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About 10,000 papers for “differential expression analysis”
Qun Zhou (414322), Bangli Song (21221704), Yibo He (4805139) et al. · Figshare · 2025
(A) A volcano plot of the DEGs. (B) KEGG pathway enrichment analysis of DEGs. (C) A Venn diagram illustrating the overlap between DEGs and DRGs. (D) A heatmap depicting the expression of 11 de-DRGs based on the GSE63514 dataset.
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Kerry E. Poppenberg (4775556), Lu Li (14069), Muhammad Waqas (535011) et al. · Figshare · 2020
<p><b>A)</b> Scatterplot depicts dispersion in expression between IA and control groups. <b>B)</b> No difference between cell type proportions of aneurysm and control groups was found. In both, neutrophils comprise majority of cells expressed in whole blood transcriptomes. <b>C)</b> Hierarchical clustering using genes with TPM sum>0 for all 67 whole blood transcriptomes. Teal indicates control samples, while pink indicates aneurysm samples.</p>
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Kristin Reiche (25614), Katharina Kasack (636069), Stephan Schreiber (636070) et al. · Figshare · 2015
<p>The expression patterns of mRNA-probes and non-coding probes of 26 breast tumors and 5 normal breast tissues were investigated using the custom microarray. (<b>A.</b>) Fraction of unique genomic loci significantly differentially expressed () between normal and tumor samples located completely in exons of protein-coding genes (Gencode v12), in exons of known lncRNAs (lincRNAs, Gencode v12 lncRNAs, lncRNAs as annotated in lncRNAdb <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Amaral1" target="_blank">[51]</a>, and lncRNAs contained in chromatin <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Mondal1" target="_blank">[27]</a>), in exons of transcripts of uncertain coding potential (TUCPs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Cabili1" target="_blank">[23]</a>), in exons of short RNAs (UCSC sno/miRNA track), in genomic loci with conserved secondary structure motifs (Evofold <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Pedersen1" target="_blank">[59]</a>, RNAz <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Gruber1" target="_blank">[58]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Washietl3" target="_blank">[97]</a> and SISSIz <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106076#pone.0106076-Gesell1" target="_blank">[53]</a>), in antisense-direction to known exons (Gencode v12), or in novel genomic regions. (<b>B.</b>) Fraction of unique genomic loci significantly differentially expressed () between Basal-like and Luminal tumors and located in genomic annotations as described for panel A. Numbers beside bars denote absolute number of unique DE-loci.</p>
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Emily C. Graff (9745447), J. Nicholas Cochran (9745450), Christopher B. Kaelin (9745453) et al. · Figshare · 2020
<p>(<b>A</b>) Log2-fold change vs. magnitude of gene expression for homozygous mutant (M–mutant) (n = 4) vs all unaffected (N&C–normal and carrier) (n = 6) (heterozygous mutant (C–carrier) (n = 3) and homozygous non-mutant (N–normal) (n = 3)). Genes with a significant difference for the strict criteria of significance in both homozygous mutant (n = 4) vs all unaffected (n = 6) and homozygous mutant (n = 4) vs homozygous non-mutant (n = 3) are labeled (triangles). Data was collected for an additional 6 animals, but excluded because of age, cause of death, or principal component analysis results (<b>Methods</b>; <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1008671#pgen.1008671.s005" target="_blank">S5 Table</a></b>; <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1008671#pgen.1008671.s011" target="_blank">S5 Fig</a></b>). (<b>B</b>) Quantitative changes in collagen gene expression for homozygous mutant, heterozygous, and homozygous non-mutant animals. No differences (p = 0.61, two-way ANOVA) were detected between normal and carrier cats.</p>
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Axelle Marchant (3281019), Florence Mougel (30470), Emmanuelle Jacquin-Joly (182895) et al. · Figshare · 2016
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Lisa J. Snoderly-Foster (13883955), Wendy M. Olivas (5786561) · Figshare · 2022
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Emma L. Berdan · Harvard Dataverse · 2021
Scripts and input files for performing the differential expression analyses
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Yue-Ling Peng (6114215), Ya-Fang Dong (16748007), Li-Li Guo (6166310) et al. · Figshare · 2023
<p><b>(A)</b> Heatmap of 20 differentially expressed m7G-related genes in the tumor and normal groups. <b>(B)</b> Pearson’s correlation analysis of the m7G regulators. <b>(C, D)</b> KEGG and GO enrichment analyses of the m7G-related differentially expressed genes (DEGs).</p>
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Gary P. Brennan (164551), Dimitrios M. Vitsios (6037802), Sophie Casey (6037805) et al. · Figshare · 2018
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Lin Lin (46073), Lili Deng (152262), Yongxia Bao (15079639) · Figshare · 2024
<p>(A) Volcano Plot: Compares lncRNA gene expression between normoxia and hypoxia groups. Each point represents a gene, with log2FC on the x-axis and -log10 (FDR) on the y-axis. Significantly differentially expressed genes are marked with blue dots; others are red. (B) Heat Map: Displays hierarchical clustering of differentially expressed lncRNAs. Yellow indicates high relative expression, while blue represents low relative expression. (C) Volcano Plot: Compares mRNA expression between normoxia and hypoxia groups. (D) Heat Map: Shows hierarchical clustering of differentially expressed mRNAs.</p>
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Nian Liu (29935), Qian Deng (582304), Zining Peng (13221129) et al. · Figshare · 2025
Gene expression in the AD training group (A) and OA training group (B) between disease samples and normal samples. (C) The overlap of upregulated DEGs in AD and OA training sets. (D) The overlap of downregulated DEGs in AD and OA training sets.
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Yue-ling Peng (14636780), Ling-xiao Wang (14636783), Mu-ye Li (14636786) et al. · Figshare · 2023
<p>(A) Heatmap of 36 differentially expressed NRGs based on their expression levels. (B) The volcano plot of the differentially expressed NRGs. (C) Boxplot of the expression of necroptosis-related DEGs. N indicates nontumor tissues; T indicates tumor tissues. (D) Mutations in NRGs. A total of 8 genes had a mutation rate ≥3%.</p>
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Ivan Carcamo-Orive (4011683), Marc Y. R. Henrion (9915338), Kuixi Zhu (9915341) et al. · Figshare · 2020
<p><b>(a)</b> All-Samples (AS): 1338 differentially expressed genes with multiple testing corrected p-value<0.05 are shown. <b>(b)</b> Average-per-Patient (ApP): top 500 differentially expressed genes identified in ApP are shown. Color scale indicates normalized residual expression levels (blue: low expression, orange: high expression). Columns have been arranged according to clustering of the samples / donors, (purple: insulin resistant, turquoise: insulin sensitive, orange: female, grey: male). Clustering was performed on all samples / donors agnostically of their IR / IS status and sex.</p>
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Khalid Raza · SpringerBriefs in applied sciences and technology · 2024
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Arvin Chireh (8135064), Rikard Grankvist (3625727), Mikael Sandell (10719902) et al. · Figshare · 2021
<p>(A) Chord plot of top regulated genes and corresponding enriched biological processes from differential expression analysis between infarcted samples (n = 24). (B) Heatmap of top regulated genes (n = 1000) with hierarchical clustering showing two main groups, where the right cluster is exclusively composed by samples from the first hours after the occlusion. Values are normalized expression values centered and scaled in the row direction. (C) Heatmap of the same genes as in B, but also including samples from the non-infarction region (n = 18). Two samples from non-infarction region (arrows) are clustered with infarcted 1–3 hour samples.</p>
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Darren A. Cusanovich (531702), Bryan Pavlovic (531703), Jonathan K. Pritchard (113911) et al. · Figshare · 2015
<p>(a) Examples of differential expression analysis results for the genes <i>HCST</i> and <i>IRF4</i>. The top two panels are ‘MA plots’ of the mean Log<sub>2</sub>(expression level) between the knockdown arrays and the controls for each gene (x-axis) to the Log<sub>2</sub>(Fold-Change) between the knockdowns and controls (y-axis). Differentially expressed genes at an FDR of 5% are plotted in yellow (points 50% larger). The gene targeted by the siRNA is highlighted in red. The bottom two panels are ‘volcano plots’ of the Log<sub>2</sub>(Fold-Change) between the knockdowns and controls (x-axis) to the P-value for differential expression (y-axis). The dashed line marks the 5% FDR threshold. Differentially expressed genes at an FDR of 5% are plotted in yellow (points 50% larger). The red dot marks the gene targeted by the siRNA. (b) Barplot of number of differentially expressed genes in each knockdown experiment. (c) Comparison of the knockdown level measured by qPCR (RNA sample collected 48 hours post-transfection) and the knockdown level measured by microarray. (d) Comparison of the level of knockdown of the transcription factor at 48 hrs (evaluated by qPCR; x-axis) and the number of genes differentially expressed in the knockdown experiment (y-axis). (e) Comparison of the variance in knockdown efficiency between replicates for each transcription factor (evaluated by qPCR; x-axis) and the number of differentially expressed genes in the knockdown experiment (y-axis).</p>
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Marianna Pauletto (538839), Massimo Milan (538838), Joana Teixeira de Sousa (538837) et al. · Figshare · 2015
<p>Number of Differentially Expressed (DE) probes in the two comparisons (LHR vs STR in dark grey; MHR vs STR in light grey), determined through a two-class unpaired SAM. Arrows specify the way in which mRNA expression is different: green arrow “↓”and red arrow “↑” mean lower and higher expression in STR oocytes, respectively. Venn diagrams show the number of DE probes shared between the two comparisons. STR: stripped oocytes; LHR: low hatching rate oocytes; MHR: medium hatching rate oocytes.</p>
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Wanhao Chi (10178817), Wei Liu (20030), Wenqin Fu (10178820) et al. · Figshare · 2021
<p>A: Clustering and heatmap showing mRNA levels in four biological replicates of each condition. B: Volcano plot of significantly regulated genes by starvation (Cutoff values: FDR < 0.05 and fold change ≥ 2 or fold change ≤ -2). (C) Enriched KEGG pathways associated with either down-regulated (blue bars) or up-regulated (red bars) genes.</p> <p>(TIF)</p>
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Thomas Ka-Luen Lui · 2015
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Kali Deans-Fielder · Zenodo (CERN European Organization for Nuclear Research) · 2024
RNA seq was conducted on a cohort of WT and Ddit4-/- (KO) mice that were ad libitum fed (AL) and fasted for 24 hours (SF) prior to doxorubicin administration and sacrificed 6, 12, and 24 hours later (hpi). This experiemnt experiment was conducted as a screen, and therefore there was only n=1 per timepoint/genotype/fed state. To assess for significance differences in gene expression across genotype and fed state, timepoints were combined for differential gene expression analysis. Results are displayed in 3 tabs: DXR-treated AL fed KO v WT, DXR-treated SF KO v WT, and DXR-treated KO SF v AL.
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