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Spotfire

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Spotfire is a data analytics and visualization software product developed by TIBCO Software. It provides users with tools for exploring, analyzing, and presenting data from various sources. Spotfire offers features for interactive data visualization, statistical analysis, and report generation. The software is designed to help users gain insights from their data and make informed decisions.

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Lab products found in correlation

Ingenuity pathway analysis (ipa), by Qiagen (2 mentions) Vectra polaris quantitative pathology imaging system, by Akoya Biosciences (1 mentions) Phenochart whole slide viewer, by Akoya Biosciences (1 mentions) Mirvana isolation kit, by Thermo Fisher Scientific (1 mentions) Targetamp nano g biotin arna labeling kit, by Illumina (1 mentions) Agilent bioanalyzer, by Agilent Technologies (1 mentions) Inform 2.2.1 image analysis software, by PerkinElmer (1 mentions) Microarray scanner system, by Agilent Technologies (1 mentions) Ribopure blood kit, by Thermo Fisher Scientific (1 mentions) Human u133 plus 2.0 array, by Thermo Fisher Scientific (1 mentions) Rnalater buffer, by Thermo Fisher Scientific (1 mentions) Globinclear kit, by Thermo Fisher Scientific (1 mentions) Opal ihc kit, by Akoya Biosciences (1 mentions) Vectra ver 3, by Akoya Biosciences (1 mentions) Simca p software version 11, by Sartorius (1 mentions) Prism 8, by GraphPad (1 mentions) Human genome u133a plus 2.0 array, by Thermo Fisher Scientific (1 mentions) Prism 6, by GraphPad (1 mentions) Mantra quantitative pathology workstation, by PerkinElmer (1 mentions) Bovine serum albumin (bsa), by Jackson ImmunoResearch (1 mentions)

16 protocols using spotfire

1

Transcriptomic Profile of Mtb-Infected THP-1 Cells

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Total RNA from uninfected and Mtb-infected THP-1 cells, treated or untreated with 100 μM RES for 24 hours, was extracted using the mirVana Isolation Kit (Life Technologies). RNA quality was confirmed using the Agilent Bioanalyzer, and only samples with RNA integrity number >7 were processed. Biotinylated complementary RNA was prepared from 100 ng of total RNA using the Epicentre TargetAmp Nano-g Biotin-aRNA Labeling Kit for the Illumina system, followed by hybridization on Illumina human arrays. Raw expression data were extracted by GenomeStudio Gene Expression v1.9.0 and processed with quantile normalization (51 (link)). Hierarchical clustering analysis with complete linkage algorithms was performed using R (52 ). Heat maps were plotted using Spotfire (TIBCO Software Inc.; Spotfire.tibco.com/">http://Spotfire.tibco.com/). Differential expression analysis was performed using Linear Models for Microarray Data (LIMMA) (52 ). GO analysis was carried out by DAVID. Pathway analysis was carried out using IPA (Ingenuity Systems; www.ingenuity.com).
Cheng C.Y., Gutierrez N.M., Marzuki M.B., Lu X., Foreman T.W., Paleja B., Lee B., Balachander A., Chen J., Tsenova L., Kurepina N., Teng K.W., West K., Mehra S., Zolezzi F., Poidinger M., Kreiswirth B., Kaushal D., Kornfeld H., Newell E.W, & Singhal A. (2017). Host sirtuin 1 regulates mycobacterial immunopathogenesis and represents a therapeutic target against tuberculosis. Science immunology, 2(9), eaaj1789.
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2

Multiplex Stained Slide Analysis

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Multiplex stained slides were scanned using a Vectra® Polaris Quantitative Pathology Imaging System (Akoya Biosciences, Marlborough, MA/Menlo Park, CA, USA), and images were visualized in the Phenochart whole slide viewer (Akoya Biosciences, Marlborough, MA/Menlo Park, CA, USA). The images were analyzed using the inForm 2.4.4 image analysis software (Akoya Biosciences, Marlborough, MA, USA/Menlo Park, CA, USA) and Spotfire (TIBCO Software Inc., Palo Alto, CA, USA).
Jung J.Y., Ryu H.J., Lee S.H., Kim D.Y., Kim M.J., Lee E.J., Ryu Y.M., Kim S.Y., Kim K.P., Choi E.Y., Ahn H.J, & Chang S. (2021). siRNA Nanoparticle Targeting PD-L1 Activates Tumor Immunity and Abrogates Pancreatic Cancer Growth in Humanized Preclinical Model. Cells, 10(10), 2734.
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3

Multispectral Image Analysis Protocol

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A spectral library containing the emitting spectral peaks of all fluorophores was created using inForm 2.2.1 image analysis software (Perkin Elmer, Wellesley, MA, USA), based on multispectral images obtained from single stained slides for each marker and associated fluorophore (Fig. 1b). This spectral library was used to separate each multispectral image cube into its individual components (spectral unmixing), allowing for the color-based identification of all six markers of interest in a single image using inForm 2.2.1 image analysis software (Fig. 1c). Quantitative measurement of the area occupied by the inflammatory cells in the scanned image was also performed with the inForm 2.2.1 software. All spectrally unmixed and segmented images were analyzed using inForm and Spotfire™ software (TIBCO Software Inc., Palo Alto, CA, USA).
Cho C.J., Kang H.J., Ryu Y.M., Park Y.S., Jeong H.J., Park Y.M., Lim H., Lee J.H., Song H.J., Jung H.Y., Kim S.Y, & Myung S.J. (2018). Poor prognosis in Epstein-Barr virus-negative gastric cancer with lymphoid stroma is associated with immune phenotype. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 21(6).
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4

Microarray Data Analysis Pipeline

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The Agilent's Microarray Scanner System (Agilent Technologies) was used to detect fluorescence signals on the hybridized microarrays. The microarray image files were read out and processed with the Agilent Feature Extraction Software. The latter determines feature intensities (including background substraction), rejects outliers and calculates statistical confidences. A heatmap was generated to visualize the expression levels of each mRNA and lincRNA (Spotfire, TIBCO Software Inc., Palo Alto, USA). The row and column dendrograms were clustered with the unweighted pair group method with arithmetic mean and Euclidean distance measure. Data are publicly available at the EMBL-EBI Array Express repository (Array Express accession number: E-MTAB-4791).
Al-Quraishy S.A., Dkhil M.A., Abdel-Baki A.A., Delic D, & Wunderlich F. (2016). Protective Vaccination against Blood-Stage Malaria of Plasmodium chabaudi: Differential Gene Expression in the Liver of Balb/c Mice toward the End of Crisis Phase. Frontiers in Microbiology, 7, 1087.
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5

Transcriptome Profiling of Whole Blood

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Whole blood was preserved on RNALater buffer (Ambion). RNA was isolated using the RiboPure-Blood kit (Ambion) and alpha and beta globin mRNA was depleted by GLOBINclear™ Kit (Ambion). Samples were checked for purity and hybridized on Human U133 Plus 2.0 Arrays (Affymetrix). Microarray intensity data of probe sets were normalized by RMA, which includes global background adjustment and quantile normalization. Probe sets representing the same gene were collapsed by taking the probe set with highest expression across all samples. Hierarchical clustering and PCA analyses were performed using Spotfire (TIBCO Software Inc.). Pathway analyses were performed using Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (Ingenuity Systems) software. Detailed description of analyses in supplemental materials.
Kwissa M., Nakaya H.I., Onlamoon N., Wrammert J., Villinger F., Perng G.C., Yoksan S., Pattanapanyasat K., Chokephaibulkit K., Ahmed R, & Pulendran B. (2014). Dengue Virus Infection Induces Expansion of a CD14+CD16+ Monocyte Population that Stimulates Plasmablast Differentiation. Cell host & microbe, 16(1), 115-127.
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6

Dose-Response Curve Analysis Protocol

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Percent inhibition data were analyzed using macro-based Excel analysis sheets generated in-house. Dose-response data were plotted using a four-parameter, variable-slope equation without constraints on the curve top and bottom provided in the curve-fitting program Prism (GraphPad Software, La Jolla, CA). The equation was of the form Y = Bottom + (Top -Bottom)/(1 + 10^((LogIC50 -X)*HillSlope)). Screening data were visualized using SpotFire (Tibco Software, Inc., Palo Alto, CA).
Danthi S.J., Liang B., Smicker O., Coupland B., Gregory J., Gefteas E., Tietz D., Klodnitsky H., Randall K., Belanger A, & Kuntzweiler T.A. (2019). Identification and Characterization of Inhibitors of a Neutral Amino Acid Transporter, SLC6A19, Using Two Functional Cell-Based Assays. SLAS discovery : advancing life sciences R & D, 24(2).
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7

Transcriptional Profiling of Ulcerative Colitis

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Microarray datasets (GSE37283; (17 (link))) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Detailed patient demographic information is available in Table 1 of (17 (link)). Microarray analysis was performed as previously described (18 (link)). Microarray assay were performed on 20 RNA samples isolated from colon mucosa of 20 patients, including 5 normal controls, 4 quiescent UC, and 11 UC with neoplasia. Inclusion criteria is as follows: a previous clinical diagnosis of UC confirmed by an expert GI pathologist, a disease duration > 7 years, and an extent of disease >20 cm proximal to the anal verge. For microarray analysis, expression and raw expression data were summarized and normalized using the Robust Multi-array Average algorithm from the Bioconductor library for the R statistical programming system. All samples were clustered using Ward’s method in Spotfire (TIBCO Software, Palo Alto, CA).
Harusato A., Viennois E., Etienne-Mesmin L., Matsuyama S., Abo H., Osuka S., Lukacs N.W., Naito Y., Itoh Y., Li J.D., Merlin D., Gewirtz A.T, & Denning T.L. (2019). Early-life microbiota exposure restricts myeloid-derived suppressor cell–driven colonic tumorigenesis. Cancer immunology research, 7(4), 544-551.
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8

Multiplexed Immunofluorescence Imaging of FFPE Tissue

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As previously described7 (link), four-micrometer-thick tissue sections obtained from formalin-fixed paraffin-embedded (FFPE) blocks were stained via mFIHC with an Opal IHC kit (AKOYA Biosciences, CA, USA). One representative FFPE block was selected from the pre-NAC and post-NAC specimens per case by the pathologist. The antibodies, dilutions, and activation conditions used are listed in Table S1. Next, a whole slide was scanned using an automated imaging system (Vectra ver. 3.0, AKOYA Biosciences). The whole specimens were captured, with an average of 20 areas at × 200 magnification. We segmented tumor tissues into cancer cell nests and stromal resions, and identified each stained cell with specific phenotypes using image-analyzing software (InForm, AKOYA Biosciences). Before the final evaluation, manual training sessions for phenotype recognition were conducted, followed by automatic machine learning for the algorithm. Two researchers (Ikarashi D, and S.T.) independently evaluated the stained slides, found no significant difference in result. An analytic program (Spotfire, TIBCO software, CA, USA) counted the infiltrating immune cells with specific phenotypes per mm2 in cancer cell nests (intratumor) plus stromal regions (stroma) (Supplemental Fig. 2).
Ikarashi D., Kitano S., Tsuyukubo T., Yamashita M., Matsuura T., Maekawa S., Kato R., Kato Y., Kanehira M., Takata R., Sugai T, & Obara W. (2024). Pathological complete response to neoadjuvant chemotherapy may improve antitumor immune response via reduction of regulatory T cells in muscle-invasive bladder cancer. Scientific Reports, 14, 1442.
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9

Metabolomic Data Normalization and Analysis

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After the data were corrected for minor variation resulting from inter-day variation in instrument tuning (Evans et al., 2009) , the missing values for a given metabolite were imputed with the observed minimum detection value, assuming they were below the limit of detection. For the convenience of data visualization, the raw area counts for each metabolite were rescaled by dividing each sample value by the median value for the specific metabolite. Furthermore, Spotfire (version 3.3.2, TIBCO Software, Palo Alto, CA, USA) was used to generate heatmaps to visualize the data (fold change and p-value versus the control). Principal component analysis (PCA) was performed for global metabolic profiles using SIMCA-P software version 11.5 (Umetrics, Umea, Sweden). Data were analyzed using JMP (SAS, http:// www.jmp.com), a commercial software package, and "R" (http://cran.r-project.org/), a freely available open-source software package. The observed relative concentrations for each metabolite were log-transformed, because, in general, the variance increased as a function of a metabolite's average response. Welch's t-tests were performed to compare data between experimental groups. The false discovery rate (FDR) method was used to account for multiple comparisons, and each FDR was estimated using q values.
Fujimoto K., Kishino H., Hashimoto K., Watanabe K., Yamoto T, & Mori K. (2020). Biochemical profiles of rat primary cultured hepatocytes following treatment with rotenone, FCCP, or (+)-usnic acid. The Journal of toxicological sciences, 45(6).
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10

Quantifying Compound Potency via qRT-PCR

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The CT (Crossing Point) obtained from the Lightcycler was converted to ΔCT by using the formula ΔCT = CT DMSO (robust mean)-CT Sample. ΔCT value was used as the response for curve fitting for pEC50 or IC50 calculations in R using the drm function of the drc package to fit a four-parameter logistic function (L.4 in the drc package) of the form
ΔCT=Max+(Min−Max)/(1+10(SlopeX(Log10(CompoundConcentration)+pXC50)))
For some plots, ΔCT value is converted to fold of induction (or inhibition) by the formula fold of induction = 2ΔCT. The data were graphed using Spotfire (Tibco Software, Inc) or in GraphPad (Prism).
Zeng X., Kirkpatrick R., Hofmann G., Grillot D., Linhart V., Viviani F., Marino J J.r., Boyer J., Graham T.L., Lu Q., Wu Z., Benowitz A, & Cousins R. (2018). Screen for modulators of atonal homolog 1 gene expression using notch pathway-relevant gene transcription based cellular assays. PLoS ONE, 13(12), e0207140.
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