Tag: LIMMA

Acute lung injury (ALI) is a severe form of sepsis that is associated with a high rate of morbidity and death in critically ill individuals. The emergence of ALI is the result of several factors at work. Case mortality rates might range from 40% to 70%. Researchers have discovered that…

Difference in number of DEGs from Deseq2 and limma-voom 0 Hello, I have RNA-seq data from two different treatment groups (F and NF ) at 2 different time points (T1 and T2). The mapping was done with STAR aligner and the quantification was done with FeatureCounts. I run differential expression…

exact counts tables for limma voom guide 1 Is there a way to download the exact counts table associated with the limma voom guide? specifically for the tutorial in chapter 15 of the limma voom guide (GSE64099). I would like to to run through the commands and recreate the plots…

Limma voom with missing values from mass spectrometry 1 Hi everyone. Firstly thank you in advance for any help you can give, I am new to working with mass spec data and biostars has been immensely helpful. I data from three technical repeats and three biological repeats (9 Controls, 9…

How to regress out age and sex using limma removeBatchEffect 1 I have a protein expression data frame with a metadata data frame which includes age and sex: nph_csf_metadata = age sex bam tau 70 f 5 2 75 m 6 1 72 m 4 1 71 f 4 2…

This might be a bit long, please bare with me. I’m conducting a differential expression analysis using limma – voom. My comparison is regarding response vs non-response to a cancer drug. However, I’m not getting any DE genes, absolute zeros. Someone here once recommended not to use contrast matrix for…

R: MA-Plot plotMA {limma} R Documentation MA-Plot Description Creates an MA-plot with color coding for control spots. Usage plotMA(MA, array=1, xlab=”A”, ylab=”M”, main=colnames(MA)[array], xlim=NULL, ylim=NULL, status, values, pch, col, cex, legend=TRUE, zero.weights=FALSE, …) Arguments MA an RGList, MAList or MArrayLM object, or any list with components M containing log-ratios and…

Dear Community, I am still wrestling with limma, trying to apply it to my metabolomics data. The main problem is the fact that, with my data, limma produces produces false positives, i.e. significant p-values when they clearly should not be significant. I already had a very similar problem, which could…

Dear Bioc, Following the rtracklayer documentation, section 2.2.4, ‘A Shortcut’, I encounter the following error browseGenome (subTargetTrack) Error in validObject(.Object) :invalid class “ucscCart” object: superclass “ANYTHING” not defined in the environment of the object’s class traceback () 13: stop(msg, ” “, errors, domain = NA)12: validObject(.Object)11: initialize(value, …)10: initialize(value, …)9:…

tReasure (tRNA Expression Analysis Software Utilizing R for Easy use) is a graphical user interface (GUI) tool for the analysis of tRNA expression profiles from deep-sequencing data of small RNAs (small RNA-seq) using R packages. The whole analysis workflow, including the uploading of FASTQ files of small RNA-seq, quantification of…

I am trying to take the “difference of differences” in contrasts from two factors (sex and group). We have male and female animals (sex factor) that were untrained or trained for 1, 2, 4, or 8 weeks (group factor, i.e., “control”, “1w”, “2w”, “4w”, “8w”). I want to know the…

I have installed DESeq2 version 1.36.0 samples <- colnames(txi$counts) group <- as.factor(c(“control”,”control”,”control”,”control”,”control”,”diet”,”diet”,”diet”,”diet”,”diet”, “control”,”control”,”control”,”control”,”control”,”diet”,”diet”,”diet”,”diet”,”diet”,”diet”)) coldata <- data.frame(samples, group, stringsAsFactors = F) coldata <- coldata[,c(“samples”,”group”)] coldata$samples <- factor(coldata$samples) coldata$group <- factor(coldata$group) rownames(coldata) <- sub(“fb”, “”, rownames(coldata)) all(rownames(coldata$samples) %in% colnames(txi)) all(rownames(coldata) == colnames(txi)) TRUE library(DESeq2) ddsTxi <- DESeqDataSetFromTximport(txi, colData = coldata, design =…

Annotated file with gene ID (instead of gene symbol) 0 @9cb59de3 Last seen 14 hours ago United States Hello, I am using “featureCounts” in Rsubread package for analyzing bulk RNA-seq of drosophila. Since there is no inbuilt annotations of drosophila, I am using a gtf file in the homepage of…

Hi, I am working with a dataframe in R containing the quantitative data and trying to plot a volcano plot using library(EnhancedVolcano) package. I am currently analyzing by subsetting based on corresponding matching pairs of “Coef” and “P.value” obtained from limma (for instance; Coef.HC_6h_vs_0h and P.value.HC_6h_vs_0h) individually and export the…

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…

Introduction Lung cancer is the major leading cause of tumour-related deaths throughout the world, while lung squamous cell carcinoma (LUSC) as the second most common histological type of lung cancer.1 Each year, almost 1.8 million people are diagnosed with lung cancer worldwide and 400,000 of these die from LUSC.2,3 Due to…

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,…

GDCprepare of RNAseq counts produces error 1 @76ac7b25 Last seen 12 minutes ago Canada Hello everyone! I have been using the TCGAbiolinks package for the last couple years to access RNAseq data for the TCGA-LAML project. Just very recently, I had noticed that I could no longer use GDCquery to…

Dear friends, We are trying to use Salmon for DTU analysis. We want to separate exogenous from endogenous transcripts by following this post www.biostars.org/p/443701/ and this paper f1000research.com/articles/7-952 We are focusing on a gene called ASCL1 (endo-ASCL1). We transduced cells with lentiviral vector containing ASCL1 ORF only (Lenti-ASCL1). There should…

GDCquery_Maf error 0 @76e1237b Last seen 1 day ago Singapore Hi all, I really need some help. I am trying to run GDCquery_Maf which worked fine until yesterday. Now I get the following error: Error in GDCquery(paste0(“TCGA-“, tumor), data.category = “Simple Nucleotide Variation”, : Please set a valid workflow.type argument…

Background: The application of RNA-seq technology has become more extensive and the number of analysis procedures available has increased over the past years. Selecting an appropriate workflow has become an important issue for researchers in the field. Methods: In our study, six popular analytical procedures/pipeline were compared using four RNA-seq…

Rawla, P., Sunkara, T., Muralidharan, P. & Raj, J. P. Update in global trends and aetiology of hepatocellular carcinoma. Contemp. Oncol. (Poznan, Poland) 22, 141–150 (2018). CAS  Google Scholar  Kong, D. et al. Current statuses of molecular targeted and immune checkpoint therapies in hepatocellular carcinoma. Am. J. Cancer Res. 10,…

When I try to install the gtf for hg38 BiocManager::install(“TxDb.Hsapiens.UCSC.hg38.knownGene”) I get the following error: ‘getOption(“repos”)’ replaces Bioconductor standard repositories, see ‘?repositories’ for details replacement repositories: CRAN: cran.rstudio.com/ Bioconductor version 3.14 (BiocManager 1.30.16), R 4.1.2 (2021-11-01) Installing package(s) ‘TxDb.Hsapiens.UCSC.hg38.knownGene’ Error in readRDS(dest) : error reading from connection Per stackoverflow.com/questions/67455984/getoptionrepos-replaces-bioconductor-standard-repositories-see-reposito I…

Hello, I have finished the RNA seq analysis and I am trying to perform some pathway analysis. I have used the gage package and I was looking online about another package called goseq that takes into account length bias. However, when I run the code I get an error. How…

Processing Illumina HumanHT-12 V4.0 data without detection p-values 1 Hello, I want to pre-process GSE17048 dataset from GEO. I followed the steps provided by Kevin in this post but I realized that neqc from limma requires the detection p-values of each probe for normalizing the data. I wanted to know…

DOI: 10.18129/B9.bioc.GeuvadisTranscriptExpr     This package is for version 3.8 of Bioconductor; for the stable, up-to-date release version, see GeuvadisTranscriptExpr. Data package with transcript expression and bi-allelic genotypes from the GEUVADIS project Bioconductor version: 3.8 Provides transcript expression and bi-allelic genotypes corresponding to the chromosome 19 for CEU individuals from…

Introduction Chronic obstructive pulmonary disease (COPD) will become the third leading cause of death worldwide.1,2 The incidence of COPD worldwide is 13.1%3 and is 13.7% in the Chinese population over 40 years of age.4 Emphysema is one of the most common phenotypes.1 Over the past few decades, we have conducted…

Introduction Acute pancreatitis (AP) is a common disease found in clinics, and requires urgent Hospital admission. The incidence of AP is increasing in recent years worldwide.1 The patients with AP increased from 1,727,789.3 to 2,814,972.3 between 1990 and 2019 in 204 countries and territories.2 Meanwhile, nearly 20% of AP patients…

I’m doing a differential expression analysis for RNA-seq data with limma – voom. My data is about a cancer drug, 49 samples in total, some of them are responders some of them are not. I need some help building the contrast. I’m dealing with only one factor here, so two…

Limma Differential Analysis on Proteomics data 1 @3c9b3fdc Last seen 7 hours ago United States Hi, I have a proteomics data set and I am doing the differential analysis on that. I used the Limma package to do that. I first removed the negative counts and did the analysis but…

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…

How to retrieve the batch corrected data frame when using Deseq in R? 1 I have several different RNAseq dataframes that I have merged together; they are from different studies and are raw counts. I want to correct the merged dataframe for study batch effects without getting negative values (I…

Introduction Thyroid carcinoma (THCA) is the most common type of endocrine malignancy and its incidence is increasing.1 Based on its histopathological characteristics, thyroid carcinoma can be classified into multiple subtypes, such as papillary thyroid carcinoma (PTC), follicular thyroid carcinoma, and anaplastic thyroid carcinoma.2 PTC is the most common subtype of…

DOI: 10.18129/B9.bioc.STATegRa     This is the development version of STATegRa; for the stable release version, see STATegRa. Classes and methods for multi-omics data integration Bioconductor version: Development (3.15) Classes and tools for multi-omics data integration. Author: STATegra Consortia Maintainer: David Gomez-Cabrero <david.gomezcabrero at ki.se>, Núria Planell <nuria.planell.picola at navarra.es>…

Hi All, In my analysis, I want to find the different expression genes betweendissese A and B. There are two type of batch effect in my analysis. Iwant to use limma to remove two type of batch effect, one is gender,another is tissue type. I do as fellow. But I…

In R 3.0.2, the following works: At the time of this writing, the value ind can take a vector with values between 1 and 8, and the following meaning: 1: CRAN 2: BioC software 3: BioC annotation 4: BioC experiment 5: BioC extra 6: Omegahat 7: R-Forge 8: rforge.net This…

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…

Defeng Pan,1,&ast; Yufei Zhou,2,&ast; Shengjue Xiao,1,&ast; Yue Hu,3,&ast; Chunyan Huan,1 Qi Wu,1 Xiaotong Wang,1 Qinyuan Pan,1 Jie Liu,1 Hong Zhu1 1Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221004, People’s Republic of China; 2Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of…

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…

DOI: 10.18129/B9.bioc.derfinder     This is the development version of derfinder; for the stable release version, see derfinder. Annotation-agnostic differential expression analysis of RNA-seq data at base-pair resolution via the DER Finder approach Bioconductor version: Development (3.15) This package provides functions for annotation-agnostic differential expression analysis of RNA-seq data. Two…

Hi, I am using EnrichR to analyze my DEGs gotten from limma. I extracted subsets of significant DEGs with their IDs and t-statistics that have been scaled, like the following example: CHI3L1 1.0000000 ARPC1B 0.9605097 SH3D21 0.9303946 FCGBP 0.9165999 MFNG 0.8830144 C2 0.8153162 CTA-398F10.2 0.8459803 CTSD 0.7543101 GRN 0.7503898 CTSB…

DOI: 10.18129/B9.bioc.bnem     This is the development version of bnem; for the stable release version, see bnem. Training of logical models from indirect measurements of perturbation experiments Bioconductor version: Development (3.15) bnem combines the use of indirect measurements of Nested Effects Models (package mnem) with the Boolean networks of…

“Paired-end reads were detected in single-end read library” 0 @9cb59de3 Last seen 12 hours ago United States Hello, I am using “featureCounts” in Rsubread package for analyzing bulk RNA-seq of drosophila. Since there is no inbuilt annotations of drosophila, I am trying to use a gtf file in the homepage…

This article was originally published here BMC Pediatr. 2021 Dec 11;21(1):566. doi: 10.1186/s12887-021-03003-5. ABSTRACT BACKGROUND: Kawasaki disease (KD) is a pediatric inflammatory disorder causes coronary artery complications. The disease overlapping manifestations with a set of symptomatically like diseases such as bacterial and viral infections, juvenile idiopathic arthritis, Henoch-Schönlein purpura, infection…

Introduction According to the cancer statistics reported in 2020, hepatocellular carcinoma (HCC) is the main type of Primary Carcinoma of the Liver and the second leading causes of cancer-related death globally, with a five-year survival rate < 20%.1 Currently, surgical resection, a standard therapy for HCC, contributes to the prognosis…

    This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see MSstats. Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments Bioconductor version: 3.4 A set of tools for statistical relative protein significance analysis in DDA, SRM and DIA…

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…

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…

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))…

Hi! I played around with the Illumina mouse demo data and ENmix. The following code worked for me and you should end up with normalized beta values for subsequent limma analysis (or DMR analysis folowing the ENmix vignette). #setwd() #download the Infinium_Mouse_Methylation_v1.0_A1_GS_Manifest_File.csv file from Illumina HP to working directory (=…

RIP-seq : normalize Input with Immunoprecipitated raw counts or not 0 Hi everyone, I am analyzing a RIP-seq experiment made of 12 RNA libraries as follows : 6 “control” libraries : 3 input (total RNA) and their corresponding immunoprecipitated RNAs (IP) and 6 “affected” libraries : 3 input (total RNA)…

Why there are same name with different value in my microarray result? 0 I have done one color agilent microarray. I am processing my data, but my data showed one miRNA present in more than one place with different value. Could someone please tell me what is the reason for…

How can we compare EdgeR to limma-voom? 0 Hi all, I did all my RNA-seq analysis for 500 patients with the EdgeR workflow as described in the manual. Now I read an article (F1000 research) where they state that EdgeR is mostly preferred in low-count situations, where limma-voom is recommended…

DOI: 10.18129/B9.bioc.Harman     This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see Harman. The removal of batch effects from datasets using a PCA and constrained optimisation based technique Bioconductor version: 3.12 Harman is a PCA and constrained optimisation based technique that maximises the…

limma+voom flips the sign of the effect from CPM? 0 Hello, I’m having a hard time figuring out how limma can switch the sign of an effect compared to the raw cpm or log2(cpm) values. In the figure below, I’m showing 4 genes (2×2 matrix) in our data compared between…

    This package is for version 2.13 of Bioconductor; for the stable, up-to-date release version, see marray. Exploratory analysis for two-color spotted microarray data Bioconductor version: 2.13 Class definitions for two-color spotted microarray data. Fuctions for data input, diagnostic plots, normalization and quality checking. Author: Yee Hwa (Jean) Yang…

voom mean-variance plot has set of genes where variance increases with expression level 0 I’m using limma + voom to model an expression dataset, but I’m observing a weird subset of genes where the standard deviation increases with the expression level rather than decreasing as is the case for most…

Creating Heatmaps Of Diffrentially Expressed Genes In Angilent Single-Color Array Analysis 0 I am using limma to analyze Agilent’s single color arrays to find differentially expressed genes, using the following procedure. targets <- limma::readTargets(“targets.txt”) project <- limma::read.maimages(targets,source=”agilent”, green.only=TRUE) project.bgc <- backgroundCorrect(project, method=”normexp”, offset=50) project.NormData <-normalizeBetweenArrays(project.bgc,method=”quantile”) design <- paste(targets$Target, sep=””) design…

    This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see ChIPComp. Quantitative comparison of multiple ChIP-seq datasets Bioconductor version: 3.4 ChIPComp detects differentially bound sharp binding sites across multiple conditions considering matching control. Author: Hao Wu, Li Chen, Zhaohui S.Qin, Chi Wang Maintainer:…

Introduction Coronary artery disease (CAD) is a complex pathology associated with behavioral and environmental factors.1–3 CAD shows high prevalence and is associated with a high fatality rate among cardiovascular diseases. The main manifestations of CAD are stable or unstable angina pectoris and identifiable or unrecognized myocardial infarction.4 The main risk…

DOI: 10.18129/B9.bioc.Ringo     This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see Ringo. R Investigation of ChIP-chip Oligoarrays Bioconductor version: 3.9 The package Ringo facilitates the primary analysis of ChIP-chip data. The main functionalities of the package are data read-in, quality assessment, data…

Batch correction for DE analysis 0 Hi, I have tried DE analysis using total and mRNA seq data (5 total RNA data and 5 mRNA data) and making the MDS plot in which 5 total RNA data are included in 2 groups (A, B). In the MDS plot, the samples…

DOI: 10.18129/B9.bioc.GEOexplorer     This is the development version of GEOexplorer; to use it, please install the devel version of Bioconductor. GEOexplorer: an R/Bioconductor package for gene expression analysis and visualisation Bioconductor version: Development (3.14) GEOexplorer is a Shiny app that enables exploratory data analysis and differential gene expression of…

Row names and probe names does not match in topTable output 0 Hello I am using limma to analyze differential methylation on a 850k Illumina array, and set up my model as recommended by the user guide. Today I noticed after running topTable() that the rownames in the result data…

DOI: 10.18129/B9.bioc.methylationArrayAnalysis     This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see methylationArrayAnalysis. A cross-package Bioconductor workflow for analysing methylation array data. Bioconductor version: 3.11 Methylation in the human genome is known to be associated with development and disease. The Illumina Infinium methylation…

DOI: 10.18129/B9.bioc.wateRmelon     This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see wateRmelon. Illumina 450 methylation array normalization and metrics Bioconductor version: 3.11 15 flavours of betas and three performance metrics, with methods for objects produced by methylumi and minfi packages. Author: Leonard…

trinity run_DE_analysis.pl Failed with error: ‘package ‘limma’ could not be loaded’ 1 Hi Experts, can someone please help me with this error while running run_DE_analysis.pl for DESeq2 analysis Loading required package: edgeR Loading required package: limma Error: package or namespace load failed for ‘limma’: .onLoad failed in loadNamespace() for ‘limma’,…

Research Officer (Statistical Bioinformatics)Bioinformatics Division, WEHI, Australia An opportunity is available for a Research Officer (Statistical Bioinformatics) to join the Bioinformatics Division at Australia’s pre-eminent biomedical research institute. About the position An exciting opportunity exists for a postdoctoral scientist (Research Officer) to join the research laboratory of Professor Gordon Smyth…

ANOVA for RNA-seq data? 2 Hello I have seem some platforms such as GEPIA offering ANOVA for differential gene expression analysis. However, as far as I’m concerned, ANOVA compares the averages and assumes equal distribution and variance among samples, which, as far I have been lead to assume, is uncommon…

TCGAbiolinks: which normalization before differential expression analysis (legacy=TRUE vs. legacy=FALSE) 1 Dear All, I am following the TCGAbiolinks tutorial for conducting differential expression analysis on TCGA data (“TCGAanalyze: Analyze data from TCGA” section). I have 2 questions about it. 1) I don’t understand the following: when dealing with legacy=TRUE data…

LIMMA 0 Guys can I ask do you know if Limma – Voom from Limma is suitable for microarrays? I know it was developed more for RNA seq but since the base technology is Limma which was originally developed for microarrays do you know if Voom is suitable for Microarrays…

Can you analyze in GEO2R? => No, because this is RNA-seq and not microarrays. You are lucky thought that the authors seem to provide raw counts so you can easily fede them into DESeq2. Here is a code suggestion, for details please read the DESeq2 vignette extensively, it contains answers…

James W. MacDonald 57k 1 week, 5 days ago United States Answer: Biomart’s getBM returns no genes for an existing GO-term in grch38, and less the Michael Love 33k 1 week, 6 days ago United States Answer: Normalizing 5′ Nascent RNA-seq data to identify differentially expressed transcr Kevin Blighe 3.3k 2 weeks, 2 days ago Republic…

Extract log2FC values from volcanoplot() possible? 1 Hello, An MArrayLM object created with eBayes() from the limma package contains the slot $p.values, which I suppose is used by volcanoplot() to make the volcano plot. Since the volcano plot has log2FC in the x-axis, I suppose volcanoplot() also gets the log2FC…

I’m really struggling with this and I need urgent help. I keep running the following code but after the gdcprepare function, it either crashes my computer or freezes the console. I have no idea what to do, someone please help. library(“TCGAbiolinks”, quietly = T) library(“limma”, quietly = T) library(“edgeR”, quietly…

Upon request, a quick tutorial for processing the Agilent micro-RNA (miRNA) microarray data of GSE28955. The raw TXT files are contained in: ftp.ncbi.nlm.nih.gov/geo/series/GSE28nnn/GSE28955/suppl/GSE28955_RAW.tar Download this TAR file Unpack it [the TAR file] Unzip the txt.gz files Store these [txt files] in a directory raw/ Then, create a tab-delimited file, targets.txt,…

How to get data from GEO by using getGEO function ? 0 Hello everyone, I am using R package GEOquery to get a geo object from file ( in my directory) by getgeo function. I already download the required packages BiocManager::install(“DESeq2”) BiocManager::install(“limma”) BiocManager::install(“GEOquery”) library(DESeq2) library(limma) library(Biobase) library(GEOquery) I used this…

Power calculation for microarray data 0 I have an initial sample of 228 patients from a microarray study. Recently I have obtained a new set of labels specifying different condition types for only 69 out of the 228 patients. I wanted to run a DEG analysis on this set of…

Why do I get a big log fold change but small mean change in b value when plotting differential methylation? 0 Hello I am doing differential methylation analysis using limma. I use the m values for testing and b values for plotting. I plotted a volcano plot visualizing the p…

I wrote a script on how to analyze the microarray-based miRNA expression data. Here is my code: # general config baseDir <- ‘.’ annotfile <- ‘mirbase_genelist.tsv’ setwd(baseDir) options(scipen = 99) require(limma) # read in the data targets <- read.csv(“/media/mdrcubuntu/46B85615B8560439/microarray_text_files/targets.txt”, sep=””) # retain information about background via gIsWellAboveBG project <- read.maimages(targets,source=”agilent.median”,green.only…

Hi, a quick check on NCBI Gene reveals that the official symbol for this is *PRXL2C*, not *AAED1*. In this way, I would not have expected `org.Hs.eg.db` (using ‘recent’ annotation) to have it. However, I can see that `EnsDb.Hsapiens.v86` (older version) does [have it]. So, there must have been an…

The biggies are obviously DESeq2, limma and edgeR, but they are massive packages doing some very complex statistics, and also have dependency trees that would need to be considered. Depending on your background, you might want to look into the rtracklayer/GenomicRanges eco-system. While I personally am not a fan, I…