report_comment: >
  This report has been generated by the <a href="https://github.com/nf-core/nanostring/releases/tag/1.3.1"
  target="_blank">nf-core/nanostring</a> analysis pipeline. For information about
  how to interpret these results, please see the <a href="https://nf-co.re/nanostring/1.3.1/docs/output"
  target="_blank">documentation</a>.
report_section_order:
  BD:
    order: 970
  FOV:
    order: 950
  Posctrl_linearity:
    order: 930
  LOD:
    order: 920
  Pos:
    order: 910
  Neg:
    order: 900
  HK:
    order: 890
  Pos_vs_neg:
    order: 880
  POSF_vs_NEGF:
    order: 870
  AVG_vs_MED:
    order: 860
  AVG_vs_BD:
    order: 850
  PCA:
    order: 840
  PCA1_vs_PCA2:
    order: 830
  PCAi:
    order: 820
  HKF:
    order: 810
  plot_normf:
    order: 800
  nf-core-nanostring-hk-genes:
    order: 790
  normalized_qc:
    order: 780
  NSolver_Pathway_Heatmap:
    order: 770
  NSolver_CellType_Heatmap:
    order: 760
  Norm_GEX_HK:
    order: 750
  Norm_GEX_ENDO:
    order: 740
  No_HK_Norm_GEX_HK:
    order: 730
  No_HK_Norm_GEX_ENDO:
    order: 720
  gene_heatmap:
    order: 710
  wo_HKnorm_gene_heatmap:
    order: 700
  "nf-core-nanostring-methods-description":
    order: -1000
  software_versions:
    order: -1001
  "nf-core-nanostring-summary":
    order: -1002

export_plots: true
disable_version_detection: true

# Run only these modules
run_modules:
  - custom_content

custom_data:
  BD:
    id: BD
    section_name: "Binding Density"
    description: "The imaging unit only counts the codes that are unambiguously distinguishable.
      It simply will not count codes that overlap within an image. This provides increased
      confidence that the molecular counts you receive are from truly recognisable
      codes. Under most conditions, forgoing the few barcodes that do overlap will
      not impact your data.<br> Too many overlapping codes in the image, however,
      will create a condition called image saturation in which significant data loss
      could occur (critical data loss from saturation is uncommon).<br> To determine
      the level of image saturation, the nCounter instrument calculates the number
      of optical features per square micron for each lane as it processes the images.
      This is called the Binding Density (BD). The Binding Density is useful for determining
      whether data collection has been compromised due to image saturation. The acceptable
      range for Binding Density is:<br><br> <b>0.1 - 2.25</b> for MAX/FLEX instruments<br>
      <b>0.1 - 1.8</b> for SPRINT instruments<br><br> Within these ranges, relatively
      few reporters on the slide surface will overlap, enabling the instrument to
      accurately tabulate counts for each reporter species. A Binding Density significantly
      greater than the upper limit in either range is indicative of overlapping reporters
      on the slide surface. The counts observed in lanes with a Binding Density at
      this level may have had significant numbers of codes ignored, which could potentially
      affect quantification and linearity of the assay."
  plot_normf:
    id: plot_normf
    section_name: "Normalization Result"
    description: "This plot describes the normalization result obtained."
  POSF_vs_NEGF:
    id: POSF_vs_NEGF
    section_name: "Positive Factor vs. Negative Factor"
    description: "Positive factor plotted against the negative factor (background
      threshold). Values should be in the grey area of the plot, otherwise be investigated
      for potential failure. Red dots mark outliers."
  AVG_vs_MED:
    id: AVG_vs_MED
    section_name: "Average Counts vs. Median Counts"
    description: "The average counts plotted against the median counts."
  PCAi:
    id: PCAi
    section_name: "Principal Component Analysis Inertia"
    description: "Inertia of the analyzed data."
  Pos:
    id: Pos
    section_name: "Positive Controls"
    description: "Positive control spike in boxplots. Red dots mark outliers."
  Neg:
    id: Neg
    section_name: "Negative Controls"
    description: "Negative control spike in boxplots. Red dots mark outliers."
  HK:
    id: HK
    section_name: "Housekeeping Genes"
    description: "Box plots showing the housekeeping gene expression per cartridge.
      Red dots mark outliers."
  Pos_vs_neg:
    id: Pos_vs_neg
    section_name: "Positive Counts vs. Negative Counts"
    description: "Line plot showing the number of positive counts against the number
      of negative counts. Red dots mark outliers."
  AVG_vs_BD:
    id: AVG_vs_BD
    section_name: "Average Counts vs. Binding Density"
    description: "This plot shows the average counts vs the respective binding density
      and can be used to determine outliers that show very low average counts and
      suffer from too high binding density simultaneously. Red dots mark outliers."
  PCA:
    id: PCA
    section_name: "Principal Component Analysis"
    description: "Principal components planes."
  PCA1_vs_PCA2:
    id: PCA1_vs_PCA2
    section_name: "PC1 vs PC2 (PCA)"
    description: "Principal component 1 vs Principal component 2 plot."
  HKF:
    id: HKF
    section_name: "Housekeeping Factors"
    description: "Housekeeping factors. Red dots mark outliers."
  FOV:
    id: FOV
    section_name: "FOV (Imaging)"
    description: "Each individual lane scanned on an nCounter system is divided into
      a few hundred imaging sections, called Fields of View (FOV), the exact number
      of which will depend on the system being used (i.e., MAX/FLEX or SPRINT), and
      the scanner settings selected by the user. <br> The system images these FOVs
      separately, and sums the barcode counts of all FOVs from a single lane to form
      the final raw data count for each unique barcode target. Finally, the system
      reports the number of FOVs successfully imaged as FOV Counted. <br><br> Significant
      discrepancy between the number of FOV for which imaging was attempted (FOV Count)
      and for which imaging was successful (FOV Counted) may indicate an issue with
      imaging performance.<br> Recommended percentage of registered FOVs (i.e., FOV
      Counted over FOV Count) is <b>75%.</b>"
  Posctrl_linearity:
    id: Posctrl_linearity
    section_name: "Positive Control Linearity"
    description: "Six synthetic DNA control targets are included with every nCounter
      Gene Expression assay. <br> Their concentrations range linearly (in codeset)
      from <b>128</b><it>fM</it> to <b>0.125</b><it>fM</it>, and they are referred
      to as <b>POS_A</b> to <b>POS_F</b>, respectively.<br> These Positive Controls
      are typically used to measure the efficiency of the hybridization reaction,
      and their step-wise concentrations also make them useful in checking the linearity
      performance of the assay.<br><br> Since the known concentrations of the Positive
      Controls increase in a linear fashion, the resulting counts should, as well."
  LOD:
    id: LOD
    section_name: "Limit Of Detection (LOD)"
    description: "The Limit Of Detection (LoD) is determined by measuring the ability
      to detect <b>POS_E</b>, the <b>0.5 fM</b> positive control probe, which corresponds
      to about 10,000 copies of this target within each sample tube. <br> On a FLEX/MAX
      system, the standard input of 100<it>ng</it> of total RNA will roughly correspond
      to about 10,000 cell equivalents (assuming one cell contains 10 <it>pg</it>
      total RNA on average). <br> An nCounter assay run on the FLEX/MAX system should
      thus conservatively be able to detect roughly one transcript copy per cell for
      each target (or 10,000 total transcript copies). <br> In most (codeset) assays,
      you will observe that even the <b>POS_F</b> probe (equivalent to <b>0.25</b>
      copies per cell) is detectable above background. Red dots mark outliers."
  normalized_qc:
    section_name: "Quality Control Metrics"
    description: "QC metrics for the data provided by NACHO. Samples that pass the
      required thresholds are marked as <code>PASS</code>.<br><br>\n<b>Outlier Thresholds
      and Metrics:</b> <br><br> Binding Density (BD) < 0.1 and > 2.25 <br> Field of
      View (FoV) < 75 <br> Positive Control Linearity (PCL) < 0.95 <br> Limit of Detection
      (LoD) < 2 <br> Positive normalisation factor (Positive_factor) < 0.25 and >
      4 <br> Housekeeping normalisation factor (house_factor) < 0.091 and > 11 <br>
      Mean Count (MC) <br> Median Count (MedC) <br>"
    plot_type: "table"
    headers:
      "BD":
        format: "{:,.3f}"
        placement: 200
      "BD QC":
        description: "Binding Density QC"
        placement: 300
      "FoV":
        format: "{:,.2f}"
        placement: 400
      "FoV QC":
        description: "Field of View QC"
        placement: 500
      "PCL":
        format: "{:,.3f}"
        placement: 600
      "PCL QC":
        description: "Positive Control Linearity QC"
        placement: 700
      "LoD":
        format: "{:,.3f}"
        placement: 800
      "LoD QC":
        description: "Limit of Detection QC"
        placement: 900
      "MC":
        format: "{:,.1f}"
        placement: 1500
      "MedC":
        format: "{:,.1f}"
        placement: 1600
      "Positive Factor":
        format: "{:,.3f}"
        placement: 1000
      "PNF QC":
        description: "Positive Normalisation Factor QC"
        placement: 1100
      "House Factor":
        format: "{:,.3f}"
        placement: 1200
      "HKNF QC":
        description: "Housekeeping Normalization Factor QC"
        placement: 1300
      "Negative Factor":
        format: "{:,.3f}"
        placement: 1400
  NSolver_Pathway_Heatmap:
    section_name: "Pathway Score Heatmap (nSolver)"
    description: "Pathway Score Heatmap based on nSolver generated scores."
  NSolver_CellType_Heatmap:
    section_name: "Celltype Score Heatmap (nSolver)"
    description: "Celltype Score Heatmap based on nSolver generated scores."
  Norm_GEX_HK:
    id: Norm_GEX_HK
    section_name: "Normalized count values for housekeeping genes."
    description: "Normalized Housekeeping gene count table, including available metadata."
  Norm_GEX_ENDO:
    id: Norm_GEX_ENDO
    section_name: "Normalized count values for endogenous genes."
    description: "Normalized Endogenous gene count table, including available metadata."
  No_HK_Norm_GEX_HK:
    id: No_HK_Norm_GEX_HK
    section_name: "Non-HK-Normalized count values for housekeeping genes."
    description: "Non-Housekeeping-Normalized Housekeeping gene count table, including
      available metadata."
  No_HK_Norm_GEX_ENDO:
    id: No_HK_Norm_GEX_ENDO
    section_name: "Non-HK-Normalized count values for endogenous genes."
    description: "Non-Housekeeping-Normalized Endogenous gene count table, including
      available metadata."
  gene_heatmap:
    section_name: "Count-Heatmap for all or selected set of target genes"
    description: "Normalized and log2+1 transformed gene expression for all or selected
      set of target genes."
  wo_HKnorm_gene_heatmap:
    section_name: "Count-Heatmap for all or selected set of target genes (Non-HK-normalized)"
    description: "Normalized and log2+1 transformed gene expression for all or selected
      set of target genes based on the Non-HK-normalized results."
  genescore_plage:
    section_name: "GeneScores"
    description: "Genescores computed with the PLAGE algorithm using the normalized
      gene expression values for all samples."
    plot_type: "table"
    pconfig:
      format: "{:.3f}"
