Tag: WGCNA

Bioconductor – BioNERO

DOI: 10.18129/B9.bioc.BioNERO     This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see BioNERO. Biological Network Reconstruction Omnibus Bioconductor version: 3.15 BioNERO aims to integrate all aspects of biological network inference in a single package, including data preprocessing, exploratory analyses, network inference, and analyses…

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Spotted Knifejaw Sex Differentiation Unraveled in New Study

A new study published in Biological Macromolecules on Dec. 7 has identified the regulatory mechanism of sex differentiation in the important cultured fish, the spotted knifejaw (X1X1X2X2/X1X2Y). Previous studies have highlighted the pivotal role of the Doublesex mab-3 related transcription (DMRT) family in male sex determination and differentiation. However, its…

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Help me confirm if my reads are properly normalized and transformed or do I need to re-do

Help me confirm if my reads are properly normalized and transformed or do I need to re-do 0 Hello, can you help me confirm whether or not my reads dataset were normalized properly prior to my work on them? The data source is 40 florets from Arabidopsis for 3 replicates…

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Correlation methods giving very different results (WGCNA)

Hi all, I’ve come back to WGCNA after some years and have run into a bit of a quirky result when looking at my soft power thresholds depending correlation the methods I use. Generally, this topic has been discussed a fair bit – but was looking to see if anyone…

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Exploration of the role of oxidative stress-related genes in LPS-induced acute lung injury via bioinformatics and experimental studies

Selection of 152 ALI-related genes (ALIRGs) by weighted gene co-expression network analysis (WGCNA) The samples of the GSE16409, GSE18341 and GSE102016 datasets were discretely distributed before merging, and the sample data (ALI = 21 and control = 14) was uniform after batch processing (Supplementary Fig. 1a,b). To identify the ALIRGs, the WGCNA was performed in…

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SOCS2 inhibits hepatoblastoma metastasis via downregulation of the JAK2/STAT5 signal pathway

Weighted gene co-expression network analysis GSE131329 has comprehensive clinical data, and WGCNA was carried out with this expression profile. WGCNA is a systems biology method for characterizing gene association patterns between different samples, used to identify highly synergistic sets of genes and to screen for candidate biomarker genes or therapeutic…

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WGCNA Dendrogram Branch missing from modules

WGCNA Dendrogram Branch missing from modules 0 Hi all, Currently using hdWGCNA for network construction in a scRNAseq dataset, and I keep identifying branches on the cluster dendrogram that look robust in terms of dissimilarity, but that fail to be assigned as modules. Figure attached. The branches in question are…

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HER2 low expression breast cancer subtyping and their correlation with prognosis and immune landscape based on the histone modification related genes

Barzaman, K. et al. Breast cancer: Biology, biomarkers, and treatments. Int. Immunopharmacol. 84, 106535 (2020). Article  CAS  PubMed  Google Scholar  Siegel, R. L., Miller, K. D., Wagle, N. S. & Jemal, A. Cancer statistics, 2023. CA Cancer J. Clin. 73(1), 17–48 (2023). Article  PubMed  Google Scholar  Mueller, C., Haymond, A.,…

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Trouble generating a dendrogram with colored gene modules using WGCNA for large RNA-seq experiment

Hi all, I am running WGCNA on my big gene expression data set, and running into a bunch of errors. I appreciate any help in advance that you can provide in navigating these! First, the graph generated to choose the power is wacky looking. I chose 28, as I figured…

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Study reveals how maternal diabetes affects birth defects at the single-cell level

In a recent study published in Nature Cardiovascular Research, researchers from California used multimodal single-cell analysis in mice to investigate the mechanisms by which maternal diabetes mellitus contributes to congenital abnormalities in the fetus. They found that during embryogenesis, maternal diabetes alters the epigenomic landscape in cardiac and craniofacial progenitors,…

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WGCNA for different tissues

WGCNA for different tissues 0 Hello everyone, I’m new to using WGCNA and have been exploring tutorials, but the developer’s websites have been under maintenance for weeks. Therefore, I’d like to ask about the potential applications of this methodology and if this analysis can be tailored to my data. Specifically,…

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Music compensates for altered gene expression in age-related cognitive disorders

Global impact of music on the human transcriptome We first aimed at quantifying the global effect of music on the transcriptomes of the two groups of donors separately. ACD patients exposed to music showed 2.3 times more DEGs (n = 2605) than controls (n = 1148); Table 2. Moreover, while the proportion up-regulated/down-regulated DEGs…

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Seeking Advice on WGCNA for Nematode Sexual Dimorphism

Seeking Advice on WGCNA for Nematode Sexual Dimorphism 0 Dear all, I am analyzing RNA-Seq data and am interested in investigating genes involved in sexual dimorphism in nematodes. I have differential expression data (15k genes) in FEMALEvsMALE conditions, each with two replicates (drf1, drf2) for FEMALE and (drm1, drm2) for…

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WGCNA convenience function

Hi, I’m using the below code in a WGCNA worfkflow # memory estimate w.r.t blocksize bwnet <- blockwiseModules(norm.counts, maxBlockSize = 14000, # Genes included in one block TOMType = “signed”, power = soft_power, mergeCutHeight = 0.25, # Threshold to merge modules Equates to 75% similarity – go and check numericLabels…

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connecting co-expression networks to injury and pathology

Full vacancy here: www.universiteitleiden.nl/vacatures/2023/q4/14246-phd-researcher-in-systems-toxicology-connecting-co-expression-networks-to-injury-and-pathology Key responsibilities Systems toxicology is emerging as key methodology to analyze and interpret omics data in the chemical safety: it mimics the modular and multi-factorial nature of diseases and perturbational statuses. In particular, Dr. Callegaro and colleagues in the PI group of Bob van de Water…

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Bioinformatician in Systems Toxicology for Chemical Safety Assessment. Leiden, the Netherlands.

Full vacancy here: www.universiteitleiden.nl/vacatures/2023/q4/14202-postdoc-or-phd-researcher-bioinformatician-in-systems-toxicology-for-chemical-safety-assessment Key Responsibilities The research group of Prof. Bob van de Water aims to unravel cell signaling programs that underlie adverse xenobiotic-induced adverse responses. In particular, high throughput toxicogenomics analysis is applied with innovative gene co-expression network models thus contributing to a system toxicology approach in qualifying…

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Bioinformatics analysis of immune cell infiltration patterns and potential diagnostic markers in atherosclerosis

A database in the Gene Set Enrichment Analysis (GSEA; www.gsea-msigdb.org/gsea/msigdb/index.jsp) platform10,11 was used to identify 134 GLN metabolism-associated genes. Weighted gene co-expression network analysis (WGCNA) and module screening GLN-associated gene sets were investigated using WGCNA. The results demonstrated that when the weighted value was 24 (Fig. 1A), scale independence was greater…

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WGCNA tutorial docs needed: Horvath Lab site down

WGCNA tutorial docs needed: Horvath Lab site down 2 HI I have that and i will sent to you. but i don’t know weather I can do it via this site or I should email to you Login before adding your answer. Traffic: 2356 users visited in the last hour…

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Choosing power value in WGCNA

Choosing power value in WGCNA 0 Hi everyone! I am working with WGCNA and GWENA packages in attempt to get consensus gene modules for several datasets (from about 5 to 500 samples). I would like to find best combination of parameters in net construction and modules detection that would give…

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Comparative transcriptome analysis reveals candidate genes for cold stress response and early flowering in pineapple

Phenotypic response of two pineapple varieties to cold stress Notable differences in flowering time were observed for the two genotypes used in this study. The first signs of flowering were observed up to two weeks later in Dole-17 (precocious flowering tolerant) than in MD2 (precocious flowering susceptible) (Supplementary Figure S1)….

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How do I select a subset of genes for functional enrichment(GO/KEGG) analysis from WGCNA results?

How do I select a subset of genes for functional enrichment(GO/KEGG) analysis from WGCNA results? 0 Hi all, I am working on using WGCNA for a bulk RNA-seq experiment. I have three experimental conditions (control, treatment 1, and treatment 2) and have a total sample size of 18 (6 per…

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Identification and validation of FPR1, FPR2, IL17RA and TLR7 as immunogenic cell death related genes in osteoarthritis

Galluzzi, L. et al. Molecular mechanisms of cell death: Recommendations of the Nomenclature Committee on Cell Death 2018. Cell Death Differ. 25(3), 486–541 (2018). Article  PubMed  PubMed Central  Google Scholar  Garg, A. D. et al. Molecular and translational classifications of DAMPs in immunogenic cell death. Front. Immunol. 6, 588 (2015)….

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Bioconductor – CVE

DOI: 10.18129/B9.bioc.CVE     This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information. This package is for version 3.11 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see CVE. Cancer…

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WGCNA plotEigengeneNetworks error (coercion to logical)

Hi everyone, hope you are all well. I am trying to run the plotEigengeneNetworks function, however I am getting an error. I have used the same code for some time now but now I am using a new machine and another R version. The code and the error is as…

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Pangenome analysis provides insight into the evolution of the orange subfamily and a key gene for citric acid accumulation in citrus fruits

Swingle, W. T. & Reece, P. C. In The Citrus Industry, History, World Distribution, Botany, and Varieties, Vol. 1 (eds Reuther, W. et al.) 190–143 (Univ. of California Press, 1967). Morton, C. M. & Telmer, C. New subfamily classification for the Rutaceae. Ann. Mo. Bot. Gard. 99, 620–641 (2014). Article …

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Single-nucleus transcriptomes reveal spatiotemporal symbiotic perception and early response in Medicago

Nutman, P. S. Centenary lecture. Phil. Trans. R. Soc. B 317, 69–106 (1987). Google Scholar  Kelly, S., Radutoiu, S. & Stougaard, J. Legume LysM receptors mediate symbiotic and pathogenic signalling. Curr. Opin. Plant Biol. 39, 152–158 (2017). Article  CAS  PubMed  Google Scholar  Roy, S. et al. Celebrating 20 years of…

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Identification of co-diagnostic effect genes for aortic dissection and metabolic syndrome by multiple machine learning algorithms

Identification and functional enrichment analysis of common DEGs Batch effects had been eliminated with Rank-In in all samples from the AD combined dataset and GSE98895 dataset, as shown in Fig. 2A,B. The 3023 DEGs (1376 up- and 1647 down-regulated) were screened between AD and control subjects using the ‘limma’ package in…

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Multiomic interpretation of fungus-infected ant metabolomes during manipulated summit disease

Infection mortality, observations of manipulation, and LC–MS/MS Similar to previous laboratory infections with O. camponoti-floridani24, we collected C. floridanus displaying manipulated summiting between four hours before (zeitgeber time, ZT 20) to half an hour after dawn (ZT 0.5), beginning three weeks after infection (Fig. 1). Sham-treated healthy ants showed no mortality…

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WGNCNA , hub gene identification

WGNCNA , hub gene identification 1 Hello All, I have RNASeq analysis data , of three parental cell lines and out of which three resistant isomorphic celline are derived . I have performed the RNAseq analysis and now want to do WGCNA. I have created the modules without the traits…

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Genome-wide analysis of circRNA regulation during spleen development of Chinese indigenous breed Meishan pigs

Background: Numerous circular RNAs (circRNAs) have been recently identified in porcine tissues and cell types. Nevertheless, their significance in porcine spleen development is yet unelucidated. Herein, we reported an extensive overlook of circRNA expression profile during spleen development in Meishan pigs. Results: Overall, 39,641 circRNAs were identified from 6,914 host…

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WGCNA Analysis – blockwiseModules data processing

WGCNA Analysis – blockwiseModules data processing 0 Good evening, I am currently running a WGCNA analysis. As suggested by a colleague, I switched from regular single-block WGCNA calculation to blockwiseModules, due to large (42,000 genes) dataset size. By setting the max block dimension to 40,000 , I obtain two separate…

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Genome-wide analysis of circRNA regulation during spleen development of Chinese indigenous breed Meishan pigs | BMC Genomics

Overview of the sequencing information To explore the presence of circRNAs during spleen development, we assessed circRNAs expression in the spleen tissues of Meishan pigs at various developmental stage. We prepared and sequenced ribo-depleted total RNA-seq libraries, as shown in the flow chart (Fig. 1). Table S2 presents our rudimentary sequencing…

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Bioconductor – Macarron

DOI: 10.18129/B9.bioc.Macarron   This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see Macarron. Prioritization of potentially bioactive metabolic features from epidemiological and environmental metabolomics datasets Bioconductor version: 3.16 Macarron is a workflow for the prioritization of potentially bioactive metabolites from metabolomics experiments. Prioritization integrates…

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How to get normalized counts corrected for variables in the design matrix of DESeq2 as an input for WGCNA

Hi everyone, I am analyzing Bulk RNA-Seq data, I generated the counts with HTSeqcount and I analyzed them with DESeq2. Then, I want to get the normalized counts corrected for the variables in my design matrix (Like age, sex, RIN, …) to use it as an input for WGCNA. But…

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Bioconductor – BioNAR

DOI: 10.18129/B9.bioc.BioNAR   Biological Network Analysis in R Bioconductor version: Release (3.17) the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of…

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How different is rlog transformation from vst transformation in DESeq2

How different is rlog transformation from vst transformation in DESeq2 1 Hi, I am trying to normalize RNA-Seq using DESeq2. I went on their website and they have three different transformations out of which I tried vst (variance stabilization transformation) and rlog. The thing is that if I have only…

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Is it proper to compare two WGCNA matrixes if they were raised to different power (soft threshold)?

Is it proper to compare two WGCNA matrixes if they were raised to different power (soft threshold)? 0 This is a theoretical question. I am trying to do a comparative analysis (meta-analysis, preservation analysis, differential analysis, etc.) on the mRNA expression network constructed from WGCNA. I acknowledge that we were…

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minModuleSize WGCNA

minModuleSize WGCNA 0 Hi all, I have a question regarding choosing the minModuleSize for WGCNA. in the tutorial, they suggested the minModuleSize = 30, but I was wondering how can I choose the minModuleSize for my data. For example, can I choose it as 80? and then how can I…

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Critical genes in human photoaged skin identified using weighted gene co-expression network analysis.

Photoaging is unique to the skin and is accompanied by an increased risk of tumors. To explore the transcriptomic regulatory mechanism of skin photoaging, the epidermis, and dermis of 16 healthy donors (eight exposed and eight non-exposed) were surgically excised and detected using total RNA-Seq. Weighted gene co-expression network analysis…

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Anatomical and molecular characterization of parvalbumin-cholecystokinin co-expressing inhibitory interneurons: implications for neuropsychiatric conditions

Genetic targeting of CCK+ interneurons restricted by the Dlx5/6 driver line in mouse hippocampus and neocortex CCK isoforms and their preprohormone can be expressed in excitatory neurons in addition to GABAergic interneurons [28]. In order to target CCK+ inhibitory interneurons only, we employed an intersectional genetic strategy by simultaneous co-expression…

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Trans-Acting Genotypes Associted with mRNA Expression Affect Metabolic and Thermal Tolerance Traits

doi: 10.1093/gbe/evad123. Online ahead of print. Affiliations Expand Affiliation 1 Department of Marine Biology and Ecology, The Rosenstiel School, University of Miami, Miami, FL, USA. Item in Clipboard Melissa K Drown et al. Genome Biol Evol. 2023. Show details Display options Display options Format AbstractPubMedPMID doi: 10.1093/gbe/evad123. Online ahead of print….

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How to go for Batch correction in RNA-seq expeiment conducted based on imbalanced Experimental design ?

I have received RNA-seq (paired end) data from my sequencing facility. Details are like this. This is human PBMC samples for 98 participants and two days day0 and day7 (corresponding to pre and post vaccination) – in total 196 samples. 54 out of 98 were high responders and 44 were…

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Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis | BMC Gastroenterology

Patients with UC have dysregulated cuproptosis regulators and activated immune responses To clarify the biological functions of cuproptosis regulators in the occurrence and progression of UC. A detailed flow chart of the study process was shown in Fig. 1. We identified 12 CRGs as differentially expressed cuproptosis genes in the evaluation prediction…

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Bioinformatics analysis and reveal potential crosstalk genetic and immune relationships between atherosclerosis and periodontitis

Slots, J. Periodontitis: Facts, fallacies and the future. Periodontology 2000(75), 7–23 (2017). Article  Google Scholar  Kinane, D. F., Stathopoulou, P. G. & Papapanou, P. N. Periodontal diseases. Nat. Rev. Dis. Primers 3, 1–14 (2017). Article  Google Scholar  Teughels, W., Dhondt, R., Dekeyser, C. & Quirynen, M. Treatment of aggressive periodontitis….

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ComBat returns negative expression value

ComBat returns negative expression value 0 Hi, I am trying to use ComBat function to remove the batch effect: combat_data <- ComBat(dat = trans_log, batch = colData$batch) But it returns some negative value, I’m not sure if this is because the batch effect itself is not obvious? Can I use…

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Bioconductor – iNETgrate (development version)

DOI: 10.18129/B9.bioc.iNETgrate   This is the development version of iNETgrate; to use it, please install the devel version of Bioconductor. Integrates DNA methylation data with gene expression in a single gene network Bioconductor version: Development (3.18) The iNETgrate package provides functions to build a correlation network in which nodes are…

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Staff Researcher in Cardiovascular Disease Bioinformatics – Karolinska Institute – job portal

Login and apply Do you want to contribute to improving human health”strong Please join Dr. Bj?rkegren’s team of world-leading bioinformaticians working across the globe in Mount Sinai Hospital in New York to Karolinska Institutet in Sweden and Tartu University Hospital in Estonian. Our main source of systems genetics analyses is…

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Identification of macrophage-related genes in sepsis-induced ARDS using bioinformatics and machine learning

Screening of differentially expressed genes in GSE32707 According to the screening criteria of differentially expressed genes, there were 489 differentially expressed genes between the control and sepsis groups, of which 152 genes were downregulated in sepsis patients and 337 genes were upregulated in sepsis patients (Fig. 1A). In contrast, there were…

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Identification of molecular mechanisms causing skin lesions of cutaneous leishmaniasis using weighted gene coexpression network analysis (WGCNA)

Data information We downloaded all the data used in this research from National Center for Biotechnology Information Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo/). We used the data set GSE1278317 to construct a co-expression network by Differential Gene Expression analysis (DGEs) and Weighted Gene Co-expression Network Analysis (WGCNA). The Data was obtained from…

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Bioconductor EDIRquery

Comment: DESeq2 remove batch effect by James W. MacDonald 63k I would reverse 1 and 2 Answer: Fishpond with unbalanced dataset by Michael Love 40k Thanks for the report, I will follow up on GH. Answer: Can DESeq2 handle low number of samples and replicates? by Michael Love 40k There…

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DESeq2 remove batch effect

DESeq2 remove batch effect 0 @36e3087a Last seen 2 hours ago Taiwan Hi, I’m new in biological analysis. I want to use DESeq2 to do my analysis, I have batch 1 and batch 2, and the batch equals group. If I want to remove the batch effect, should I only…

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Correlation of gene expression in Spatial Transcriptomics (ELI5)

Hi all, I feel totally ill-equip to ask this question that I know is likely a “bad question”, so I am hoping for an educational moment here. I have a set of spatial transcriptomic data that we are trying to squeeze like a dirty dish rag for any salient information….

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Bioconductor – GmicR

DOI: 10.18129/B9.bioc.GmicR     This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see GmicR. Combines WGCNA and xCell readouts with bayesian network learrning to generate a Gene-Module Immune-Cell network (GMIC) Bioconductor version: 3.13 This package uses bayesian network learning to detect relationships between Gene…

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Adjusting for batch effect and covariates with ComBat

Dear All, my question is related to this post: Error in while (change > conv) { : missing value where TRUE/FALSE needed I have a heterogeneous RNAseq dataset in TPMs from 66 samples and two sequencing batches (64 from one batch, 2 from the second batch). This dataset contains many…

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Eigen genes using WGCNA

Eigen genes using WGCNA 2 I have looked up previous WGCNA code that I used and you should be able to produce the gene-to-eigengene colour assignments via: data.frame(colnames(datExpr), mergedColors) Kevin I think this is very old, but I think the commenters are misinterpreting your (miswritten) question. Based on the back-and-forth,…

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WGCNA Trait File Issues

WGCNA Trait File Issues 1 I have RNASeq data that I am trying to use for WGCNA. However I am running into downstream issues that I believe stem from my trait file. I have 24 samples, 3 replicates of 8 different treatment groups. I am trying to follow the WGCNA…

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Network cross-validation

Network cross-validation 0 How to validate that a network constructed from RNA-Seq data is robust when no additional data are available to construct a second network? One approach might be to split the data into 5-folds and then use four of the folds to create the network. Once we have…

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Bioinformatics Analyst II – Seibold Lab job with National Jewish Health

The Seibold Laboratory is a cutting-edge, NIH funded, laboratory focused on elucidating the pathobiological basis of asthma and other complex lung and allergic diseases. Our goal is to discover pathobiological subgroups of disease (termed disease endotypes) and the genetic, environmental, and immune factors driving their development. We are accomplishing these…

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Ageing restructures the transcriptome of the hypothalamic supraoptic nucleus and alters the response to dehydration

Hooper, L. et al. Which frail older people are dehydrated? The UK DRIE study. J. Gerontol. A Biol. Sci. Med. Sci. 71, 1341–1347 (2015). Article  PubMed  PubMed Central  Google Scholar  Cowen, L. E., Hodak, S. P. & Verbalis, J. G. Age-associated abnormalities of water homeostasis. Endocrinol. Metab. Clin. North Am….

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many over and under-expressed features in modules of a signed network

WGCNA: many over and under-expressed features in modules of a signed network 1 In a WGCNA analysis of transcriptome and proteome of a white blood cell in development (in 6 stages), I find in most modules (especially the large ones) over, as well as underexpressed features, but I am using…

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The draft genome sequence of the Japanese rhinoceros beetle Trypoxylus dichotomus septentrionalis towards an understanding of horn formation

Hunt, T. et al. A comprehensive phylogeny of beetles reveals the evolutionary origins of a superradiation. Science 318, 1913–1916 (2007). Article  ADS  CAS  PubMed  Google Scholar  Crowson, R. A. The phylogeny of coleoptera. Annu. Rev. Entomol. 5, 111–134 (1960). Article  Google Scholar  Darwin, C. The Descent of Man, and Selection…

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WGCNA of two different cohorts study

WGCNA of two different cohorts study 0 @a48b0d5d Last seen 2 hours ago Japan Hi I would like to ask for suggestion how can I normalize the dataset before WGCNA analysis since I have two cohorts of my study. As you can see from the diagram; cohort 1 == start…

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Correcting for continuous covariates before WGCNA

Correcting for continuous covariates before WGCNA 1 Hi all, I’m doing WGCNA downstream to DESeq2 and would like to correct for the effect of covariates, including continuous ones (SVs from using SVA package, pH, Age, PMI) and a discrete covariate, namely sex, before moving on with transforming counts using VST….

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WGCNA module-trait correlation heatmap has horizontal streaks — how to interpret/fix?

WGCNA module-trait correlation heatmap has horizontal streaks — how to interpret/fix? 0 Hi, I want to correlate my WGCNA modules with some other module eigengenes and used WGCNA’s moduleTraitCor() function to do so. The correlations returned are shown in the heatmap below. WGCNA modules are on the vertical axis, my…

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CRISPR-cas9 screening identified lethal genes enriched in Hippo kinase pathway and of predictive significance in primary low-grade glioma.

Low-grade gliomas (LGG) are a type of brain tumor that can be lethal, and it is essential to identify genes that are correlated with patient prognosis. In this study, we aimed to use CRISPR-cas9 screening data to identify key signaling pathways and develop a genetic signature associated with high-risk, low-grade…

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How do you select DEGs for further validation?

How do you select DEGs for further validation? 1 Perhaps this a silly question, but I’m overwhelmed with the different ways to give context to results after DGE analysis (RNA sequencing in a disease vs healthy control context). Of course I know that one should establish criteria for significance and/or…

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Bioconductor – miRSM

DOI: 10.18129/B9.bioc.miRSM   This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see miRSM. Inferring miRNA sponge modules in heterogeneous data Bioconductor version: 3.16 The package aims to identify miRNA sponge modules in heterogeneous data. It provides several functions to study miRNA sponge modules, including…

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bioconductor – R package installation and issues with gfortran on Mac M1 while updating old dependent packages

I am trying to install an R library on my Mac M1, the installation process requires updating old libraries. The problem appears to be with gfortran library. I would really appreciate if I can get any guidance on fixing this issue. >sessionInfo() R version 4.1.0 (2021-05-18) Platform: x86_64-apple-darwin17.0 (64-bit) Running…

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Problems with the input (from TPM) to run the WGCNA

Hello everyone, Initially I express that I am not very expert in bioinformatics analysis. I have the TMP from RNAseq data. These data come from Arabidopsis seeds infected with a fungal inoculum. I select the data by calculating the zscore. Thanks to the tutorials and the forums I have managed…

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Same correlation values obtained at different soft threshold powers in WGCNA signed network analysis

Same correlation values obtained at different soft threshold powers in WGCNA signed network analysis 0 Hello, I am performing WGCNA to relate genes with specific traits. While constructing signed network by specifying network type and TOM type as “signed”, I couldn’t decide the appropriate power. So I constructed multiple networks…

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WGCNA problem

WGCNA problem 0 Hello. I have problem to choose soft power for WGCNA. please guide me!! I have 501 sample (cancer=481 , normal=39) that download from TCGA database. Then, normalization and filtration was carried out using TCGA package. With this data I started using WGCNA for co-expression network analysis. For…

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Construction of a circRNA-Related ceRNA Prognostic Regulatory Network in Breast Cancer

Introduction Breast cancer is the second most common cancer and is the leading cause of cancer-related death among females worldwide with over 2 million newly diagnosed cases and more than 60 thousand deaths every year.Citation1 Despite advances in treatment, the mortality rate of breast cancer remains high, mainly due to…

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Comment: How to remove unknown batch-batch effects from GEO datasets

It is a great honor to receive your response. The data in question is sourced from GSE53625. While using arrayQualityMetrics to assess the quality of the data, I noticed batch effects. However, I was unable to identify the known batch effect factors for this dataset. I would like to remove…

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Module color label in WGCNA

Module color label in WGCNA 1 I have a data set with about 500 features. Following the WGCNA tutorial, I got 19 modules. One of them is labeled as grey60, and I am a little confused whether this is unassigned or not. It is a small branch in the middle…

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module and trait correlation for WGCNA

module and trait correlation for WGCNA 0 I am trying to run WGCNA analysis on a microarray dataset. I have been following this tutorial: bioinformaticsworkbook.org/tutorials/wgcna.html#gsc.tab=0 I am confused about the subheading “Relate Module (cluster) Assignments to Treatment Groups.” The question is: Can we see how each module is associated with…

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problem for comparing 2 type of annotation file

Thanks, Dear Dr. Blighe Hi, As you know, my data set belong to TCGA and the labels of genes that I see in my downloaded file is e.g. same as ENSG00000000003. Again, in WGCNA, I have to provide annotation file same as WGCNA tutorial(GeneAnnotation.csv). based on that, I wrote an…

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Creating sample groups from a combination of genes for survival analysis

This is the post/tutorial where Dr Kevin Blighe showed how to perform survival analysis with gene here in this he showed how to use single gene as predictor and create groups based on expression and classify them as mid or high or low. Now How to do the same with…

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Bioconductor – Macarron (development version)

DOI: 10.18129/B9.bioc.Macarron     This is the development version of Macarron; for the stable release version, see Macarron. Prioritization of potentially bioactive metabolic features from epidemiological and environmental metabolomics datasets Bioconductor version: Development (3.17) Macarron is a workflow for the prioritization of potentially bioactive metabolites from metabolomics experiments. Prioritization integrates…

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How is module-trait association calculated in WGCNA?

How is module-trait association calculated in WGCNA? 1 I have read some papers using WGCNA to explore relationship between metabolomics and clinical outcomes. I wanted to use this method in my work as well. Following the tutorial of WGCNA, I can understand most of the method except the module-trait association….

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Batch correction and Deseq2

Hi, I would like to ask that the deta input fort Deseq2 is required a count metric. However, after I look into my count data, I would that there is a batch effect in my count data. How should I normalized my read count data before applying in Deseq2 and…

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WGCNA hub genes VS. DEG

WGCNA hub genes VS. DEG 0 Hi Im a newbie in Bioinfo field. I am now doing WGCNA and DEG on RNA-seq data. I was wondering if DE genes should be the same as hub genes identified through WGCNA? Actually I am a bit confused about the different purposes between…

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Postdoctoral Researcher in Cardiovascular Disease Bioinformatics

Do you want to contribute to improving human health? Please join my team of world-leading bioinformaticians working across the globe in Mount Sinai Hospital in New York to Karolinska Institutet in Sweden and Tartu University Hospital in Estonian. Our main source of systems genetics analyses is the cardiovascular disease (CVD)…

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WGCNA number of modules issue

WGCNA number of modules issue 0 Hi all! I am working on RNAseq data from a 3 treatment: condition 1, condition 2, and condition 3. There are 70k genes in my data. I would like to use WGCNA to find genes expressed correlated to conditions, in particular, strongly positive correlated…

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WGCNA goodGenes message error

WGCNA goodGenes message error 0 Hello I am new to R and when using the WGCNA pipeline I encounter this message error that I can not seem to solve: Error in WGCNA::goodGenes(datExpr, …) : Too few genes with valid expression levels in the required number of samples. I have already…

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Network analysis of 16S rRNA sequences suggests microbial keystone taxa contribute to marine N2O cycling

Fuhrman, J. A. Microbial community structure and its functional implications. Nature 459, 193–199 (2009). Article  CAS  PubMed  Google Scholar  Graham, E. B. et al. Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes? Front. Microbiol. 7, 214 (2016). Article  PubMed  PubMed Central  Google Scholar …

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summary | Finding WGCNA modules that are “absent” from the healthy cells and so “exclusive” to cancer cells ?

Hello, I am currently using the hdWGCNA package on single cell data. So I get modules on a scRNAseq of cancer cells that I project on healthy cells in order to see what are the modules that are “absent” from the healthy cells and so “exclusive” to cancer cells. To…

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A Trem2R47H mouse model without cryptic splicing drives age- and disease-dependent tissue damage and synaptic loss in response to plaques | Molecular Neurodegeneration

The Trem2 R47H NSS mutation promotes loss of oligodendrocyte gene expression in response to cuprizone treatment. Results of previous studies of mice with the Trem2R47H missense mutation introduced via CRISPR suggested that it acts as a near-complete loss of function, recapitulating phenotypes seen in Trem2 knock-out (KO) mice [34, 36]….

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Strange Cook’s Values with DESeq2

Hi, I’m currently trying to assess fold change when comparing two different sample types using DESeq2 package and I’m getting weird Cook’s distance values which are causing major problems. The two different samples have different amounts of replicates (6 replicates vs 5 replicates) which might be the reason for these…

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Nearest neighbors from a determinate gene in the module

Nearest neighbors from a determinate gene in the module 0 Dear community, I am doing a gene co-expression analysis using the R packages WGCNA and igraph for visualization. I have generated all modules and found the hub gene for each one, but, another step I would like to do is…

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Whole-body adipose tissue multi-omic analyses in sheep reveal molecular mechanisms underlying local adaptation to extreme environments

RNA-Seq data Across all 250 adipose tissue samples, a total of 1780 Gb of clean reads were retained with an average of 23.7 million reads (14.6–43.5 million reads) per sample after quality control (Fig. 1a, b and Supplementary Data 1, 2). Of the total clean reads, 83.42–97.42% of reads were mapped to the…

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WGCNA TOM calculation time

WGCNA TOM calculation time 0 I am currently working on co-expression analysis for a data set of around 60,000 genes and running the job on server. I am currently waiting to complete TOM calculation (matrix multiplication BLAS) as it already taken few days and still running. If anyone have any…

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Identification of essential genes and immune cell infiltration in rheumatoid arthritis by bioinformatics analysis

It has been reported that genes are not independent of each other, co-expressed genes may have similar biological functions, and the effect of grouping genes is relatively strong17. WGCNA algorithm, which has been widely used for studying network changes, can be used to identify network topologies and sub-networks (called modules),…

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WGCNA gene selection: gene significance or LASSO?

WGCNA gene selection: gene significance or LASSO? 0 Hello, I am having some trouble understanding how to choose a method for gene selection to identify genes from top WGCNA modules that most correlate with a clinical trait. I understand that WGCNA has a built-in feature called gene significance (GS), which…

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Software Finds Common Biomarkers for PAH, Metabolic Syndrome

Genes associated with both pulmonary arterial hypertension (PAH) and metabolic syndrome have been identified using computer software tools, a study reports. Metabolic syndrome, thought to promote PAH, is a cluster of conditions marked by high blood pressure, elevated blood sugar, excess body fat around the waist, and abnormal cholesterol or…

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Help selecting WGCNA soft thresholding power

Here we go. A word of caution… you seems to have a lot of variation especially in the INT dataset that is not explained by the WS-LS traits. This is why I get a lot of modules. If you have other traits to include in the analysis please, do so….

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A multi-omics integrative network map of maize

Eisenstein, M. Big data: the power of petabytes. Nature 527, S2–S4 (2015). Article  CAS  Google Scholar  Trewavas, A. A brief history of systems biology: ‘Every object that biology studies is a system of systems’. Francois Jacob (1974). Plant Cell 18, 2420–2430 (2006). Article  CAS  Google Scholar  Dixon, S. J., Costanzo,…

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Dementia with Lewy bodies post-mortem brains reveal differentially methylated CpG sites with biomarker potential

Weisman, D. & McKeith, I. Dementia with Lewy Bodies. Semin. Neurol. 27, 042–047 (2007). Article  Google Scholar  Foguem, C. & Manckoundia, P. Lewy Body Disease: Clinical and Pathological “Overlap Syndrome” Between Synucleinopathies (Parkinson Disease) and Tauopathies (Alzheimer Disease). Curr. Neurol. Neurosci. Rep. 2018 18:5 18, 1–9 (2018). CAS  Google Scholar …

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Integrative cross-species analysis of GABAergic neuron cell types and their functions in Alzheimer’s disease

The heterogeneity of GABAergic neurons in human, macaque, mouse, and pig To perform a cross-species comparative study of the GABAergic neurons, we collected the snRNA-seq datasets of the cerebral cortex for human10,11, macaque12,13, mouse14,15, and pig16. After cell-type annotation and filtering out the excitatory neurons and non-neurons, the GABAergic neurons…

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Multi-level cellular and functional annotation of single-cell transcriptomes using scPipeline

Software Figure preparation: CorelDRAW x8 (Corel); Bioinformatic analyses: R v 4.0.3 (R Foundation for Statistical Computing). Computational resources Analyses were run on a desktop computer with an Intel Core i9-10900L CPU (3.70 GHz, 10 cores, 20 threads) with 120 GB RAM running Windows 10 Pro (v21H2). Data preprocessing scRNA-seq data sets…

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Genomic signatures associated with maintenance of genome stability and venom turnover in two parasitoid wasps

Genomic features of two Anastatus wasps, A. japonicus and A. fulloi We employed PacBio high-fidelity (HiFi) long-read sequencing and Illumina short-read sequencing technologies to generate high-quality contigs for two Anastatus wasps, A. japonicus and A. fulloi (Supplementary Tables 1 and 2). These contigs were further scaffolded using Hi-C libraries to…

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