. Taxons are sortable by benefit as well as pathogenic potential.

    The LOAM table displays the following data by column:

    • Taxon name
    • Repute, displaying beneficial !, neutral ! and pathogenic ! 
    • Rank
    • Client-specific % population
    • Average % (if available)
    • Standard deviation (if available)
    • Interpretation (displayed up to +6 times the standard deviation, populations found in a greater abundance are indicated by )
    • Normal variance
    • Order magnitude

    Click on any desired taxon to open up its information pop—up window for detailed information including taxonomy, an overview of known disease or health benefit associations, interactions and metabolomics. Click ‘add/ curate’ to include it in your clients report. The Curated column will then show a green checkmark against all curated taxon after refreshing the page. 

    LOAM columns are sortable. Click on any column title to sort by that column. Click that column again to reverse the sort order.

  • Lewis negative and secretor status

    Fucus vesiculosis
    Fucus vesiculosis, by Emőke Dénes CC BY-SA 2.5 via Wikimedia Commons

    Many people are aware of the concept that their blood group influences their interaction with the environment: intestinal secretions of blood group antigens affect a person’s interaction with foods through being a marker of self recognised by the immune system. Similar to the way that a transfusion of blood from the wrong blood group causes a powerful IgM immune reaction, food lectins can also lead to a reaction (albeit less immunologically strong) by stimulating release of IL4 and IL13 from basophils, potentially leading to type I allergy. [1] Depending on diet, this could result from lectins incompatible with specific blood group glycoproteins, which would create an immune response individual to the person’s blood group: lectins from some foods are used to preferentially agglutinate specific glycoprotein antigens when testing saliva. [2]

    Secretor status is under genetic control: 15-20% of people of Western European descent are unable to secrete their blood group antigens due to a homozygous mutation on the fucosyltransferase 2 (FUT2) gene at the rs601338 SNP. The FUT2 (secretor) gene is expressed predominantly in secretory tissues, giving rise to glycoprotein products in mucin secretions. [3] This mutation is rare in Chinese and Japanese populations, and instead the more common homozygous FUT2 rs1047781 missense mutation is responsible for dramatically decreased expression of ABH antigens (partial ABH secretors). [4]

    Non-secretor status is associated with immunity to norovirus, [5] higher vitamin B12 levels, [PMID: 18776911] and secretor status also affects phagocytic activity of the leukocytes in a manner that places non-secretors at an advantage from increased activity, [6] in addition to the influence of the ABO blood group on phagocytosis. [7] Many disease risks are also associated with non-secretor status: antigen barrier function favours secretors, the free ABH antigen on the mucosal barriers of ABH secretors acts as an effective anti-adhesive mechanism against ABH specific bacterial fimbriae lectins. [8] Non-secretors may have an increased risk for Crohn’s disease, [9] type 1 diabetes, [10] and vaginal candidiasis. [11]

    One way to determine whether a person is a secretor of their blood group is to test their saliva for their ABO blood group antigens. This method is not commonly available, as a supply of red blood cells is needed for testing the saliva. Another way to find secretor status is to test for Lewis blood group. The Lewis a (Le a) antigen is normally secreted into the blood and then adsorbed onto red blood cells, [12] where it can be agglutinated with anti-Lewis a reagent. Fucose is a common sugar, found in seaweeds such as fucus vesiculosus (bladderwrack), and also forms the terminal sugar of the H antigen in people with blood group O. Fucosyltransferase enzymes can attach the fucose molecule onto another sugar or glycoprotein through fucosylation, such as that of the blood group A or B antigen or Lewis antigens. If there is a working copy of the FUT2 SNP the Lewis a antigen will be catalysed into Lewis b by the FUT2 enzyme. Consequently those with a functional FUT2 enzyme don’t have any Lewis a antigen on their erythrocytes, but they will have the Lewis b antigen, and therefore a finding of Lewis b on erythrocytes indicates an ABH secretor. The problem arises with the small number of people who don’t have the Lewis blood group antigens on their blood cells. This is similar to the rare ‘Bombay’ blood group, which results in a loss of production of ABH antigens on erythrocytes (from loss of FUT1 function): the fucosyltransferase 1 (FUT1) gene is expressed predominantly in erythroid tissues, giving rise to FUT1 (H enzyme) giving rise to products found on erythrocytes. About 5% of the European population (and more in some other populations) lack a functional fucosyltransferase 3 (FUT3) enzyme. These FUT3 negative people are unable to make any Lewis antigens. They may be either ABH secretors or non-secretors, but the Lewis test cannot be used to determine secretor status due to the lack of any Lewis antigen for agglutination.

    People with no Lewis antigens are classed as Lewis negative, however this phenotype might not always be only caused by FUT3 mutation. Erythrocyte membranes have been found to lose their Lewis antigens during pregnancy and during diseases such as cancer: individuals have been identified who change from Lewis positive to Lewis negative on erythrocytes, although they persistently express Lewis enzyme activity in saliva. The reason for this change has been attributed to an increased level of circulating lipoproteins during the burden of disease or pregnancy, which alter the balance between production of Lewis glycolipids, transport in lipoproteins, and incorporation into erythrocyte membranes. Fucosyltransferase activity in saliva is variable, being lower in FUT3 heterozygotes than it is in homozygous wild-type individuals, and those with mutation in the FUT2 gene (non-secretors) do not fucosylate the Lewis a structure to H and the Lewis b, in competition with a sialyltransferase. [13]

    There are also epigenetic influences on FUT3 expression. Certain cancer markers are not found in patients with FUT3 mutation: it is not thought useful to measure the CA19-9 titer of Lewis negative cancer patients. A study found that Lewis-negative individuals consisting of a homozygous negative FUT3 genotype had completely negative CA19-9 values, irrespective of the FUT2 secretor genotype. [14] Very few Lewis-positive patients exhibit positive DU-PAN-2 values. [15]

    Although Lewis negative status may be protective against Rotavirus, [16] it is also linked with markers of inflammation: WBC, hs-CRP and ESR were significantly elevated, and rheological parameters (RBC aggregation, plasma viscosity) were found to be abnormal in Lewis negative subjects. [17] Lewis negative men were found to have a higher systolic blood pressure (6 mm Hg), higher values for BMI (8%) and total body fat mass than Lewis positive individuals. [18] Lewis negative status is a genetic risk factor for ischemic heart disease (IHD), particularly in men, and is associated with high triglycerides. Lewis negative status also confers protection from IHD with moderate alcohol intake: Studies found that the risk of IHD was negatively correlated with alcohol consumption. [19] The authors suggest that alcohol consumption may modify insulin resistance in Le(a-b-) men. [20] Asthma is related to both non-secretor and Lewis negative phenotypes, and low lung function values have been observed in Lewis negative non-secretors. Alcohol intake is also protective against asthma in Lewis negative individuals, [21] but Lewis negative individuals are more likely to suffer from alcoholism. [22] Lewis negative phenotype confers a three times greater risk of diabetes, [23] and an increased risk for Sjögren’s syndrome. [24] The intestinal microbiota of individuals with Lewis negative blood groups were reported to contain a less rich and diverse range of bacteria than those with Lewis a phenotype. [25] Urinary tract infections in women are more common amongst non-secretors, and most common in Lewis negative individuals. [26] Polymorphisms in FUT3 and its intestinal expression might be associated with pathogenesis of ulcerative colitis. [27]

    Despite the differences in disease risk between ABH secretors and non-secretors, clinical experience suggests that Lewis negative individuals appear to have unique interactions with certain disease states. [8] Opus 23 Pro [28] provides algorithms in the Lumen app to find secretor status from the FUT2 rs601338 SNP, and to estimate Lewis status from 23andMe raw data based on the SNPs available for FUT3 (all except one of the most common FUT3 SNPs resulting in Lewis negative status are typically reported by 23andMe). This can give the practitioner another level of insight into the likely glycosylation levels, immune status, inflammatory and health risks of the patient, as well as the likelihood of relevance of testing for tumour markers.

    1. Haas H, Falcone FH, Schramm G, et.al. Dietary lectins can induce in vitro release of IL-4 and IL-13 from human basophils. Eur J Immunol. 1999 Mar;29(3):918-27. PMID: 10092096.
    2. Albertolle ME, Hassis ME, Ng CJ, et. al. Mass spectrometry-based analyses showing the effects of secretor and blood group status on salivary N-glycosylation. Clin Proteomics. 2015 Dec 30;12:29. doi: 10.1186/s12014-015-9100-y. PMID: 26719750; PMCID: PMC4696288.
    3. Prakobphol A, Leffler H, Fisher SJ. The high-molecular-weight human mucin is the primary salivary carrier of ABH, Le(a), and Le(b) blood group antigens. Crit Rev Oral Biol Med. 1993;4(3-4):325-33. PMID: 7690601.
    4. Hu D, Zhang D, Zheng S, et. al. Association of Ulcerative Colitis with FUT2 and FUT3 Polymorphisms in Patients from Southeast China. PLoS One. 2016 Jan 14;11(1):e0146557. doi: 10.1371/journal.pone.0146557. PMID: 26766790; PMCID: PMC4713070.
    5. Lindesmith L, Moe C, Marionneau S, et. al. Human susceptibility and resistance to Norwalk virus infection. Nat Med. 2003 May;9(5):548-53. PMID: 12692541.
    6. Tandon OP, Bhatia S, Tripathi RL, Sharma KN. Phagocytic response of leucocytes in secretors and non-secretors of ABH (O) blood group substances. Indian J Physiol Pharmacol. 1979 Oct-Dec;23(4):321-4. PMID: 528036.
    7. Tandon OP. Leucocyte phagocytic response in relation to abo blood groups. Indian J Physiol Pharmacol. 1977 Jul-Sep;21(3):191-4. PMID: 612601.
    8. D’Adamo PJ, Kelly GS. Metabolic and immunologic consequences of ABH secretor and Lewis subtype status. Altern Med Rev. 2001 Aug;6(4):390-405. Review. PMID: 11578255.
    9. McGovern DP, Jones MR, Taylor KD, et. al. International IBD Genetics Consortium. Fucosyltransferase 2 (FUT2) non-secretor status is associated with Crohn’s disease. Hum Mol Genet. 2010 Sep 1;19(17):3468-76. doi: 10.1093/hmg/ddq248. PMID: 20570966; PMCID: PMC2916706.
    10. Smyth DJ, Cooper JD, Howson JM, et. al. FUT2 nonsecretor status links type 1 diabetes susceptibility and resistance to infection. Diabetes. 2011 Nov;60(11):3081-4. doi: 10.2337/db11-0638. PMID: 22025780; PMCID: PMC3198057.
    11. Hurd EA, Domino SE. Increased susceptibility of secretor factor gene Fut2-null mice to experimental vaginal candidiasis. Infect Immun. 2004 Jul;72(7):4279-81. PMID: 15213174; PMCID: PMC427463.
    12. Henry S, Oriol R, Samuelsson B. Lewis histo-blood group system and associated secretory phenotypes. Vox Sang. 1995;69(3):166-82. Review. PMID: 8578728.
    13. Orntoft TF, Vestergaard EM, Holmes E, et. al. Influence of Lewis alpha1-3/4-L-fucosyltransferase (FUT3) gene mutations on enzyme activity, erythrocyte phenotyping, and circulating tumor marker sialyl-Lewis a levels. J Biol Chem. 1996 Dec 13;271(50):32260-8. PMID: 8943285.
    14. Narimatsu H, Iwasaki H, Nakayama F, et. al. Lewis and secretor gene dosages affect CA19-9 and DU-PAN-2 serum levels in normal individuals and colorectal cancer patients. Cancer Res. 1998 Feb 1;58(3):512-8. PMID: 9458099.
    15. Vestergaard EM, Hein HO, Meyer H, et.al. Reference values and biological variation for tumor marker CA 19-9 in serum for different Lewis and secretor genotypes and evaluation of secretor and Lewis genotyping in a Caucasian population. Clin Chem. 1999 Jan;45(1):54-61. PMID: 9895338.
    16. Nordgren J, Sharma S, Bucardo F, et. al. Both Lewis and secretor status mediate susceptibility to rotavirus infections in a rotavirus genotype-dependent manner. Clin Infect Dis. 2014 Dec 1;59(11):1567-73. doi: 10.1093/cid/ciu633. PMID: 25097083; PMCID: PMC4650770.
    17. Alexy T, Pais E, Wenby RB, et al. Abnormal blood rheology and chronic low grade inflammation: possible risk factors for accelerated atherosclerosis and coronary artery disease in Lewis negative subjects. Atherosclerosis. 2015;239(1):248-251. doi:10.1016/j.atherosclerosis.2015.01.015.PMID: 25626016; PMCID: PMC4331217
    18. Clausen JO, Hein HO, Suadicani P, et. al. Lewis phenotypes and the insulin resistance syndrome in young healthy white men and women. Am J Hypertens. 1995 Nov;8(11):1060-6. PMID: 8554728.
    19. Hein HO, Sørensen H, Suadicani P, Gyntelberg F. Alcohol intake, Lewis phenotypes and risk of ischemic heart disease. The Copenhagen Male Study. Ugeskr Laeger. 1994 Feb 28;156(9):1297-302. PMID: 8009753.
    20. Hein HO, Sørensen H, Suadicani P, Gyntelberg F. Alcohol consumption, Lewis phenotypes, and risk of ischaemic heart disease. Lancet. 1993 Feb 13;341(8842):392-6. PMID: 8094167.
    21. Kauffmann F, Frette C, Pham QT, Nafissi S, Bertrand JP, Oriol R. Associations of blood group-related antigens to FEV1, wheezing, and asthma. Am J Respir Crit Care Med. 1996 Jan;153(1):76-82. PMID: 8542166.
    22. Cruz-Coke R. Genetics and alcoholism. Neurobehav Toxicol Teratol. 1983 Mar-Apr;5(2):179-80. PMID: 6346123.
    23. Melis C, Mercier P, Vague P, Vialettes B. Lewis antigen and diabetes. Rev Fr Transfus Immunohematol. 1978 Sep;21(4):965-71. PMID: 734307.
    24. Manthorpe R, Staub Nielsen L, Hagen Petersen S, Prause JU. Lewis blood type frequency in patients with primary Sjögren’s syndrome. A prospective study including analyses for A1A2BO, Secretor, MNSs, P, Duffy, Kell, Lutheran and rhesus blood groups. Scand J Rheumatol. 1985;14(2):159-62. PMID: 4001887
    25. Wacklin P, Tuimala J, Nikkilä J. Faecal microbiota composition in adults is associated with the FUT2 gene determining the secretor status. PLoS One. 2014 Apr 14;9(4):e94863. doi: 10.1371/journal.pone.0094863. PMID: 24733310; PMCID: PMC3986271.
    26. Sheinfeld J, Schaeffer AJ, Cordon-Cardo C, Rogatko A, Fair WR. Association of  the Lewis blood-group phenotype with recurrent urinary tract infections in women. N Engl J Med. 1989 Mar 23;320(12):773-7. PMID: 2922027.
    27. Hu D, Zhang D, Zheng S, et. al. Association of Ulcerative Colitis with FUT2 and FUT3 Polymorphisms in Patients from Southeast China. PLoS One. 2016 Jan 14;11(1):e0146557. doi: 10.1371/journal.pone.0146557. PMID: 26766790; PMCID: PMC4713070.
    28. Opus 23 Pro genetic analysis and reporting software by Dr P. D’Adamo www.opus23.com.
  • Decoding 23andMe ‘i’ Numbers

    23andMe currently reports over 600,000 SNPs in the genome explorer, which are analyzed by their custom 2014 v4 chip. The process used is genotyping, rather than sequencing. The former is cheaper and quicker, and targets specific parts of the genome that are known to have variants in some or many people; the latter is used to find out the code of nucleotide base pairs in a sequence (or continuous stretch) of DNA, the exome (the coding part of DNA), or all the DNA in the whole genome.

    Genotyping does not report on all possible insertions or deletions. In general, it only reports small changes, spanning only one or a few bases. Sequencing will check whether all the DNA code in a region is found in the usual configuration or whether there are any unknown insertions or deletions.

    23andMe doesn’t test for all the SNPs they report on, but might impute variants present on larger chips or in sequencing analysis, using a statistical method that allows researchers to fill in missing data. This may be the reason 23andMe say “This data has undergone a general quality review, however only a subset of markers have been individually validated for accuracy.” [1]

    An example of this might be RhD blood group status: If you have a double deletion (DD) at “i4001527” you are RhD negative, if you don’t have the double deletion (DI or II) you are Rh positive. This number is available from a search in the 23andMe explorer, but is not found in the raw data can be downloaded in an ASCII text file and used for uploading to Opus23 Pro.

    Most of the numbers representing SNPs in the 23andMe raw data begin with ‘rs’, which are reference SNP identifiers, or reference SNP cluster IDs. [2] These rsIDs are assigned and managed by dbSNP, the official database for short genetic variations. However some numbers in the 23andMe raw data begin with ‘i’, which is an internal number assigned by 23andMe for testing locations on the genome for various reasons. This includes SNPs where the probes used differ from the reference sequence.[3] Some ‘i’ numbers are SNPs that don’t have rsIDs: 23andMe maps the i-number to the chromosome position, and internally they map this number to anything else they need to know about the SNPs to put it on a chip (many of these SNPs come from the custom portion of the genotyping array). Other ‘i’ numbers relate to SNPs that could highlight a genetic mutation in a user which is related to significant health risks or genetic conditions. The FDA don’t want users to be able to find out that they have these problems without genetic counselling, except for under specific circumstances where the user has made a declaration that they understand the consequences of accessing this data and what it might mean. The FDA are currently seeking medical opinion on situations where genetic test results might be available directly to the user. Comments can be submitted online  to the FDA by March 31st 2016. All submissions must include reference to: “Docket No.  FDA-2015-N-4809 for `Patient and Medical Professional Perspectives on the Return of Genetic Test Results; Public Workshop; Request for Comments.’”

    How does Opus23 Pro deal with ‘i’ numbers?

    Opus23 Pro curators use the genomic location linked with the coded ‘i’ numbers to find the rsID (if one exists), and if relevant, the ‘i’ numbers are added to the Opus23 Pro SNP database, and a lookup is performed by the software when analysing a client’s raw data. The ‘i’ numbers are linked with the rsID in the software, and this gives the practitioner a reference for further research in published medical literature. Any significant genetic risk factors can be added to the client report and explained to the patient, along with genetic counselling as necessary.


    1. Web page: “How 23andMe Reports Genotypes” https://customercare.23andme.com/hc/en-us/articles/212883677-How-23andMe-Reports-Genotypes.  Accessed 3/5/16
    2. The NCBI Handbook [Internet]. 2nd edition. Bethesda (MD): National Center for Biotechnology Information (US); 2013-. Accessed 3/5/16

    3. 23andMe forum “23andMe upgrading to NCBI Build 37 coordinates on Aug. 1” https://www.23andme.com/you/community/thread/14308/6/ Accessed 3/5/16
  • Psychic

    The Opus 23 PSYCHIC app allows you to search for natural products known to control gene expression. However, unlike a simple search engine, PSYCHIC is able to crawl up and down the molecular ‘Interactome’ (protein-protein interactions and gene expression data) to determine the upstream and downstream genes that interact with the gene you’ve searched for. In addition PSYCHIC allows you to chose which type of natural products (agonists/ antagonists) to include in the upstream and downstream results.

    As seen above, when the PSYCHIC screen loads you will be presented with the results of the default search term for the current client, the MTOR gene. The main infographic is comprised of a bar graph divided into two halves. The left half displays the upstream results, while the right half displays the downstream results, based on MTOR’s position in the interactome. The labels along the x-axis display the various natural products and their gene targets PSYCHIC has found that meet the search criteria. The y-axis value of each bar in the graph is determined by the evidence basis and strength of the position in the network for the gene depicted.

    At the bottom is a small half-pie chart depicts the SNPs for that gene contained in the Opus 23 Pro database.


    You can set filters on each half of the graph to limit results to a specific type (agonism or antagonism) by selecting an option from the pull down menu below. There are four options:

    • Inhibit/ Drain: This will tell PSYCHIC to return all upstream antagonists and downstream agonists
    • Inhibit/ Bottleneck: This will tell PSYCHIC to return all upstream antagonists and downstream antagonists
    • Stimulate/Drain: This will tell PSYCHIC to return all upstream agonists and downstream agonists
    • Stimulate/ Bottleneck: This will tell PSYCHIC to return all upstream agonists and downstream antagonists

    To select a gene to run in PSYCHIC, simply begin typing in its gene symbol in the text input field; PSYCHIC will auto-complete the entry with any genes for which it has data. If multiple options are displayed, simply select the gene you wish to analyze.

    When you’re ready, press the ‘Run Psychic’ button to have PSYCHIC run results.

    PSYCHIC uses highcharts.js for its data depiction, the CPAN Perl module graph.pm for creating the abstract data structures, the PPI (protein-protein interactions) database, and Opus 23’s own internal agent/gene expression database of PubMed citations.