Categories
Tag: LIMMA
Notch signaling in thyrocytes is essential for adult thyroid function and mammalian homeostasis
Brent, G. A. Mechanisms of thyroid hormone action. J. Clin. Invest. 9, 3035–3043 (2012). Article Google Scholar Iwen, K. A., Oelkrug, R. & Brabant, G. Effects of thyroid hormones on thermogenesis and energy partitioning. J. Mol. Endocrinol. 60, R157–R170 (2018). Article PubMed CAS Google Scholar Biondi, B. & Wartofsky, L….
Batch and Sample correction for downstream analysis using DESeq2
Hello everyone, I am an absolute beginner on sequencing analysis and DESeq2, so please forgive me for possibly mundane questions. I have tried to look up different methods, but couldn’t find a fitting answer yet. I am currently working with sequencing data derived from an Illumina sequencer. The data is…
Does gene raw read count mean and dispersion preserve batch effects if I used raw counts from different batches to calculate them?
Question: Does gene raw read count mean and dispersion preserve batch effects if I used raw counts from different batches to calculate them? ContextI ask this because I need these values as inputs to the ssizeRNA_vary function of the ssizeRNA package. Alternatively, I can remove batch effects with removeBatchEffect() function…
Bioconductor – RTN
DOI: 10.18129/B9.bioc.RTN This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see RTN. RTN: Reconstruction of Transcriptional regulatory Networks and analysis of regulons Bioconductor version: 3.12 A transcriptional regulatory network (TRN) consists of a collection of transcription factors (TFs) and the regulated target…
Bioconductor T2T-CHM13
Comment: Reduce single cell experiment size to use as reference for annotation with Singl by elgomez • 0 Thank you, James! I ended up running seurat FindVariableFeatures with nfeatures = 10000 and then subsetting the object to just those varia… Comment: Help with model.matrix and creating the right contrast matrix…
A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain
Mouse breeding and husbandry All experimental procedures related to the use of mice were approved by the Institutional Animal Care and Use Committee of the AIBS, in accordance with NIH guidelines. Mice were housed in a room with temperature (21–22 °C) and humidity (40–51%) control within the vivarium of the AIBS…
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…
Methylation Analysis Tutorial in R_part1
The code and approaches that I share here are those I am using to analyze TCGA methylation data. At the bottom of the page, you can find references used to make this tutorial. If you are coming from a computer background, please bear with a geneticist who tried to code…
removeBatchEffect with non-linear model fit
removeBatchEffect with non-linear model fit 0 @2289c15f Last seen 6 hours ago Germany Hello, I am attempting to use limma’s removeBatchEffect for visualization purposes (heatmat & PCA) while fitting non-linear models (splines) to my expression data in DESeq2. Given that my design is balanced, would this approach work within the…
Cibersort input data
Cibersort input data 1 Hello everynone. Could you please guide me. I have an expression matrix that I have filtered and normalized it by edgeR and limma packages. Can I use this for cibersort? Or I have to use PFKM or TPM for cibersort? cibersort • 122 views • link…
ScRNAseq analysis scran :: quickcluster Error
ScRNAseq analysis scran :: quickcluster Error 1 @d4a334e3 Last seen 15 hours ago Germany Hello! I am having an error while doing normalization for my scRNAseq data, I would appreciate the help of anyone who countered the same problem the error is during quickcluster command as follow: clust <- quickCluster(sce)…
Filter genes by expression for voomLmFit
Filter genes by expression for voomLmFit 1 @78889942 Last seen 1 day ago Switzerland Following up on limma::voom vs edgeR::voomLmFit – when to use? I’m wondering: With limma::voom, we always filtered out lowly-expressed genes (typically using edgeR::filterByExpr) beforehand, because voom did not work well for low-count genes (and also because…
Bioconductor – octad (development version)
DOI: 10.18129/B9.bioc.octad This is the development version of octad; for the stable release version, see octad. Open Cancer TherApeutic Discovery (OCTAD) Bioconductor version: Development (3.19) OCTAD provides a platform for virtually screening compounds targeting precise cancer patient groups. The essential idea is to identify drugs that reverse the gene…
GEO dataset Microarray data analysis help
Hello Everyone , I am new to microarray dataset . I want to do this similar kind of plotting using this same mentioned dataset for a different gene . GEO ID : GSE76008 I have tried GEO2R script : <h6>#</h6> library(GEOquery) library(limma) library(umap) gset <- getGEO(“GSE76008”, GSEMatrix =TRUE, AnnotGPL=TRUE)[1] fvarLabels(gset)…
Microarray batch correction method suggestions
Microarray batch correction method suggestions 0 Hi All, I am working on minimum 10 different datasets of microarray, which combines of Affymetrix, Agilent, illumina etc. All data is pre-processed and log2 transformed. I would like to perform the analysis combining all data together. I applied limma batcheffect removal method, however,…
Genetic risk converges on regulatory networks mediating early type 2 diabetes
Kahn, S. E., Hull, R. L. & Utzschneider, K. M. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 444, 840–846 (2006). Article ADS PubMed Google Scholar Halban, P. A. et al. β-cell failure in type 2 diabetes: postulated mechanisms and prospects for prevention and treatment. Diabetes Care…
using RMA normalized microarray in Limma
using RMA normalized microarray in Limma 0 Hi, i downloaded raw.tar file containing .CEL microarray data from GEO database. and then i use affy() package in R to extracted .CEL file and normalized with RMA(). Can i use this expression data to put in Limma? or it is better to…
Comprehensive analysis of necroptotic patterns and associated immune landscapes in individualized treatment of skin cutaneous melanoma
Identification of the SKCM necroptosis cluster The comprehensive analysis encompassed a total of 803 patients drawn from five distinct melanoma cohorts, namely, TCGA-SKCM, GSE65094, GSE53118, GSE54467, and GSE19234. Employing an unsupervised clustering algorithm, we stratified melanoma patients based on their NRG expression profiles. This facilitated a deeper exploration of the…
Can I use TCGA-LUAD RNAseq count that had already normalized by RSEM in Limma-voom
Can I use TCGA-LUAD RNAseq count that had already normalized by RSEM in Limma-voom 0 Hi everyone, first of all, I’m new for bioinformatics. I have downloaded RNAseq data of TCGA-LUAD from UCSC that had already normalized RSEM normalized count and log2 transformed (log2 normcount+1). i wonder if i can…
Bioconductor – limma
Linear Models for Microarray Data Bioconductor version: 2.5 Data analysis, linear models and differential expression for microarray data. Author: Gordon Smyth with contributions from Matthew Ritchie, Jeremy Silver, James Wettenhall, Natalie Thorne, Mette Langaas, Egil Ferkingstad, Marcus Davy, Francois Pepin, Dongseok Choi, Di Wu, Alicia Oshlack, Carolyn de Graaf, Yifang…
Is it appropriate to apply linear mixed models to Voom transformed data?
Is it appropriate to apply linear mixed models to Voom transformed data? 1 @4b83ad99 Last seen 18 hours ago Canada Hello, I have some gene expression data for different tissue types with multiple replicates. My species has undergone a historical duplication event and and I am looking to compare the…
Chromatin priming elements direct tissue-specific gene activity before hematopoietic specification
Introduction The development of multicellular organisms requires the activation of different gene batteries which specify the identity of each individual cell type. Such shifts in cellular identity are driven by shifts in the gene regulatory network (GRN) consisting of transcription factors (TFs) binding to the enhancers and promoters of their…
Limma/DESeq2 for unbalanced nested design (paired samples)
I have an RNAseq dataset that I want to perform differential gene-expression analysis on. The dataset consists of 3 groups = macrophages deriving from adults (n=6), term-born infants (n=5), and preterm infants (n=3). Each sample has been treated with an immune-stimulus, or left untreated (paired samples). Group Treatment Sample_Nr Sample_within_group…
Analysis of nucleoporin 107 overexpression
Introduction Lung cancer is one of the most common types of cancer worldwide and the leading cause of cancer death.1 The main category of lung cancer is non-small cell lung cancer, accounting for about 85%, and lung adenocarcinoma, as a kind of non-small cell lung cancer, is the most frequently…
MAJOR Computational Biology Research Lab
MAJOR Computational Biology Research Lab (MCBRL) uses computer science algorithms to solve biology related problems, bioinformatics software development and develop bioinformatics cloud computing platforms or services for handling and analyzing large-scale biological data.. The workflow of hdWGCNA analysis for Single-cell Spatial Transcriptomics data RNA-seq Schematicsc/nRNA-seq Schematic ” RNA-seq Schematic 空间转录共表达网络分析流程…
Predicting missing values splines DESeq2
Hello, I am fitting splines in DESeq2 like so: dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata, design = ~ ns(age_scaled, df = 3)) Plotting later using the code Mike Love posted elsewhere: dat <- plotCounts(dds, gene, intgroup = c(“age”, “sex”, “genotype”), returnData = TRUE) %>% mutate(logmu = design_mat %*%…
Transgenerational epigenetic effects imposed by neonicotinoid thiacloprid exposure
This study is aimed at revealing the transgenerational effects of thia. We chose the developmental window from embryonic days 6.5 to E15.5 because of its importance in germ cell program establishment. The mice breeding was described in the Materials and Methods section “Mouse treatment and dissection.” The design of the…
Bioconductor – dreamlet
DOI: 10.18129/B9.bioc.dreamlet Cohort-scale differential expression analysis of single cell data using linear (mixed) models Bioconductor version: Release (3.18) Recent advances in single cell/nucleus transcriptomic technology has enabled collection of cohort-scale datasets to study cell type specific gene expression differences associated disease state, stimulus, and genetic regulation. The scale of…
Bioconductor – CountClust
DOI: 10.18129/B9.bioc.CountClust This package is for version 3.10 of Bioconductor; for the stable, up-to-date release version, see CountClust. Clustering and Visualizing RNA-Seq Expression Data using Grade of Membership Models Bioconductor version: 3.10 Fits grade of membership models (GoM, also known as admixture models) to cluster RNA-seq gene expression…
Bioconductor – Category
This package is for version 2.14 of Bioconductor; for the stable, up-to-date release version, see Category. Category Analysis Bioconductor version: 2.14 A collection of tools for performing category analysis. Author: R. Gentleman with contributions from S. Falcon and D.Sarkar Maintainer: Bioconductor Package Maintainer <maintainer at bioconductor.org> Citation (from…
Bioconductor – TCGAbiolinks
DOI: 10.18129/B9.bioc.TCGAbiolinks TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data Bioconductor version: Release (3.5) The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses…
Bioconductor – rtracklayer
DOI: 10.18129/B9.bioc.rtracklayer R interface to genome annotation files and the UCSC genome browser Bioconductor version: Release (3.6) Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may…
Bioconductor – iCOBRA
DOI: 10.18129/B9.bioc.iCOBRA Comparison and Visualization of Ranking and Assignment Methods Bioconductor version: Release (3.6) This package provides functions for calculation and visualization of performance metrics for evaluation of ranking and binary classification (assignment) methods. It also contains a shiny application for interactive exploration of results. Author: Charlotte Soneson…
How will you perform batch correction in DESeq2 when you don’t have any group information?
How will you perform batch correction in DESeq2 when you don’t have any group information? 1 I have 500 tumor samples collected at 5 batches. My samples don’t have any groups. How will I do the batch correction. Is the step below correct? #Expression data counts = read.table(“tumor.unstranded.txt”, sep=”\t”, header…
Any one familiar with IP-MS data analysis?
Any one familiar with IP-MS data analysis? 0 I have a dataset from an IP-MS experiment. In the excel, I have the spectral counts for “pre clear” (as background) in addition to the spectral counts for prey proteins. I assume to perform DE analysis, I need to substract “pre-clear” counts…
Microarray data analysis with and without contrast
I have 6 samples of control and test condition normalized microarray intensities which Im using a starting point of my analysis. This is my basic analysis code library(readxl) library(dplyr) library(tidyverse) library(limma) # t # Create a data frame with the sample names and group names metdata <- data.frame( SampleName =…
Differential Gene Expression between patients and not groups
Differential Gene Expression between patients and not groups 0 Hello, Is there any way to instead of doing differential gene expression between groups of interest do between patients? Let’s say i have a subgroup of patients of a disease called LMS/NOS composed by 102 patients having high heterogeneity. I want…
Differential Expression Analysis using Bioconductor (RStudio) and GEO2R (GEO)
Hello everyone, I’ve been having the same question for a while now. I’m also conducting my own analysis of differential expression on a microarray dataset in R. However, the data is different from the results obtained using GEO2R. Here’s my line of code: my_id <- “GSE80178” gse <- getGEO(my_id, GSEMatrix…
ncRNA | Free Full-Text | Downregulation of Exosomal hsa-miR-551b-3p in Obesity and Its Link to Type 2 Diabetes Mellitus
Non-Coding RNA 2023, 9(6), 67; doi.org/10.3390/ncrna9060067 (registering DOI) Non-Coding RNA 2023, 9(6), 67; doi.org/10.3390/ncrna9060067 (registering DOI) Received: 31 August 2023 / Revised: 6 October 2023 / Accepted: 24 October 2023 / Published: 2 November 2023 Round 1 Reviewer 1 Report Comments and Suggestions for Authors The study by Kseniia V. Dracheva and…
Insights into expression patterns and immunotherapy response prediction
[1] D. Schadendorf, D. E. Fisher, C. Garbe, J. E. Gershenwald, J. Grob, A. Halpern, et al., Melanoma, Nat. Rev. Dis. Primers, 1 (2015), 15003. doi.org/10.1038/nrdp.2015.3 doi: 10.1038/nrdp.2015.3 [2] A. M. M. Eggermont, A. Spatz, C….
Illumina HumanHT-12 V4.0 expression beadchip
Illumina HumanHT-12 V4.0 expression beadchip 2 I’m quite new to the bioinformatics world and just started working with the GEO data set GSE119600. My intention is to extract deferentially expressed genes and will start my work using the Lumi package to import ,read and normalize the raw data into R….
What are some of the Python libraries and packages that can perform similar tasks to DESeq2, edgeR, and limma-voom?
Python offers several libraries and packages that can perform similar tasks to DESeq2, edgeR, and limma-voom. One such library is numpy, which provides efficient numerical operations for handling large datasets. Another library is scipy, which offers sparse matrix support and linear algebra routines for solving boundary value problems and partial…
How to install or uninstall “r-bioc-drimseq” on Linux Mint 21 “Vanessa” ?
1. Install r-bioc-drimseq package This guide let you learn how to install r-bioc-drimseq package: sudo apt install r-bioc-drimseq Copy 2. Uninstall / Remove r-bioc-drimseq package Please follow the guidance below to uninstall r-bioc-drimseq package: sudo apt remove r-bioc-drimseq Copy sudo apt autoclean && sudo apt autoremove Copy 3. Details of…
Error in Gviz (actually, rtracklayer)
Error in Gviz (actually, rtracklayer) | IdeogramTrack 0 @25075190 Last seen 7 minutes ago South Korea When I run this code (below) iTrack <- IdeogramTrack(genome = “hg19”, chromosome = “chr2”, name = “”) then I get the error Error: failed to load external entity “http://genome.ucsc.edu/FAQ/FAQreleases” Did someone else encounter this…
Analysis and results microarray data for research
Analysis and results microarray data for research 0 Hello everyone, I am analyzing microarray and RNA-seq data in patients with diabetic foot ulcers for my research. I am an undergraduate student, and my group doesn’t have much experience with these types of analyses. I would like to receive some tips…
R packages for DNA methylation as mediator analysis
R packages for DNA methylation as mediator analysis 0 Hi, I do have diabetes and no diabetes disease phenotypes, and also arsenic exposure and DNA methylation data (epic array). Could you please suggest best way to find CpG sites associated with arsenic exposure and diabetes. We know that toxic element…
FPKM values for DE analysis
FPKM values for DE analysis – Why? 1 Hello everyone! I believe my questions are quite naive, but I am super new to RNA-seq data analysis, so forgive me! I already saw some questions regarding this subject, but I still do not understand it well. I am currently performing (trying…
Fisher exact test on different gene sets
Fisher exact test on different gene sets 0 Hey everyone! I am working on a project exploring the role of one exact transcriptional factor on the acquired chemoresistance. I have Illumina transcriptome data, which has been proceeded with DESeq2 to find differentially expressed genes, and the resulting table containing only…
Calculating p-value and adjusted p-value for pre-normalized microarray data with fold change precalculated
Calculating p-value and adjusted p-value for pre-normalized microarray data with fold change precalculated 1 I have a microarray dataset with two mutants dataset that has already been normalised, and the fold change values for each gene in each mutant versus the wild type have been calculated. I’m interested in determining…
Bioconductor – Rvisdiff
DOI: 10.18129/B9.bioc.Rvisdiff Interactive Graphs for Differential Expression Bioconductor version: Release (3.18) Creates a muti-graph web page which allows the interactive exploration of differential expression results. The graphical web interface presents results as a table which is integrated with five interactive graphs: MA-plot, volcano plot, box plot, lines plot and…
Bioconductor – lemur
DOI: 10.18129/B9.bioc.lemur Latent Embedding Multivariate Regression Bioconductor version: Release (3.18) Fit a latent embedding multivariate regression (LEMUR) model to multi-condition single-cell data. The model provides a parametric description of single-cell data measured with complex experimental designs. The parametric model is used to (1) align conditions, (2) predict log fold…
Bioconductor – gg4way
DOI: 10.18129/B9.bioc.gg4way 4way Plots of Differential Expression Bioconductor version: Release (3.18) 4way plots enable a comparison of the logFC values from two contrasts of differential gene expression. The gg4way package creates 4way plots using the ggplot2 framework and supports popular Bioconductor objects. The package also provides information about the…
How to correct for known and surrogate variables in DESeq2?
Dear all, We have RNA-seq data of 9 High force versus 9 Low force scallop adductors along with known covariates like Height, Length, Width, Weight (I have cut() them )and Strain. So in DESeq2 I could correct for these covariates as follows: #We only chose Height, Weight and Strain as…
Bioinformatic Analysis of circRNAs in Human ASO
Introduction Arteriosclerosis obliterans (ASO) is a chronic disorder with atherosclerosis involving lower extremity arteries leading to arterial stenosis or occlusion. The incidence continues to increase with age, affecting about 202 million people worldwide to varying degree.1–3 Despite the proposed theories of lipid infiltration, arterial intimal injury, and chronic inflammation, the…
Analyzing contributions to DEG signature
I am trying to perform an analysis that I’ve not seen others done and would like some guidance. I ran a DEG analysis comparing populations A and B. I account for batch effects by incorporating the batch as a covariate in the design formula, eg: ~batch + group I have…
Matrix not full rank – IDs distinct within group
Matrix not full rank – IDs distinct within group 0 I have expression data with two conditions. There are 10 IDs in condition A with two replicates total per ID (same animal). There are 20 IDs in condition B with two replicates per ID. I want to test condition A…
Combining Microarray and RNAseq data
Combining Microarray and RNAseq data 5 Hi, I want to combine RNAseq and microarray data of samples, and do clustering analysis. I don’t want to comparison between these techniques but merge them and analyze.I came across this post but this mentions comparison of these techniques: Combined Rnaseq + Microarray Transcriptomics…
Error creating SPIA data for KEGG Orthology (KO) Database KEGG xml files
Hi all, I’m trying to create a SPIA data file for all 483 xml files for the KEGG Orthology (KO) Database. I’m working with a non-model organism that is not supported by KEGG as it’s own organism, so I have to use the KEGG Orthology (KO) Database instead of a…
Plotting time series data after running natural splines regression in DESeq2.
Hello, I am running differential expression analysis on age-related changes in transcription using natural splines with DESeq2 like so: dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata, design = ~ ns(age_scaled, df = 3)) keep <- rowSums(counts(dds) >= 10) >= 3 dds <- dds[keep,] dds <- DESeq(dds, test=”LRT”, reduced =…
DE analysis in paired samples with limma
Hello! I am interested in doing DE analysis in 12 samples from 3 different patients (“id”). The samples have been sequenced using bulk RNA-seq in a specific group of isolated cells. I have treated the cells by doing a knock-out experiment to remove a gene (group1 as mutated “MUT” and…
Bioconductor – subSeq
DOI: 10.18129/B9.bioc.subSeq This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see subSeq. Subsampling of high-throughput sequencing count data Bioconductor version: 3.9 Subsampling of high throughput sequencing count data for use in experiment design and analysis. Author: David Robinson, John D. Storey, with…
Crohn’s Disease treatment after failure of anti-TNF therapy
Introduction Crohn’s Disease (CD) is a typical group of inflammatory bowel disease, a chronic intestinal disease with an unclear cause that fluctuates between clinical remission and relapse. The disease may affect the entirety of the gastrointestinal tract, frequently manifesting as segmental, asymmetric, and transmural lesions. 21–47% of patients present with…
using technical replicates for batch bridging of illumina epic methylation data
using technical replicates for batch bridging of illumina epic methylation data 0 Hey, I have Illumina EPIC methylation data of about 500 samples measured in 9 batches including 25 pairs of technical replicates across different batches. Can someone help how to best use these measurements for bridging between the batches…
R encountered fatal error when using processBismarkAln in methylKit
R encountered fatal error when using processBismarkAln in methylKit 2 Hi I am attempting to use methylkit to analyse my RRBS data but cannot seem to be able to import my files. I have .bam files generated from bismark. I read I can use function processBismarkAln to read these kind…
Bioconductor – TimeSeriesExperiment
DOI: 10.18129/B9.bioc.TimeSeriesExperiment Analysis for short time-series data Bioconductor version: Release (3.11) Visualization and analysis toolbox for short time course data which includes dimensionality reduction, clustering, two-sample differential expression testing and gene ranking techniques. The package also provides methods for retrieving enriched pathways. Author: Lan Huong Nguyen Maintainer: Lan…
Signatures of necroptosis-related genes as diagnostic markers of endometriosis and their correlation with immune infiltration | BMC Women’s Health
Technical roadmap Figure 1. Fig. 1 Analysis of endometriosis-related differentially expressed genes Using the limma package, we first normalized the expression profile data of the endometriosis datasets, GSE7305 and GSE11691. The data distribution before and after standardized treatment is revealed in a box plot (Figs. 2A–D). We found that the data after…
The mutational signature of hypertrophic cardiomyopathy
Introduction Hypertrophic cardiomyopathy (HCM), characterized by asymmetric hypertrophy of the ventricular wall, is a condition where the heart becomes thickened without a distinct inducement.1,2 Epidemiological investigation shows that the estimated prevalence rate of HCM in the general population is 1:500.3,4 The clinical manifestations vary greatly, with no symptoms and mild…
DuplicateCorrelation() block by duplicate sample or by cell line ?
I have Bulk-RNAseq data from 3 drug exposures (vehicle, low and high dose) x 2 replicates per condition x 6 cell lines. So its a total of 36 samples. I am interested in the Exposure effect. I am using DuplicateCorrelation and limma voom, but my cell Line effect is eating…
The Biostar Herald for Monday, October 09, 2023
Herald:The Biostar Herald for Monday, October 09, 2023 0 The Biostar Herald publishes user submitted links of bioinformatics relevance. It aims to provide a summary of interesting and relevant information you may have missed. You too can submit links here. This edition of the Herald was brought to you by…
DiffBind dba.count() crash/can’t finish problems
I am using Diffbind for an ATAC-Seq analysis. My peak caller is MACS2, and here is my sample sheet: I run Diffbind with the following codes, but it crashed every time on dba.count . it can finished Computing summits… Recentering peaks… Reads will be counted as Paired-end. But have this…
US Tech Solutions hiring Bioinformatics Scientist in United States
Title: Bioinformatics Scientist Job type: Contract Duration: 06+ Months Client’s Location: Remote Job Description: We are seeking a highly skilled and motivated contractor to join the Genomics Research Center and provide support for bioinformatics projects in the field of Ophthalmology and Specialty Medicine. As a contractor, you will collaborate with…
DeSeq2 data comparison and extracting outputs
Hi, I have an RNA-seq experiment where there are 2 conditions and 2 genotypes. I am trying to figure out how to output the 2 conditions with 2 genotypes from the dds object. I have read online resources, however, it is still not clear what is extracted. I followed and…
Index of /~psgendb/birchhomedir/public_html/doc/local/pkg/MeV_4_8_0/documentation/manual
Name Last modified Size Description Parent Directory – 2anova1.jpg 2011-09-09 05:55 121K 4.3.1.jpg 2011-09-09 05:55 117K 4.4.1.jpg 2011-09-09 05:55 63K 4.6.1.jpg 2011-09-09 05:55 38K 4.7.1.jpg 2011-09-09 05:55 56K 4.10.1.jpg 2011-09-09 05:55 63K 4.11.1.jpg 2011-09-09 05:55 112K 4.12.1.jpg 2011-09-09 05:55 55K …
Histone regulator KAT2A acts as a potential biomarker related to tumor microenvironment and prognosis of diffuse large B cell lymphoma | BMC Cancer
Zhang Y, Tan H, Daniels JD, Zandkarimi F, Liu H, Brown LM, et al. Imidazole Ketone Erastin induces ferroptosis and slows Tumor Growth in a mouse lymphoma model. Cell Chem Biol. 2019;26(5):623–33e9. Article CAS PubMed PubMed Central Google Scholar Hartert KT, Wenzl K, Krull JE, Manske M, Sarangi V, Asmann…
DMRcate design
Hi all, I am trying to use DMRcate first time for epic array data. I have done the limma association analysis using below model design but not sure how to design model metrix for DMRcate for same type of BMI and CpG sites association analysis; Could you help me if…
A subpopulation of lipogenic brown adipocytes drives thermogenic memory
Farber, D. L., Netea, M. G., Radbruch, A., Rajewsky, K. & Zinkernagel, R. M. Immunological memory: lessons from the past and a look to the future. Nat. Rev. Immunol. 16, 124–128 (2016). Article PubMed Google Scholar Netea, M. G. et al. Defining trained immunity and its role in health and…
Large fold change when analyzing expression profiling from microarray
Large fold change when analyzing expression profiling from microarray 0 Hi, dear all. I am trying to analyze a expression profiling dataset from GEO, which was detected by Affymetrix microarray. Its data processing method was described as “The data were analyzed with Microarray Suite GCOS using Affymetrix default analysis settings…
Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
Samples for H3K27ac ChIP–seq Samples were collected by the GTEx Consortium. The donor enrollment and consent, informed consent approval, histopathological review procedures, and biospecimen procurement methods and fixation were the same as previously described22. No compensation was provided to the families of participants. Massachusetts Institute of Technology Committee on the…
TPM RNA-seq data for differential expression analysis
TPM RNA-seq data for differential expression analysis 1 Hello. I have a project where I need to identify differences in gene expression between two categories of cancer patients: low and high survival rate. I am retrieving RNA seq data from the Cancer Genome Atlas TCGA, but I can only find…
Convert from limma voom normalized matrix each gene to high/low
Convert from limma voom normalized matrix each gene to high/low 0 I did the limma voom pipeline to normalize the expression using quantile normalization. I want to discretize the expression of each gene into “high” or “low”. This is my current approach: table <- data.frame(row.names = names, pvalue = numeric(length(names)))…
Complex multifactorial DE analysis with limma/edgeR based on rnaseq data
Dear Biostars, I would like to ask you one specific question regarding the DE analysis on an RNASeq dataset of samples, spanning a multi-factor experimental design. Briefly, unstimulated neutrophils of 4 healthy donors, were cultivated with distinct treatment conditions-that is, supernatant of organoids from different cancer/normal patient samples; There are…
Frustrated with DEA results
Hello! I am currently analyzing some data that was provided to me. It consists of more than 150 microarray samples from a single kind of tumor. The data is already normalized and background corrected, and in theory I should be able to find differences in gene expression among patients that…
Bioconductor – GWAS.BAYES
DOI: 10.18129/B9.bioc.GWAS.BAYES Bayesian analysis of Gaussian GWAS data Bioconductor version: Release (3.17) This package is built to perform GWAS analysis using Bayesian techniques. Currently, GWAS.BAYES has functionality for the implementation of BICOSS for Gaussian phenotypes (Williams, J., Ferreira, M. A., and Ji, T. (2022). BICOSS: Bayesian iterative conditional stochastic…
Batch effect normalization
Batch effect normalization 0 hello people! my rna seq data has been sequenced in 5 batches. upon applying MW stats, i found signifcance for orimary aligned readcounts between batches. since the data is for severity, i compared mild of batch 1 with mild of another batch and likewise for mod…
Bioconductor – Linnorm
DOI: 10.18129/B9.bioc.Linnorm This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see Linnorm. Linear model and normality based normalization and transformation method (Linnorm) Bioconductor version: 3.16 Linnorm is an algorithm for normalizing and transforming RNA-seq, single cell RNA-seq, ChIP-seq count data or any large…
Bioconductor – Rnits
DOI: 10.18129/B9.bioc.Rnits This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see Rnits. R Normalization and Inference of Time Series data Bioconductor version: 3.16 R/Bioconductor package for normalization, curve registration and inference in time course gene expression data. Author: Dipen P. Sangurdekar <dipen.sangurdekar at…
Paired ATAC- and RNA-seq offer insight into the impact of HIV on alveolar macrophages: a pilot study
Fitzpatrick, M. E., Kunisaki, K. M. & Morris, A. Pulmonary disease in HIV-infected adults in the era of antiretroviral therapy. AIDS 32, 277–292. doi.org/10.1097/qad.0000000000001712 (2018). Article PubMed Google Scholar Brown, J. & Lipman, M. Community-acquired pneumonia in HIV-Infected individuals. Curr. Infect. Dis. Rep. 16, 397. doi.org/10.1007/s11908-014-0397-x (2014). Article PubMed PubMed…
Bioconductor – zFPKM
DOI: 10.18129/B9.bioc.zFPKM This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see zFPKM. A suite of functions to facilitate zFPKM transformations Bioconductor version: 3.16 Perform the zFPKM transform on RNA-seq FPKM data. This algorithm is based on the publication by Hart et al., 2013…
Somatic SLC30A1 mutations altering zinc transporter ZnT1 cause aldosterone-producing adenomas and primary aldosteronism
Young, W. F. Primary aldosteronism: renaissance of a syndrome. Clin. Endocrinol. 66, 607–618 (2007). Article CAS Google Scholar Rossi, G. P. et al. A prospective study of the prevalence of primary aldosteronism in 1,125 hypertensive patients. J. Am. Coll. Cardiol. 48, 2293–2300 (2006). Article CAS PubMed Google Scholar Fardella, C….
Use limma for correlation analysis of RNA-seqdata and continous trait
Use limma for correlation analysis of RNA-seqdata and continous trait 1 Hi, there I want to use voom function in limma package to analyze the correlations between expression and age(continous data). I am not sure whether it is suitable to use this package, which is often used for binary data….
Molecular control of endurance training adaptation in male mouse skeletal muscle
A surprisingly low number of genes define the trained muscle To study differences between untrained and endurance-trained muscles (in the present study, muscle always refers to quadriceps), mice were exercised by treadmill running on 5 d per week for 1 h. After 4 weeks, a significant improvement in running performance was observed (Extended…
BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures
Jonsson, A. L. & Bäckhed, F. Role of gut microbiota in atherosclerosis. Nat. Rev. Cardiol. 14, 79–87 (2017). CAS PubMed Google Scholar Tang, W. H. W., Kitai, T. & Hazen, S. L. Gut microbiota in cardiovascular health and disease. Circ. Res. 120, 1183–1196 (2017). CAS PubMed PubMed Central Google Scholar …
RNA-sequencing and bioinformatics analysis | COPD
Introduction COPD, a common preventable and treatable disease characterized by persistent airflow limitation and respiratory symptoms, is associated with exposure to harmful environments. COPD is currently the third leading cause of death globally. The high incidence and mortality of COPD, which seriously threaten human health, represent a public health problem…
CCDC50, an essential driver involved in tumorigenesis, is a potential severity marker of diffuse large B cell lymphoma
Data collection and bioinformatic analysis GSE10846, GSE19246, GSE32918, GSE50721, GSE64820, and GSE94669, were downloaded from the Gene Expression Omnibus database (www.ncbi.nlm.nih.gov/geo/). DLBCL datasets from the GEPIA (Gene Expression Profiling Interactive Analysis) (gepia.cancer-pku.cn) and the TCGA (The Cancer Genome Atlas) (xenabrowser.net/datapages/) were also used in this study. A total of 284…
TCGAbiolinks not working anymore
TCGAbiolinks not working anymore 0 The script in this tutorial does not work anymore bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/analysis.html I get to GDCprepare stage and get error: Starting to add information to samples => Add clinical information to samples => Adding TCGA molecular information from marker papers => Information will have prefix paper_ brca…
Top 25 Bioconductor Interview Questions and Answers
Bioconductor is an open-source software project that provides tools for the analysis and comprehension of high-throughput genomic data. It’s a powerful tool, widely used in bioinformatics and computational biology to process and analyze intricate biological data. Bioconductor’s strength lies in its vast array of packages specifically tailored for genomics research,…
Consensus Cluster takes normalized gene counts or raw gene counts?
Hi! I am using package ConsensusClusterPlus in R to discover the optimal number of gene expression clusters. Following the steps [note: the code is pseudocode, just to help the understanding]: 1 Get the RNA SEQ data (rows: genes, cols: samples/patients) 2 Keep only the top 30% Most Variable Genes by…
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…
Bioconductor – POWSC
DOI: 10.18129/B9.bioc.POWSC Simulation, power evaluation, and sample size recommendation for single cell RNA-seq Bioconductor version: Release (3.17) Determining the sample size for adequate power to detect statistical significance is a crucial step at the design stage for high-throughput experiments. Even though a number of methods and tools are available…
Integrated unbiased multiomics defines disease-independent placental clusters in common obstetrical syndromes | BMC Medicine
Barker DJ. The origins of the developmental origins theory. J Intern Med. 2007;261:412–7. Article CAS PubMed Google Scholar Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life. Lancet. 1993;341:938–41. Article CAS PubMed Google Scholar Cain MA, Salemi JL, Tanner…