Tag: corr.test

Interferon-gamma is quintessential for NOS2 and COX2 expression in ER- breast tumors that lead to poor outcome

Cell culture The MDA-MB231 (MB231) human breast cancer cell line was obtained from the American Type Culture Collection (ATCC, Manassas, VA) and grown in RPM1-1640 (Invitrogen) supplemented with 10% fetal bovine serum (FBS; Invitrogen, Waltham, MA) at 37 °C in a humidified atmosphere of 5% CO2 in the air. Cells were…

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`MOFAobject@expectations` is empty list

`MOFAobject@expectations` is empty list 0 Hello I run the tutorial (raw.githack.com/bioFAM/MOFA2_tutorials/master/R_tutorials/CLL.html) library(MOFA2) library(MOFAdata) library(data.table) library(ggplot2) library(tidyverse) utils::data(“CLL_data”) MOFAobject <- create_mofa(CLL_data) MOFAobject data_opts <- get_default_data_options(MOFAobject) model_opts <- get_default_model_options(MOFAobject) model_opts$num_factors <- 15 train_opts <- get_default_training_options(MOFAobject) train_opts$convergence_mode <- “slow” train_opts$seed <- 42 MOFAobject <- prepare_mofa(MOFAobject, data_options = data_opts, model_options = model_opts, training_options =…

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Bioconductor – retrofit (development version)

DOI: 10.18129/B9.bioc.retrofit   This is the development version of retrofit; to use it, please install the devel version of Bioconductor. RETROFIT: Reference-free deconvolution of cell mixtures in spatial transcriptomics Bioconductor version: Development (3.17) RETROFIT is a Bayesian non-negative matrix factorization framework to decompose cell type mixtures in ST data without…

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Graph using corrplot for multiple sets of data

Graph using corrplot for multiple sets of data 1 I am using the corrplot package to create a graph for different sets of matrices. Is there anyway to merge all the graphs together into one using R? R • 2.9k views You can try as follows: library(corrplot) data(mtcars) M <-…

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Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction

Data collection and processing The RNA-sequencing data, clinical information and simple nucleotide variation of LUAD patients were retrieved from TCGA database (portal.gdc.cancer.gov/, accessed April 8, 2022). Nineteen cuproptosis-related genes (CRG) were mainly collected from previous study, including LIPT1, GLS, NFE2L2, NLRP3, LIAS, ATP7B, ATP7A, SLC31A1, FDX1, LIPT2, DLD, DLAT, PDHA1,…

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Bioconductor – metaseqR2

DOI: 10.18129/B9.bioc.metaseqR2     An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms Bioconductor version: Release (3.11) Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining…

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Bioconductor – HPiP

DOI: 10.18129/B9.bioc.HPiP     Host-Pathogen Interaction Prediction Bioconductor version: Release (3.15) HPiP (Host-Pathogen Interaction Prediction) uses an ensemble learning algorithm for prediction of host-pathogen protein-protein interactions (HP-PPIs) using structural and physicochemical descriptors computed from amino acid-composition of host and pathogen proteins.The proposed package can effectively address data shortages and data…

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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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Bioconductor – mirTarRnaSeq

DOI: 10.18129/B9.bioc.mirTarRnaSeq     mirTarRnaSeq Bioconductor version: Release (3.14) mirTarRnaSeq R package can be used for interactive mRNA miRNA sequencing statistical analysis. This package utilizes expression or differential expression mRNA and miRNA sequencing results and performs interactive correlation and various GLMs (Regular GLM, Multivariate GLM, and Interaction GLMs ) analysis…

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Butterfly eyespots evolved via cooption of an ancestral gene-regulatory network that also patterns antennae, legs, and wings

Although the hypothesis of gene-regulatory network (GRN) cooption is a plausible model to explain the origin of morphological novelties (1), there has been limited empirical evidence to show that this mechanism led to the origin of any novel trait. Several hypotheses have been proposed for the origin of butterfly eyespots,…

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Bioconductor – DaMiRseq (development version)

DOI: 10.18129/B9.bioc.DaMiRseq     This is the development version of DaMiRseq; for the stable release version, see DaMiRseq. Data Mining for RNA-seq data: normalization, feature selection and classification Bioconductor version: Development (3.15) The DaMiRseq package offers a tidy pipeline of data mining procedures to identify transcriptional biomarkers and exploit them…

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how to analyse the correlation between two datasets (corr.test and corrplot)

Hi. I am Newbie in R. I am facing the problem of corr.test analysis. Actually, I would like to clarify the correlation between two different vectors ( Bacteria types versus environment factors). Then, I would like to plot a graph like this: There are two dataset for my analysis, here’s…

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network analysis for microbial amplicon sequencing data

Hello, I need to do microbial network analysis to identify the hub taxa and want to compare overall network properties. For this; I already calculated cor value and p-value in R by using the below codes, but I am not sure after this how to use igraph and how to…

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