Tag: PCA

Oncolytic Adenovirus with SPAG9 shRNA Driven by DD3 Promoter Improved the Efficacy of Docetaxil for Prostate Cancer

. 2022 Apr 30;2022:7918067. doi: 10.1155/2022/7918067. eCollection 2022. Affiliations Expand Affiliations 1 Department of Urology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, Jiangsu Province, China. 2 Department of Urology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, Jiangsu Province, China. Free PMC article Item in Clipboard Meng…

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Frontiers | Divergence With Gene Flow and Contrasting Population Size Blur the Species Boundary in Cycas Sect. Asiorientales, as Inferred From Morphology and RAD-Seq Data

Introduction Incipient species are critical for evolutionary biologists to study speciation, but they also challenge taxonomy due to gene flow or ancestral polymorphism. The former and contrasting population size lead to larger intraspecific than interspecific variations, a phenomenon called the species-definition anomaly zone (Jiao and Yang, 2021). The latter results…

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Problem on R when creating a PCA plot

Problem on R when creating a PCA plot 0 A very weird thing is happening to me on R, the first time i installed “ggfortify” pacakage to create a PCA plot, the result was an Rplots.pdf file, it worked perfectly. The second time i used it, with the same exact…

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scRNAseq analysis – h5ad file conversion to Seurat format

scRNAseq analysis – h5ad file conversion to Seurat format 0 Hi all. I have a single .h5ad file that contains scRNAseq data from several samples. I would like to convert it so that I can open it in Seurat (I am comfortable with R, but not with Python). I have…

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Batch-effect detection, correction and characterisation in Illumina HumanMethylation450 and MethylationEPIC BeadChip array data | Clinical Epigenetics

Experimental design and processing steps For the EpiSCOPE study [20], DHA supplementation and gender were balanced as much as possible across the 12 450K BeadChips on each glass slide, with these factors also randomly distributed over the 6 rows and 2 columns of 31 slides (Additional file 1: Fig. S1). Blood…

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Removing replicate not clustering and group with replicate Vs without -edgeR rnaseq analysis

Removing replicate not clustering and group with replicate Vs without -edgeR rnaseq analysis 0 I am working with bacteria samples – in 3 groups that include the control, Treatment A, and Treatment B. From the PCA I find that the replicates are far apart. So I have removed the treatment…

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Bioinformatics Scientist for Whole Genome and Whole Exome Sequencing

** Bioinformatics Scientist for Whole Genome and Whole Exome Sequencing ** The NeuroGenomics and Informatics (NGI) Center lead by Dr. Carlos Cruchaga at Washington University School of Medicine is recruiting a Bioinformatics Scientist to work on Whole Genome and Whole Exome Sequencing. We are seeking an experienced, self-motivated, self-driven scientist…

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Endometriosis-related functional modules and hub genes

Introduction Endometriosis (EMS) is a chronic gynecological disease defined as implantation and periodic growth of the endometrial glands and stroma outside the uterine cavity, causing chronic pelvic pain, severe dysmenorrhea, and infertility in 10% reproductive-age women, among which the infertility rate is approximately 30–50%.1,2 Surgical excision is commonly used for…

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Metagenomics technology and microbial community diversity analysis methods

A large number of microorganisms in nature cannot be cultivated under laboratory conditions by pure culture methods, and the technical methods of traditional microbiology limit the research on environmental microorganisms. The rapid development of high-throughput omics technology has enabled humans to have an unprecedented understanding of the complex microbial communities…

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deseq2 problem

deseq2 problem 0 Hi I am trying to draw a PCA plot with DESeq2 but somehow I cannot use DESeq2 functions. It is a really simple code i wil be pasting below. > transform <- DESeq2::rlog(eliminated_data, blind = TRUE) Error in (function (classes, fdef, mtable) : unable to find an…

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Postdoc in Computer Science / Bioinformatics – University of Bern – job portal

Postdoc in Computer Science / Bioinformatics 80 – 100% The Digital Pathology Research Group at the University of Bern (Group of Prof. I. Zlobec) takes a deep dive into the morphomolecular aspects and spatial biology of colorectal cancer using various computational and tissue visualization techniques in order to gain insights…

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Choose more PC for the silhouette score, and run the deconvolution benchmark and see if it improves, out methods compared to cibersortX #14

Jianwu1 @stemangiola Finalised benchmark: using new tree (treg as a sibling to t_helper) and the tip nodes for non_hierarchical and cibersortx: PCA as reduction method; Overall hierarchical_pairwise_contrast_bayes_silhouette_penalty gives cell signatures that result in the lowest median deconvolution error, it’s ranked first in dim=4 and dim=10, ranked third in dim=2, and…

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Bioinformatics analysis identifies widely expressed genes

1Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Department of Pediatrics, The Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China Correspondence: Jun Qian, Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui,…

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Bioconductor – SNPRelate

DOI: 10.18129/B9.bioc.SNPRelate     This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see SNPRelate. Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data Bioconductor version: 3.12 Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and…

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rna seq – How will Seurat handle pre-normalized and pre-scaled data?

I don’t do transcriptome analysis, it ain’t my thing, however I do understand statistical analysis as well as the underlying issue regarding the public availability of molecular data … I agree with the OP its not ideal. However, yes the OP can continue with ‘clustering’, personally I definitely prefer it…

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dataframe – uwot is throwing an error running the Monocle3 R package’s “find_gene_module()” function, likely as an issue with how my data is formatted

I am trying to run the Monocle3 function find_gene_modules() on a cell_data_set (cds) but am getting a variety of errors in this. I have not had any other issues before this. I am working with an imported Seurat object. My first error came back stating that the number of rows…

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Analysis of differential gene expression of bulk RNA-seq data using “DESeq2” in RStudio. – Yale Library Study Spaces Scheduling

RNA-Seq is a high-throughput sequencing method used for unbiased detection and quantification of messenger RNA molecules, allowing the identification of genes and pathways underlying normal and pathological conditions. RNA-seq sequencing services are increasingly affordable which has led to the proliferation of published data available in public repositories accessible for everyone’s…

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Understanding signatures of positive natural selection in human zinc transporter genes

Datasets and populations We first compiled whole-genome sequencing data to analyze the patterns of variation in ZTGs on two geographical levels. Thus, we explored a worldwide dataset of 2,328 unrelated individuals representing 24 populations across Africa (AFR), Europe (EUR), East Asia (EAS), South Asia (SAS) and America (AMR), denoted as…

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Loop through columns to generate PCA from DESeq2 data

I’d like to generate a PCA of my bulk RNAseq data, coloured by each of my variables in the DESeq2 object “vsd”. My current code looks like this (to generate a single plot): pcaData <- plotPCA(vsd, intgroup=c(“Age”, “BlastRate”), returnData=TRUE) percentVar <- round(100 * attr(pcaData, “percentVar”)) ggplot(pcaData, aes(PC1, PC2, color=Age, shape=BlastRate))…

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Transcriptional kinetics and molecular functions of long noncoding RNAs

Ethical compliance The research carried out in this study has been approved by the Swedish Board of Agriculture, Jordbruksverket: N343/12. Cell culture Mouse primary fibroblasts were derived from adult (>10 weeks old) CAST/EiJ × C57BL/6J or C57BL/6J × CAST/EiJ mice by skinning, mincing and culturing tail explants (for at least 10 d) in DMEM high…

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Interactive Shiny App for Bulk Sequencing Data

calculate_condition_mean_sd_per_gene Calculate statistics for each gene of an expression matrix given a grouping crossPanel Generate the cross plot panel of the shiny app crossPanelServer Generate the cross plot panel of the shiny app crossPanelUI Generate the cross plot panel of the shiny app cross_plot Create a cross plot comparing differential…

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Change of protein-protein-interaction free energy upon ligand binding (procedure and controls) – User discussions

GROMACS version: 2021.1GROMACS modification: No Dear Gromacs and simulation community, in the course of my master’s thesis, I want to determine the protein-protein-binding free energy between two GTPases using PMF calculations via umbrella sampling. Especially I am interested in the contribution of the bound nucleotides (one per protein) which are…

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Genomic variation from an extinct species is retained in the extant radiation following speciation reversal

Vamosi, J. C., Magallon, S., Mayrose, I., Otto, S. P. & Sauquet, H. Macroevolutionary patterns of flowering plant speciation and extinction. Annu. Rev. Plant Biol. 69, 685–706 (2018). CAS  PubMed  Google Scholar  Rhymer, J. M. & Simberloff, D. Extinction by hybridization and introgression. Annu. Rev. Ecol. Syst. 27, 83–109 (1996)….

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r – Can I analyze RNAseq data from two different cell types using the design matrix model.matrix(~0 + group + celltype)?

I have two cell types(11C and 13C) and two groups (KO and CTRL). sample celltype group 11C-17 11C KO 11C-84 11C KO 11C-C 11C CTRL 13C-17 13C KO 13C-84 13C KO 13C-C 13C CTRL As shown in the PCA plot, the cell type is the dominant difference. But, I’d like…

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Large DE LogFC range

Large DE LogFC range 1 @3d20f23f Last seen 1 hour ago Italy I’m working with DESeq2 to make a DE analysis between samples in two different conditions. During the analysis, I identified a batch effect due to the sequencing time modelled as a covariate in the design formula. From the…

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DE analysis model matrix for paired samples

DE analysis model matrix for paired samples 1 @tkapell-14647 Last seen 2 hours ago Helmholtz Center Munich, Germany Hi, I am analyzing a NanoString dataset where the metadata look as below: The factor of interest is the “group” and both groups are found in each mouse (“mouseID”) (paired samples). I…

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H2O is an in-memory platform for distributed, scalable machine learning

H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Flow notebook/web interface, and works seamlessly with big data technologies like Hadoop and Spark. H2O provides implementations of many popular algorithms such as Generalized Linear Models (GLM), Gradient…

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normalization for unsupervised analysis by DESeq2

normalization for unsupervised analysis by DESeq2 1 Hi friends I want to use DESeq2 to normalize the raw count data to do PCA. I dont have colData. What code should I use? because in the DESeq2 workflow we need colData and design. thanks RNA-Seq • 216 views • link updated…

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Genetic diversity and selection in Puerto Rican horses

Horses have been considered one of our most prized possessions, used for travel, work, food, and pleasure for at least five and a half millennia17,18,19,20. Nevertheless, the ancestry of various horse breeds and their characteristic traits remains unclear21. In this paper, we describe the patterns and the origins of genetic…

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Predicting sepsis severity at first clinical presentation: The role of endotypes and mechanistic signatures

Summary Background Inter-individual variability during sepsis limits appropriate triage of patients. Identifying, at first clinical presentation, gene expression signatures that predict subsequent severity will allow clinicians to identify the most at-risk groups of patients and enable appropriate antibiotic use. Methods Blood RNA-Seq and clinical data were collected from 348 patients…

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DESeq2 analysis for targeted RNA-seq

Dear all, I am attempting to perform DESeq2 analysis (using the Geneious plugin) for targeted RNA-seq of several hundred genes. Only the target set of genes is sequenced, as the primer that I use for first strand cDNA synthesis is specific to the target set of genes. I have three…

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Bioinformation Analysis Reveals IFIT1 as Potential Biomarkers in Centr

Introduction Tuberculosis (TB) is considered to be one of the top ten causes of death in the world, about a quarter of the world’s population is infected with M. tuberculosis.1 The World Health Organization (WHO) divides tuberculosis into pulmonary tuberculosis (PTB) and extra-pulmonary tuberculosis (EPTB). Although breakthroughs have been made…

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Pan-AMPK activator O304 prevents gene expression changes and remobilisation of histone marks in islets of diet-induced obese mice

O304 treatment prevents islet gene expression signature changes induced by HFD We have previously demonstrated that the AMPK activator O304 improves blood glucose homeostasis in both human T2D subjects as well as in high-fat diet induced obese and diabetic mouse models. In the present study, we have now analysed the…

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DESeq2 comparisons using contrast

DESeq2 comparisons using contrast 0 Hi all, I recently started analyzing some bacterial RNAseq data. So, I have 4 different strains and for each strain I have 2 conditions. Let’s say strains are A, B, C and D while conditions are X and Y. I have a total of 24…

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Senior Bioinformatics Scientist (Statistical Geneticist) – Research – Cambridge, UK in San Diego, California

Senior Bioinformatics Scientist – Cambridge, UK Candidates wishing to work remotely from the Netherlands, France, or Belgium may also be considered. Overview Since 2001, the cost of DNA sequencing has dropped more than 100,000-fold, from $100,000,000 USD per human genome to less than $600 USD today. This is resulting in…

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RunPCA function – RDocumentation

RunPCA(object, …) # S3 method for default RunPCA( object, assay = NULL, npcs = 50, rev.pca = FALSE, weight.by.var = TRUE, verbose = TRUE, ndims.print = 1:5, nfeatures.print = 30, reduction.key = “PC_”, seed.use = 42, approx = TRUE, … ) # S3 method for Assay RunPCA( object, assay =…

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No differentially expressed genes

Hi, I have a dataset now with 36k lncRNAs and I’m using DESeq2 to find differentially expressed lncRNAs between a healthy group and a disease group, but unfortunately I cannot find any DE lncRNAs with low padj values. However, when I explore my data by taking the log2 fold change…

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Large-scale genome-wide study reveals climate adaptive variability in a cosmopolitan pest

Genomic data The foundational resource for this study was a dataset of 40,107,925 nuclear SNPs sequenced from a worldwide sample of 532 DBM individuals collected in 114 different sites based on our previous project15. DNA was extracted from each of the 532 individuals using DNeasy Blood and Tissue Kit (Qiagen,…

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Metagenomics survey of major metabolic network of sunflower microbiota

Abstract The microbial communities inhabiting the root, termed the rhizosphere, are in a symbiotic association with their host. However, the plant-microbe interaction study at its current stage is still an evolving field of science. Though still largely unexplored, the soil consists of a metabolically active microbiome where microorganisms are abundant….

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Are these samples good enough for DEA analysis?

Are these samples good enough for DEA analysis? 0 Hi all, Are these samples good enough for DEA analysis? Because I think the tumor and normal samples are not well separated. Here is my code: NormalizedCounts.scaled <- t(scale(t(NormalizedCounts) , scale = F)) pc <- prcomp(NormalizedCounts.scaled) pcr <- data.frame(pc$rotation[,1:3] , Group…

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Design formula in DESeq2

Hello, I am using DESeq2 for analysis of RNAseq data. I would like to ask you about the design in the DESEq2 formula. I have tissue from animals treated with a chemical and my animal model is a colorectal cancer model. My variables are gender (male or female), treatment (treated…

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Identification of lipid metabolism-associated gene signature

Background Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer. Despite the dramatic improvement in breast cancer prognosis due to recent therapeutic advances, such as more effective adjuvant and neo-adjuvant chemotherapies, together with more radical and safer surgery, advances in early diagnosis and treatment over the…

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tSNE and UMAP of scATAC-seq data looks like spaghetti

tSNE and UMAP of scATAC-seq data looks like spaghetti 0 I would like to use R to generate cluster my 20k cells from a single cell ATAC-seq experiment. I ran PCA then selected the first 50 components, which were put into tSNE’s normalize_input() then Rtsne(). This is the result I…

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Assigning Object to Function Rather than vice-versa?

R Syntax Clarification in DeSeq2 Vignette: Assigning Object to Function Rather than vice-versa? 1 Hi, I have a question about some of the R syntax present in the DeSeq2 vignette. The following comes directly from the section regarding the removal of batch effects: mat <- assay(vsd) mm <- model.matrix(~condition, colData(vsd))…

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Bioconductor – lfa

    This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see lfa. Logistic Factor Analysis for Categorical Data Bioconductor version: 3.2 LFA is a method for a PCA analogue on Binomial data via estimation of latent structure in the natural parameter. Author: Wei Hao,…

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About outliers and non -separated samples in PCA

About outliers and non -separated samples in PCA 0 Hi all, I have plotted PCA for my samples(Tumor and Normal) in some cancer types. I have used the HTSeq-counts data from TCGA. Then I’ve normalized them by DESeq2 and the total normalized counts are in cnt dataframe. Head of cnt:…

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pca3d worked with 3 dimension

pca3d worked with 3 dimension 0 Hello, I want to show pca in three dimension with pca3d. But I can not see anything. It said “Creating new device”. Thank you in advance for great help! Best, Yue library(pca3d) library(rgl) data( metabo ) pca <- prcomp( metabo[,-1], scale.= TRUE ) pca3d(…

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RStudio AI Weblog: torch for tabular information

Machine studying on image-like information will be many issues: enjoyable (canines vs. cats), societally helpful (medical imaging), or societally dangerous (surveillance). As compared, tabular information – the bread and butter of knowledge science – could appear extra mundane. What’s extra, if you happen to’re notably all for deep studying (DL), and…

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Error running smartpca from eigensoft: failed to create thread

Error running smartpca from eigensoft: failed to create thread 1 Hello, I’m trying to run smartpca from the eigensoft package (v. 6.1.4). However, I get a premature termination with a “Failed to create thread” error. Any idea where this is coming from or how to fix it? I’ve attached below…

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PCA troubles

PCA troubles 0 Hello everyone! I’m trying to project my ancient sample on PCA with 2 different basis: simons data and 1000. I am using smartpca from admixtools and eigenstrat files as input (exclude outliers). Something strange occurred, the ancient genome and its downsampling versions (cucrled) laid far away from…

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How to describe bi-plot PCA figure?

How to describe bi-plot PCA figure? 1 Hello everyone, I have this bi-plot PCA in my manuscript. I submitted this manuscript in a journal and now one of the reviewers has said “the authors do not identify clearly what are the PC1 and PC2 components”. I really couldn’t figure out…

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principal component analysis on pool-seq SNP data

principal component analysis on pool-seq SNP data 0 I would like to perform principal component analysis on a pool-seq SNP dataset. I’ve been looking into methods for doing this, but have had trouble finding examples that may apply for pooled data as opposed to individual genotypes. For example, I’m not…

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Frontiers | Plasma Cell-Free DNA Methylomics of Bipolar Disorder With and Without Rapid Cycling

Introduction Bipolar disorder (BD) features recurrent episodes of mania/hypomania and depression, interspersed with periods of euthymia. Symptoms usually include drastic changes in energy levels, sleep, thinking, and behaviors, which can significantly disrupt the daily life of BD patients (Craddock and Sklar, 2013). A mood cycle is defined as the period…

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principal compoent analysis on pool-seq SNP data

principal compoent analysis on pool-seq SNP data 0 I would like to perform principal component analysis on a pool-seq SNP dataset. I’ve been looking into methods for doing this, but have had trouble finding examples that may apply for pooled data as opposed to individual genotypes. For example, I’m not…

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The Construction and Comprehensive Analysis of a ceRNA Immunoregulator

1Department of Cardiology, Xiangtan Central Hospital, Xiangtan, Hunan, People’s Republic of China; 2Department of Cardiology, Guangxi Cardiovascular Institute, The First Affiliated Hospital of Guangxi Medical University, Guangxi, People’s Republic of China; 3Department of Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, Hunan, People’s Republic of China Correspondence: Yiqian ZengDepartment of Critical…

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Normalization by variance stabilizing transformation VST

Normalization by variance stabilizing transformation VST 1 @6c372dab Last seen 8 hours ago Sweden Hello! I am a bit confused about the normalization performed by the DESeq2 varianceStabilizingTransformation() and vst() functions in addition to the actual variance stabilization. My understanding is that the normalization by division by size factors (which…

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corral: Single-cell RNA-seq dimension reduction, batch integration, and visualization with correspondence analysis

Abstract Effective dimension reduction is an essential step in analysis of single cell RNA-seq(scRNAseq) count data, which are high-dimensional, sparse, and noisy. Principal component analysis (PCA) is widely used in analytical pipelines, and since PCA requires continuous data, it is often coupled with log-transformation in scRNAseq applications. However, log-transformation of…

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A series of scripts that facilitate the prediction of protein structures in multiple conformations using AlphaFold2

This repository accompanies the manuscript “Sampling the conformational landscapes of transporters and receptors with AlphaFold2” by Diego del Alamo, Davide Sala, Hassane S. Mchaourab, and Jens Meiler. The code used to generate these models can be found in scripts/ and was derived from the closely related repository ColabFold. This repository…

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Diagnostic markers of AIDS combined with TM infection

Introduction The prevalence of Human immunodeficiency virus/Acquired Immune Deficiency Syndrome (HIV/AIDS) is still a public health problem that threatens the health of all human beings. According to the latest report of the World Health Organization, in the end of 2019, there were 38 million patients with human immunodeficiency virus/acquired immunodeficiency…

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Rstudio Online Free

Listing Results Rstudio online free RStudio Cloud Preview 2 hours agoRStudio Cloud is a lightweight, cloud-based solution that allows anyone to do, share, teach and learn data science online. Analyze your data using the RStudio IDE, directly from your browser. Share projects with your team, class, workshop or the world….

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Analyzing DEG from different dataset in my study design

Analyzing DEG from different dataset in my study design 0 Hi I have a situation here which make me confused and not sure if i have every thing right. I compared 5 different datasets in one study with each other separately. for example data1 vs data2, data1 vs data3, data1…

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Senior Bioinformatics Scientist in Cambridge, Cambridgeshire | The Tec Recruitment Group Limited

Senior Bioinformatics Scientist – Cambridge Remote/hybrid working option Role overview: You will be part of an industry leading Genomics company, who are working in the development and accessibility of sequencing products to push the boundaries of drug discovery and therapy development. You will be part of a global team of…

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Identification of downstream effectors of retinoic acid specifying the zebrafish pancreas by integrative genomics

Retinoic acid affects the transcriptome of zebrafish endodermal cells To identify genes regulated by RA in zebrafish endodermal cells, we used the transgenic Tg(sox17:GFP) line which drives GFP expression in endodermal cells and allows their selection by fluorescence activated cell sorting (FACS). Tg(sox17:GFP) embryos were treated either with RA, BMS493…

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r – Change line width of specific boxplots with ggplot2

I am using the following code to generate a box plot: df %>% ggplot2::ggplot(ggplot2::aes(x = group, y = count, fill = batch)) + ggplot2::geom_boxplot(ggplot2::aes(lwd = stroke)) + ggplot2::scale_y_log10() + ggplot2::theme_bw() + ggplot2::theme( axis.text.x = ggplot2::element_text(angle = 90, hjust = 1), legend.position = “none” ) + ggplot2::labs(title = nm_dds) which produces…

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Matlab cross-validation in PCA in bioinformatics data analysis – Freelance Job in Quantitative Analysis – Less than 30 hrs/week – undefined

Require help in matlab working in bioinformatic dataset that consists of 3 alignment methods. 1)Clustal, 2)Muscle, and 3) is Mafft Each method has its own data that consists of Matrix of N X M where the N = number of observations and M = number of Variables. Clustal = 32…

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european-soccer from arthur960304 – Github Help

Data Analysis and Machine Learning with Kaggle European Soccer Database Getting Started These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system. Dataset Kaggle…

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Asc-Seurat: analytical single-cell Seurat-based web application | BMC Bioinformatics

To demonstrate Asc-Seurat’s functionalities, we analyzed the publicly available 10× Genomics’ 3k Peripheral Blood Mononuclear Cells (PBMC) dataset [26], showcasing the analysis of an individual sample. In addition, we used a second PBMC dataset to demonstrate the analysis integrating multiple samples in Asc-Seurat. The second PBMC dataset was generated by Hang…

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PCA plot from read count matrix from RNA-Seq

NB – this is now a Bioconductor R package: github.com/kevinblighe/PCAtools ————————- You should normalise your data prior to performing PCA. In the code below, you’ll have to add plot legends yourself, and also colour vectors (passed to the ‘col‘ parameter). Then, assuming that you have transcripts as rows and samples…

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Interploidy gene flow involving the sexual-asexual cycle facilitates the diversification of gynogenetic triploid Carassius fish

1. Muller, H. J. The relation of recombination to mutational advance. Mutat. Res. Mol. Mech. Mutagen. 1, 2–9 (1964). Google Scholar  2. Maynard Smith, J. The Evolution of Sex (Cambridge University Press, 1978). Google Scholar  3. Avise, J. C. Clonality (Oxford University Press, 2008). Google Scholar  4. Hamilton, W. D.,…

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how to find each cluster in single-cell represent which cell type?

how to find each cluster in single-cell represent which cell type? 0 I have a gene expression matrix and I would like to cluster it and find different cell-types. Let’s suppose we would like to cluster our gene expression matrix (gene* cells) and use one of the clustering methods such…

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python – predictions on datasets

Closed. This question needs debugging details. It is not currently accepting answers. Want to improve this question? Update the question so it’s on-topic for Stack Overflow. Closed 18 hours ago. We were given 3 datasets: X_public , y_public and X_eval. We are supposed create…

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Genes and Pathways Involved in Postmenopausal Osteoporosis

Introduction Many postmenopausal women suffer from postmenopausal osteoporosis (PMO). A survey of 3247 Italian postmenopausal women found that according to bone mineral density (BMD) diagnostic criteria, the prevalence of osteoporosis was 36.6%.1 PMO patients may suffer from chronic pain and fractures, and as a result their quality of life is…

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Use yyplot to modify the font of ggplot2 drawing, causing the arrow position in the figure to shift

Hi, I am using ggplot2 to draw a scatter plot of PCA analysis. In order to make the results more intuitive, I used geom_label_repel to add labels and arrows. In addition, I want to modify the font in the figure and use yyplot. But after using yyplot to modify the…

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Principal Component Analysis Rna Seq

Listing Results Principal component analysis rna seq Genomatix Principal Component Analysis For RNASeq Data Preview 2 hours agoThis is explained in detail on “RNA–Seq workflow: gene-level exploratory analysis and differential expression”. The matrix of raw counts is input to the DESeq2 rlog function and the resulting transformed matrix is used…

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95% confidence intervals for PCA in DESEQ2

95% confidence intervals for PCA in DESEQ2 2 @add481ab Last seen 1 hour ago United States Dear Help, We have used your package DESEQ2 (including the vst transform) on some RNA-seq data, in order to perform PCA analysis. We were hoping to add Monte-Carlo noise to the data in order…

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Plink2 –keep Removing All Samples

Plink2 –keep Removing All Samples 1 I am trying to include the –keep and –remove options in my plink2 command. I am finding that despite my files for these options having identical text to the main file’s IDs, all the samples are removed. Command: plink2 –bfile pca_final –keep EUR.sample –remove…

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Linked supergenes underlie split sex ratio and social organization in an ant

Significance Some social insects exhibit split sex ratios, wherein a subset of colonies produce future queens and others produce males. This phenomenon spawned many influential theoretical studies and empirical tests, both of which have advanced our understanding of parent–offspring conflicts and the maintenance of cooperative breeding. However, previous studies assumed…

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Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data

The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic methods in recent years. In this paper,…

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Python Scikit learn PCA plt.bar

Can anyone help to explain items in these codes when we plot and check the variance of the component: var = np.round(pca.explained_variance_ratio_*100, decimals = 1) lbls = [str(x) for x in range(1,len(var)+1)] plt.bar(x=range(1,len(var)+1), height = var, tick_label = lbls) The original article about Implementation of Principal Component Analysis(PCA) in K…

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Archaeogenetic analysis of Neolithic sheep from Anatolia suggests a complex demographic history since domestication

We analyzed DNA from 180 archaeological sheep bone and tooth samples from late Pleistocene and early Holocene Anatolia, originating from six different sites from central and west Anatolia and spanning the Epipaleolithic/Pre-Pottery Neolithic (n = 7) and early to late Pottery Neolithic (n = 173) periods (Fig. 1 and Supplementary Data 1). We generated genome-wide ancient…

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VCF file generation from multiple samples fro PCA

VCF file generation from multiple samples fro PCA 0 I am trying to generate vcf file for 80 samples(human) and use it for pca. But when trying to get eigen vectors using plink it says genotyping rate is 0.12 and when i remove snps with missing data threshold all data…

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Comment: how to improve PCA visualization using ggplot?

Thanks the legend worked. the PC1 and PC2 axes didn’t! it says: Error in “PC1 (” + percentage[1] : non-numeric argument to binary operator that is how my percentage looks like > percentage [1] ” (36.61%)” ” (33.7%)” ” (19.75%)” ” (18.03%)” ” (-0.1%)” I can only adjust the `hjust=0.4`…

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Answer: how to improve PCA visualization using ggplot?

I like to use `labs` instead of `xlab` and `ylab` and add the information to the data.frame directly. Do you only have 4 data point and you are certain that the name are corresponding to the correct PC value? If so do “` percentage <- round((eigenval/(sum(eigenval))*100), 2) percentage <- as.matrix(percentage)…

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how to improve PCA visualization using ggplot?

I have used this piece of script to draw the PCA based on eigenvalue and eigenvector percentage <- round((eigenval/(sum(eigenval))*100), 2) percentage <- as.matrix(percentage) percentage <- paste0(names(percentage), " (", percentage, "%)") Names <- c ("mn27hd", "mdkk987", "mnsdnu83", "sjednu83", "bjeo972s") pop.colour <- c("blue", "red", "green", "orange", "brown") ggplot(eigenvec, aes(x=PC1, y=PC2, colour=pop.colour, label=Names))…

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Assessment of CircRNA Expression Profiles and Potential Functions in Brown Adipogenesis

doi: 10.3389/fgene.2021.769690. eCollection 2021. Affiliations Expand Affiliations 1 Department of Biotechnology, College of Life Sciences, Xinyang Normal University, Xinyang, China. 2 Institute of Animal Science and Veterinary Medicine, Hainan Academy of Agricultural Sciences, Haikou, China. 3 Institute for Conservation and Utilization of Agro-Bioresources in Dabie Mountains, Xinyang Normal University, Xinyang,…

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Problem with vcf file columns

Problem with vcf file columns 0 Hello. I’m having troubles with a vcf file I just generated with Stacks. The thing is that the column of the first sample (the first individual in my vcf file) instead of having the information about the genotype, the depth and other things, it…

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Weird WGCNA plot

Weird WGCNA plot 2 Dear Seniors and All members, I am wondering whether anyone has done weighted gene co-expression network analysis (WGCNA) from Bulk-RNAseq before. I followed the WGNCA tutorial using my data and the module detection outputs are here. However, once I visualized the modules in clustering, I got…

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Population stratification with PCA

Population stratification with PCA 1 Hi all! I have a genotype dataset in plink format. Now I want to correct for population structure with PCA in association analysis. I split my dataset to training and testing datasets. I want to do the PCA only in the training dataset and use…

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Microarrays analysis for differential gene expression by R

You want to be a professional in the field of Bioinformatics by R. If you don’t know how to use R on data problems and what ways of its uses, then this course will be beneficial for you. R is an emerging part of Bioinformatics. There are many sources to…

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DNA methylation batch effect remove

DNA methylation batch effect remove 1 Hi, I’m studying about DNA methylation. I draw heatmap with beta-value, but there are batch effects.. How can I remove these cgID with studio R? DNA effect batch methylation • 24 views Can you explain what do you mean by ‘beta-value’? Generally batch effect…

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analyzing spatial transcriptome data (Part 2)

Recognition of spatial variable features Seurat Two workflows are provided to identify molecular features related to tissue spatial location . The first is differential expression according to the pre labeled anatomical regions in the tissue , This differential expression can be determined by unsupervised clustering or a priori knowledge ….

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Discovery and construction of prognostic model for clear cell renal cell carcinoma based on single-cell and bulk transcriptome analysis

This article was originally published here Transl Androl Urol. 2021 Sep;10(9):3540-3554. doi: 10.21037/tau-21-581. ABSTRACT BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common malignant kidney tumor in adults. Single-cell transcriptome sequencing can provide accurate gene expression data of individual cells. Integrated single-cell and bulk transcriptome data from ccRCC…

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Covariate correction which data take for downstream analysis?

Hi, I am really bad in stats so I am really sorry if this question is inappropriate or too stupid (also I wasn`t if this was the right forum…if not, apologies again!). A collaborator asked me to correct for age and sex using linear regression) our bulk-RNAseq dataset (6 human…

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Bioconductor – courses and conferences

About press copyright contact us creators advertise developers terms privacy policy & safety how youtube works test new features press copyright contact us creators online – flexible short courses. This course is the ideal introduction to english garden history. It provides an overview of five centuries of development, from baroque…

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Gene expression (RNA-seq) clustering

Unsupervised class discovery is a data mining method to identify unknown possible groups (clusters) of items solely based on intrinsic features and no external variables. Basically clustering includes four steps: 1 Data preparation and Feature selection, 2 Dissimilarity matrix calculation, 3 applying clustering algorithms, 4 Assessing cluster assignment I use…

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How to generate a 2D PCA plot from bulk RNA-seq data (log2 CPM) using the PCAtools?

How to generate a 2D PCA plot from bulk RNA-seq data (log2 CPM) using the PCAtools? 1 Hi all, I have bulk RNA-seq data with 12 samples – WT (x4), ‘A’ KO (x4), and ‘B’ KO (x4). I want to generate a 2D PCA plot (biplot) like below figure to…

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Bioconductor – Bioconductor 3.14 Released

Home Bioconductor 3.14 Released October 27, 2021 Bioconductors: We are pleased to announce Bioconductor 3.14, consisting of 2083 software packages, 408 experiment data packages, 904 annotation packages, 29 workflows and 8 books. There are 89 new software packages, 13 new data experiment packages, 10 new annotation packages, 1 new workflow,…

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X-shaped PCA plot

X-shaped PCA plot 0 What does an X-shaped PCA plot indicate? (I performed PCA analysis based on gene expression data. Each dot indicates a gene expression profile, and the colors reflect the cell lines. ) I have never seen PCA plots like this before. Please someone help me! I really…

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Distance matrix PCA

Distance matrix PCA 0 Hi all, I generated PCA values for the 1000genomes dataset using PLINK. I know how to plot the values for PC1 and PC2, but my question is how can I generate a distance matrix to select near samples based on populations? Like for example if I…

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General question about clustering in scRNAseq

I have recently finished an online scRNAseq course. I was a complete beginner in the field and I really enjoyed the course and have learnt a lot. Now that I have an overview of single cell, I have a flood of maybe dumb questions that escaped me during the course….

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