Journal: PeerJ

Article Title: Advancements in monitoring: a comparison of traditional and application-based tools for measuring outdoor recreation

doi: 10.7717/peerj.17744

Figure Lengend Snippet: Research questions that compare data from traditional and application-based tools.

Article Snippet: Strava Global Heatmap – Strava Global Heatmap (hereafter, Strava Heatmap; https://www.strava.com/heatmap) is a crowdsourced heatmap that uses GPS-based recreation tracks of public non-motorized recreation activities (run, hike, walk, ride, water, winter) recorded on phones, fitness watches, and GPS devices.

Techniques:

Journal: PeerJ

Article Title: Advancements in monitoring: a comparison of traditional and application-based tools for measuring outdoor recreation

doi: 10.7717/peerj.17744

Figure Lengend Snippet: Strava Heatmap not displayed (see ). Base map sources: ©OpenStreetMap and contributors, CC-BY-SA.

Article Snippet: Strava Global Heatmap – Strava Global Heatmap (hereafter, Strava Heatmap; https://www.strava.com/heatmap) is a crowdsourced heatmap that uses GPS-based recreation tracks of public non-motorized recreation activities (run, hike, walk, ride, water, winter) recorded on phones, fitness watches, and GPS devices.

Techniques:

Journal: PeerJ

Article Title: Advancements in monitoring: a comparison of traditional and application-based tools for measuring outdoor recreation

doi: 10.7717/peerj.17744

Figure Lengend Snippet: Comparison of tools to monitor recreation use. The table includes a description of how each tool quantifies recreation use, data type (resolution), minimum temporal grain, temporal and spatial extent, recreation activity type (motorized, non-motorized, all recreation activity types), season (summer, winter, year round).

Article Snippet: Strava Global Heatmap – Strava Global Heatmap (hereafter, Strava Heatmap; https://www.strava.com/heatmap) is a crowdsourced heatmap that uses GPS-based recreation tracks of public non-motorized recreation activities (run, hike, walk, ride, water, winter) recorded on phones, fitness watches, and GPS devices.

Techniques: Comparison, Activity Assay

Journal: PeerJ

Article Title: Advancements in monitoring: a comparison of traditional and application-based tools for measuring outdoor recreation

doi: 10.7717/peerj.17744

Figure Lengend Snippet: Data for cameras, counters and Strava Metro are from 2017 to 2019 for all spatially matched locations in the study area, data from Strava Heatmap is from 2016 to 2017. Trendline represented in red.

Article Snippet: Strava Global Heatmap – Strava Global Heatmap (hereafter, Strava Heatmap; https://www.strava.com/heatmap) is a crowdsourced heatmap that uses GPS-based recreation tracks of public non-motorized recreation activities (run, hike, walk, ride, water, winter) recorded on phones, fitness watches, and GPS devices.

Techniques:

Journal: PLOS Pathogens

Article Title: Activation loop phosphorylation and cGMP saturation of PKG regulate egress of malaria parasites

doi: 10.1371/journal.ppat.1012360

Figure Lengend Snippet: Heatmaps showing the specificities of PfPKG WT , PfPKG T695A and PfPKG T695E , measured using the X4-S/T-X4 OPAL library (n = 1). Upper and lower panels are Fixed Threonine and Fixed Serine libraries, respectively. Enrichment scores were log2-transformed and displayed as follows: blue (favoured), beige (neutral), red (disfavoured). Sequence logos obtained are shown below each heatmap. Values were converted into a position-specific scoring matrix (PSSM) and Seq2Logo 2.0 was used to convert this to amino acid preferences (shown as sequence bits). Average level was set to 0 and positive and negative values show amino acids favoured or disfavoured in that position. Fixed Ser and Thr displayed in magenta colour.

Article Snippet: Heatmaps were made in R studio using package ggplot2 ( https://ggplot2.tidyverse.org ).

Techniques: Transformation Assay, Sequencing

Journal: bioRxiv

Article Title: Immunophenotyping and transcriptional profiling of human plasmablasts in dengue

doi: 10.1101/2021.04.09.439257

Figure Lengend Snippet: Heat maps of the differentially expressed Immunoglobulin genes. 130 immunoglobulin genes including variable and constant regions of heavy and light chains and pseudogenes are shown in the heatmap. IgG, IgA, IgM, IgE and IgD are shown in boxes. Pseudogenes are marked by an asterisk (*). Gradient of high to low gene expression based on z-score normalized counts is indicated from red to blue color. Genes that were significantly differential were only considered and clustered subjects using ward.D2 method. Mentioned on right side of heatmap are gene name with common name (in brackets), log2 fold change (LFC), average normalized counts of naïve (N) and average normalized counts of plasmablast (PB).

Article Snippet: Heatmap was made using heatmaply package in R studio.

Techniques: Gene Expression

Journal: bioRxiv

Article Title: Immunophenotyping and transcriptional profiling of human plasmablasts in dengue

doi: 10.1101/2021.04.09.439257

Figure Lengend Snippet: Transcriptional profiling of the plasmablasts from dengue patients. (A) Principal component analysis (PCA) score plot of normalized counts of 14,773 genes showing clustering within plasmablasts (green) and naïve B cells (black) from eight different acute dengue febrile subjects. (B) Volcano plot with -log (adjusted P value) on y-axis and log2 (fold change) on x-axis. Scattered dots represent genes. Red dots are genes that are significantly upregulated and blue dots represent significantly downregulated genes in plasmablasts versus naïve B cells (total: 4137 genes), whereas grey dots are either non-significant, non-differential or both. (for significant : adjusted P value < 0.05 and P value < 0.01; for differential : log2 fold change >= 1 or =<-1). (C) Heatmap showing the 4137 significantly upregulated (red) or downregulated (blue) genes in plasmablasts compared to naïve B cells from eight different acute dengue febrile patients. Z-score of normalized counts were taken for the heatmap. Ward.D2 method was used for clustering. (for significant : adjusted P value < 0.05 and P value < 0.01; for differential : log2 fold change >= 1 or =<-1). (D) Gene expression profile of select genes that are already known in literature, and (E) immunophenotypic markers used in flow cytometric analysis for plasmablasts. Red- highest and blue- lowest. The gene name with common name in brackets, log2 fold change (LFC), average normalized counts of naïve (N) and average normalized counts of plasmablast (PB) are indicated below the heatmap and are arranged as per the descending LFC values. Z-score of normalized counts were taken for the heatmap. (F) Gene set enrichment analysis (GSEA) performed using gene sets derived from GO: biological process, Hallmark, KEGG and Reactome gene sets from MSigDB. Significant pathways with FDR q value < 25% are shown. Enriched term names are manually collapsed. Positive and negative NES correlates to upregulated and downregulated pathways, respectively in plasmablasts compared to naïve B cells.

Article Snippet: Heatmap was made using heatmaply package in R studio.

Techniques: Gene Expression, Derivative Assay

Journal: bioRxiv

Article Title: Immunophenotyping and transcriptional profiling of human plasmablasts in dengue

doi: 10.1101/2021.04.09.439257

Figure Lengend Snippet: Heat maps of the differentially expressed genes (DEGs) pertaining to select biological processes. Heatmaps (A to F) showing genes related to (A) Proliferation, (B) Metabolism, (C) Antibody synthesis, glycosylation and secretion, (D) Growth factors, (E) Transcription factors (TFs) – top 50 upregulated and top 50 downregulated and (F) Interferon stimulated genes (ISGs). Gradient of high to low gene expression based on z-score normalized counts is indicated from red to blue color. Genes that were significantly differential are shown. Mentioned on right side of heatmap are gene name with common name (in brackets), log2 fold change (LFC), average normalized counts of naïve (N) and average normalized counts of plasmablast (PB).

Article Snippet: Heatmap was made using heatmaply package in R studio.

Techniques: Glycoproteomics, Gene Expression

Journal: bioRxiv

Article Title: Immunophenotyping and transcriptional profiling of human plasmablasts in dengue

doi: 10.1101/2021.04.09.439257

Figure Lengend Snippet: Plasmablasts from dengue patients express several cytokines involved in angiogenesis, cellular extravasation and vascular permeability. Heatmaps showing genes related to (A) cytokines and (B) cytokine receptors. Gradient of high to low gene expression based on z-score normalized counts is indicated from red to blue color. Genes that were significantly differential are shown. Mentioned on right side of heatmap are gene name with common name (in brackets), log2 fold change (LFC), average normalized counts of naïve (N) and average normalized counts of plasmablast (PB). (C) Network analysis performed in STRING describing associations between the upregulated cytokines in plasmablasts based on text-mining; annotated database; experimental evidence; homology. Protein-protein associations are represented by the edges and the thickness of edges corresponds to confidence in the evidences used to deduce the associations (thick – high confidence; narrow – low confidence). Red nodes highlighted represent the cytokines involved in vascular permeability, leukocyte extravasation and angiogenesis.

Article Snippet: Heatmap was made using heatmaply package in R studio.

Techniques: Permeability, Gene Expression

Journal: bioRxiv

Article Title: Immunophenotyping and transcriptional profiling of human plasmablasts in dengue

doi: 10.1101/2021.04.09.439257

Figure Lengend Snippet: Plasmablasts from dengue patients express several adhesion molecules, chemokines and chemokine receptors involved in endothelial interactions and homing to skin or mucosal tissues including intestine. Heatmaps showing genes related to (A) cell adhesion molecules (CAMs), (B) Chemokine and (C) Chemokine receptors. Gradient of high to low gene expression based on z- score normalized counts is indicated from red to blue color. Genes that were significantly differential are shown. Mentioned on right side of heatmap are gene name with common name in brackets, log2 fold change (LFC), average normalized counts of naïve B cells (N) and average normalized counts of plasmablasts (PB). The genes are arranged as per the descending LFC values. (D) Network analysis performed in STRING describing associations between the upregulated cell adhesion molecules (CAMs), chemokines and chemokine receptors in plasmablasts based on text-mining; annotated database; experimental evidence; homology. Protein-protein associations are represented by the edges and the thickness of edges corresponds to confidence in the evidences used to deduce the associations (thick – high confidence; narrow – low confidence). Red nodes highlighted represent the CAMs, chemokines and chemokine receptors involved in vascular endothelial cell interactions, adhesion and cell migration to inflamed tissues, mucosa and intestine.

Article Snippet: Heatmap was made using heatmaply package in R studio.

Techniques: Gene Expression, Migration

Journal: bioRxiv

Article Title: Immunophenotyping and transcriptional profiling of human plasmablasts in dengue

doi: 10.1101/2021.04.09.439257

Figure Lengend Snippet: Transcriptional profile of plasmablast derived from flu vaccinees and their comparison with plasmablast derived from Dengue subjects. (A) Volcano plot with -log (adjusted P value) on y-axis and log2 (fold change) on x-axis. Scattered dots represent genes. Red dots are genes that are significantly upregulated genes and blue dots represent significantly downregulated genes in plasmablasts versus naïve B cells (total: 5008 genes), whereas grey dots are either non- significant, non-differential or both. (for significant : adjusted P value < 0.05; for differential : log2 fold change >= 1 or =<-1). (B) Sample-to-sample correlation heatmap depicting Pearson’s correlation coefficient among samples of dengue and flu. Grouping patterns are represented by agglomerative hierarchical clustering by using Ward.D2 method. Color key depicts a strong correlation for values more than 0.8 (green) or weak correlation for values less than 0.4 (blue). (C) Comparison of GSEA terms enriched for plasmablast versus naïve in Flu with the terms enriched for plasmablast versus naïve in Dengue. Size of the bubble is proportional to the normalized enrichment scores (NES), red and blue color represents terms with positive and negative NES, respectively. Heatmaps showing genes related to (D) Cytokine, (E) Cell adhesion molecules (CAMs). Gradient of high to low gene expression based on z-score normalized counts is indicated from red to blue color. Genes that were significantly differential are shown. Mentioned on right side of heatmap are gene name with common name in brackets, log2 fold change (LFC), average normalized counts of naïve B cells (N) and average normalized counts of plasmablasts (PB). The genes are arranged as per the descending LFC values.

Article Snippet: Heatmap was made using heatmaply package in R studio.

Techniques: Derivative Assay, Comparison, Gene Expression