Categories
Tag: DGE
Merging multiple samples in Seurat
Hello! I am very recent to snRNAseq , however has recently started using Seurat to process the data I have available. This is more of a clarification that I have understood the tutorials appropriately. A breakdown of my data: I have snRNAseq data from diseased with mutation, diseased without mutation…
Error in CIBERSORTx
Hello, I am trying to use CIBERSORT to deconvolute the immune cells in pancreatic cancer after my treatments. I have 3 biological replicates of Control, Treatments A,B,C. Using edgeR, I created the cpm matrix which is not log transformed. and converted it to the required format as follows: # Load…
Potent latency reversal by Tat RNA-containing nanoparticle enables multi-omic analysis of the HIV-1 reservoir
Participants and blood collection A total of n = 23 HIV-1 seropositive individuals on stably suppressive ART were included in this study (Supplementary Table 1). Participants were recruited at Ghent University Hospital. 2/23 individuals are female, 21/23 are male; the limited representation of female individuals in our study is a direct reflection of…
DESeq2 interaction term + sva
Hello, I am performing DGE analysis using DESeq2. I have two groups to compare: CTRL and SA, and I have performed a group comparison using DESeq2 and there’s no issue with that. However, I have males and females in each group, and I’m curious to see if there’s an interaction…
how to test for differential expression in samples where a global increase in gene expression is expected
As the title suggestions, I’m wondering what the best way to test each gene in a count matrix containing two groups is, where one group is expected to have a global increase in gene expression. I need to use spike-in normalized RPKM data, so from my understanding of DESeq, it…
Collapsing Transcript Count Matrix to Gene Count Matrix
Collapsing Transcript Count Matrix to Gene Count Matrix 0 Hi all, My colleague is trying to do some DGE. He got hold of a transcript count matrix from another colleague but he was trying to do the analysis at gene level not transcript level. Eventually I found those RSEM files…
Normalization of RNA captureSeq data (
Normalization of RNA captureSeq data (<20 genes captured) 0 Hi all Hope someone can help with this. We are working on RNA captureSeq experiments where we perform targeted RNAseq on 20 genes of interest (+ probes for the 92 ERCC standards). In the initial phase of the experiment we were…
RNA-seq log2 fold change to linear
RNA-seq log2 fold change to linear 1 Hello, I have RNA-seq data with log2 fold changes in gene expression along with adjusted p values. If I transform the fold changes to linear fold changes, how do I transform the adjusted p values? Secondly, where can I find the error between…
Ggolot in R – GGplot basic syntaxes included – DigHde aphs ciaion Libxasy- name hbMa ” Library-
DigHde aphs ciaion Libxasy- name hbMa ” Library- name data(rame) Home hame Tucouncthons 99plot) data jet plot level aesthebiig 3Peufres Jayeu Sprube aesthefig 9eOTn-ba () ####### Aesthehs gaom-bau (CJ – (1 Y) colo, L ght ba Colot ####### /79pet (dat o ode Vcu’ahle Colo ge Om-ba 99dot dala s (…
Global Metagenomics Sequencing Market Trends, Opportunities, Competition and Forecasts, 2018-2022 & 2023-2028 – ResearchAndMarkets.com | Business
DUBLIN–(BUSINESS WIRE)–Nov 8, 2023– The “Metagenomics Sequencing Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Product and Service (Reagents & consumables, Instruments, Services), By Technology, By Application, By Region, and By Competition” report has been added to ResearchAndMarkets.com‘s offering. × This page requires Javascript. …
zero counts for all genes in RNAseq data of Ferret
zero counts for all genes in RNAseq data of Ferret 0 I have bulk RNAseq data from Ferret and trying to get counts per gene. to do so I used hisat2 and got the genome from here: hgdownload.soe.ucsc.edu/goldenPath/musFur1/bigZips/musFur1.2bit after aligning the fastq files I used htseq and the following command:…
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…
Transcriptome de novo from different library types
Transcriptome de novo from different library types 0 Hello guys, I sequenced RNA from whole individuals from 4 different experimental conditions (non-model isopod species). The thing is that I used different library prep protocols: Condition 1 and condition 2: samples were made with library prep kit X (stranded, reverse–forward) Condition…
DESeq2 Normalization with 4 Groups
Hello All! I am running DESeq2 on my RNA Seq dataset. I have four groups in my treatment with 8 replicates and about 14,500 rows (genes) after using keep (removing low copy numbers) and removing NA. I also used level so that my Control is the reference. So I have…
Correcting for covariates in GWAS studies and differential gene expression analysis
Correcting for covariates in GWAS studies and differential gene expression analysis 0 Hi all, recently, I read quite a few papers in the GWAS field and noticed something which I did not quite understand. When looking for associations, often a “simple” linear model is used, however, before fitting the model,…
Contamination found in sequencing data of an isolated cell structure, what can I do?
Contamination found in sequencing data of an isolated cell structure, what can I do? 0 Hi all, I isolated particular cell types (cell types that comprise a functional structure that can be isolated as a structure) from brain tissue (brain samples belong to two groups). This was more of an…
Differential Expression Cutoffs for n = 1
Differential Expression Cutoffs for n = 1 1 @2289c15f Last seen 22 hours ago Germany I have an experimental setup of bulk RNAseq with a control group n = 6, and condition group n = 1. It was impossible to get more than one sample for the condition, it is…
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…
Deseq2, how to model design for comparing Mutant mouse at age 14 days versus Mutant mouse at birth with normalization to the age difference of the Wildtype condition
Deseq2, how to model design for comparing Mutant mouse at age 14 days versus Mutant mouse at birth with normalization to the age difference of the Wildtype condition 0 @d4a334e3 Last seen 3 hours ago Germany Hello! I would appreciate the help with modeling design of My bulk RNA experiment,…
How to find target genes From RNA seq data?
How to find target genes From RNA seq data? 0 Hello, I am working on Differential Gene Expression analysis of 2 different cotton varieties. After finding DEGs from RNA seq data the next step is annotation and I need help in that I am trying to find genes that are…
Gene-based differential expression analysis of genetically modified mouse line
Gene-based differential expression analysis of genetically modified mouse line 0 Hello, I am trying to analyze my bulk RNAseq data set from hippocampal tissue extracted from our WT/KO mice. The knockout consists of a 10kb deletion in a single exon of our gene of interest. I want to look at…
microarrayDGE analysis protocol modify
microarrayDGE analysis protocol modify 0 Hello, I am trying to perform microarray DGE analysis in R. I am following this protocol: www.costalab.org/wp-content/uploads/2020/11/handout.html I am up to the step of selecting the samples following reading in the data using the GEOquery package. sel <- 1:12 However, the protocol selects the first…
Meta analysis randon effects model and combined p-values
I am performing a meta analysis based on 10 different data sets (derived from different platforms and technologies (RNAseq as well as Microarray)). DGE analysis was pretty much straight forward and mostly performed using limma package. The experimental setup was nothing special, just a treatment (heat) vs. control design. So…
Differential Gene Expression (DGE) Analysis in RNA Sequencing
What Are DEGs in Genetics? DEGs, or Differentially Expressed Genes, are genes whose expression levels show significant differences between two or more conditions or experimental groups. In genetics and genomics research, gene expression refers to the process by which information encoded in a gene’s DNA sequence is converted into functional…
Microarray DGE analysis
Microarray DGE analysis 1 Hi, www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSE30929 I have performed DGE analysis between WDLPS and DDLPS tumour samples in R and have the following results table. I ended up with the same results as the GEO2R. logFC AveExpr t P.Value adj.P.Val B 207175_at -5.7 8.8 -14 3.1e-25 7.0e-21 47 213706_at -3.5…
microarray DEG analysis
microarray DEG analysis 1 Hi, I was following this microarray bioinformatic differential gene expression analyses tutorial R code: github.com/Lindseynicer/How-to-analyze-GEO-microarray-data/blob/main/GSE_analysis_microarray.Rmd I analysed GSE30929 instead. However, when I run this line of code fit2 <- contrasts.fit(fit, contrasts) fit2 <- eBayes(fit2) topTable(fit2) topTable1 <- topTable(fit2, coef=1) topTable2 <- topTable(fit2, coef=2) topTable3 <- topTable(fit2,…
What to do after importing quantification with tximport
What to do after importing quantification with tximport 1 I am doing the classic pipeline for DGE Analysis. I have quantified some rna-sequences with Salmon and now I have imported them with tximport package (as the vignette says). I am new to the field and I am stuck at this…
Load MF, CC and BP from org.Hs.eg.db
Hi! I would like to load all the pathways related to CC, MF and BP from the org.Hs.eg.db, converting into a dataset that has as columns pathway, gene_symbols. In order that after this I filter the pathways that have genes in common with the metabolism pathways from KEGG. So that…
How to add value of column to barchart on hover?
Hi! Ii have a dataset called final_result with the colnames1 “pathway” “genes_involved_in_pathway” “kit_gene_counts”[4] “leiomyo_lipo_gene_counts” “nos_leiomyo_gene_counts” “nos_lipo_gene_counts”[7] “genes_leiomyo_lipo” “genes_nos_leiomyo” “genes_nos_lipo”[10] “genes_leiomyo_lipo_commonly_expressed” “genes_nos_leiomyo_commonly_expressed” “genes_nos_lipo_commonly_expressed” gg <- ggplot(final_result, aes(x = reorder(pathway, -kit_gene_counts))) + geom_bar(aes(y = kit_gene_counts), stat = “identity”, fill = “lightblue”, width = 0.5) + geom_bar(aes(y = leiomyo_lipo_gene_counts), stat = “identity”, fill…
Enricher – Hyper Geometric Test Details
Hi! I have a set of 1435 genes with 445 DE and I am using enricher to analyse a specific group of pathways like this. em <- enricher(genes, minGSSize=1, maxGSSize = 20, universe = names(gene_list), TERM2GENE=hs_kegg_df, pAdjustMethod = “bonferroni”) The hs_kegg_df is a set of lipid metabolism pathways. I got…
Over Representation Analysis over one specific pathway
Over Representation Analysis over one specific pathway 0 Hi! Let’s say I would like to analyse if a particular pathway is enriched how would I do that given that I have a set of DGE genes resulting from 1500 genes of RNA Seq? I do not want to analise any…
Enricher with Gene Symbols
Enricher with Gene Symbols 0 Hi! I have a list of genes with abs(logfc) >= 0.9 like this: > genes [1] “MDM2” “CDK4” “CCND2” “FLNA” “RBP7” “EDNRB” “EPHA4” “PTPRB” “PPP1R13L” “TPM1” “INSR” [12] “DLC1” “WNT7B” “SFRP1” “IFI16” “ZMAT3” “MEST” “AKT3” “CD36” “SRD5A1” “KIF23” “EPOR” So the list has the gene…
Differential gene expression with specif genes of interest
Differential gene expression with specif genes of interest 1 I have a matrix with read counts data from RNA-seq analysis. Let’s say I’m only interested in 10 specific genes (I want to know if they are differentially expressed), but the data is for all genes. Should I:1) Filter the counts…
Gene set enrichment analysis / Kegg analysis
Gene set enrichment analysis / Kegg analysis 0 Hi all, I recently did differential gene expression of Daphnia magna using DESeq2 in R studio. It was my first time doing the analysis. Now the next step is to conduct Kegg analysis or Gene set enrichment analysis of the differentially expressed…
LogFc vs t_statistic to estimate over/under expressed genes?
LogFc vs t_statistic to estimate over/under expressed genes? 0 Hi! I am doing DGE using limma+voom over two populations, I have a gene X that has significant adjusted p values yet logfc values of 0.6/0.7 which is below the threshold of 1. Additionally I did t test over the Voom$E…
Question on using Sleuth for differential gene expression analysis
Question on using Sleuth for differential gene expression analysis 0 Hi, I am using Kallisto and Sleuth to analyze my RNA-seq data. I have an issue performing a step to associate transcripts to genes using the command “aggregation_colum = ‘ens_gene’. I received an error message: “Error in check_target_mapping(tmp_names, target_mapping, !is.null(aggregation_column))…
Direct inference and control of genetic population structure from RNA sequencing data
In this study, we constructed the RGStraP pipeline to calculate RG-PCs from genetic variants called from RNAseq data. RGStraP relies on GATK for its variant calling suite, as well as PLINK and flashPCA to filter the SNPs and calculate genetic principal components from them, respectively (Methods). We make RGStraP available…
CombatSeq on a large dataset before running DSeq2 on a very small subset?
CombatSeq on a large dataset before running DSeq2 on a very small subset? 0 I have an RNA-Seq counting table containing approximately 400 patients with similar diseases, and these patients were sequenced in four batches. (Among the batches, we have noticed a strong effect in batch 4 and a “moderate”…
Typical Volcano Plot for DGE
Typical Volcano Plot for DGE 1 Hello, This is my first doing a DGE and created a volcano plot for the genes that were found to be significantly differentially expressed. I have been looking at gene expression volcano plots in the literature and mine doesn’t look quite similar to those….
How to analyse a particular pathway after doing DGE?
How to analyse a particular pathway after doing DGE? 0 Let’s say I have a set of RNA-seq of 1500 genes and I did DGE over two groups and got a list os DGE genes. GSEA is out of question due to the 1500 gene set. I have done already…
Add gene counts of same samples run on two lanes (Novaseq)
Add gene counts of same samples run on two lanes (Novaseq) 0 Hello, I am a beginner in the field of Bioinformatics and would like your feedback on a roadblock I am currently facing. I have to perform DGE of RNAseq data using DESeq2 in R. For one fastq sample,…
Optimal Over Representation Analysis DE genes foldFC threshold?
Optimal Over Representation Analysis DE genes foldFC threshold? 0 Regarding Over Representation analysis over identification of DGE genes, firstly I have a set of 1550 genes resulting of RNA Seq. Given this number decided to do ORA instead of GSEA. After choosing ORA, I have to pass to enrichGO a…
A universal tool for predicting differentially active features in single-cell and spatial genomics data
singleCellHaystack methodology For a detailed description of the original singleCellHaystack implementation (version 0.3.2) we refer to Vandenbon and Diez19. In brief, singleCellHaystack uses the distribution of cells inside an input space to predict DAFs. First, it infers a reference distribution \(Q\) of all cells in the space by estimating the…
losing many genes while doing DGE on the RNAseq data due to read count threshold
losing many genes while doing DGE on the RNAseq data due to read count threshold 2 I am working with RNAseq data from patients and conditions I have and want to compare to each other for the gene expression analysis, are before and after treatment. the threshold I used for…
DGE analysis for diseased samples through DESeq2 and Ballgown
DGE analysis for diseased samples through DESeq2 and Ballgown 1 @9eef20e1 Last seen 5 hours ago Pakistan I have diseased and normal samples. How will DGE analysis tools DESeq2 and Ballgown know that they have to analyse differentially expressed genes from diseased samples comparing diseased with normal. Where I need…
How to do GSEA over limma + voom DGE ?
I am doing DGE over RNASeq data of two types of cancer. Here is the code: keep <- filterByExpr(RNA_data, design = design) RNA_data <- RNA_data[keep,] RNA_data <- DGEList(counts = RNA_data, genes = rownames(RNA_data)) # Normalize the counts using the TMM method RNA_data <- calcNormFactors(RNA_data, method = “TMM”) # Create the…
Genomic characteristics of triple negative apocrine carcinoma: a comparison to triple negative breast cancer
Baseline characteristics We described the baseline clinical and pathological characteristics of TNAC and LK-TNBC in Supplementary Table 1. Only stage at diagnosis was different between TNAC and LK-TNBC (P = 0.03), while no significant differences were observed in other characteristics, including nuclear grade, histologic grade, Ki-67, and status of (neo)adjuvant treatment. Somatic…
Comparing P-Values & FDR adjusted p-values between RNA-Seq experiments?
Comparing P-Values & FDR adjusted p-values between RNA-Seq experiments? 0 Hello, I ran my RNA-Seq comparisons individually: Co-Infection RSV & Bacteria versus Control RSV Infection versus Control I used the same parameters for the experiments and used EdgeR TO TMM-normalize and filter the counts based on expression. This filtering results…
Set up on SLURM – JupyterHub
Hello, I’m trying to set up a HPC-Enabled Jupyterhub to launch notebooks on our compute and gpu nodes, with the hub service running on the login node. So far, everything seems to be working, I have jupyterhub installed in a conda environment (eventually this will migrate to a systemd control…
Analysis of Differential Gene Expression (DGE) in RNA Sequencing
What are Differentially Expressed Genes (DEGs) in Genetics? Differentially Expressed Genes (DEGs) are genes that exhibit significant differences in expression levels between two or more conditions or experimental groups. In genetics and genomics research, gene expression refers to the process through which the information encoded in a gene’s DNA sequence…
complex heatmap with CPM
complex heatmap with CPM 0 Hi all, To draw complex heatmap, I started to use ComplexHeatmap package in R. I have a RNASeq data which has 2 cell lines with 2 conditions (CellLine1-WT, CellLine1-KO, CellLine2-WT, CellLine2-KO). When I try to draw heatmap with log2(CPM+1) values, the h2052 doesnt cluster together…
Limma differential expression analysis across subtypes
I want to retrieve the ANOVA-based differential expression between KIRP1a, KIRP1b, KIRP1c, KIRP2a, KIRP2b, and KIRP2c groups to identify biomarkers for each group. My code below returned deg that are statistically significant but my heatmap (z-scaled) did not show any observable differences across the subtypes. Is there an issue with…
RNA seq differential expression analysis
RNA seq differential expression analysis 0 @14ef1b09 Last seen 4 hours ago Egypt I have a DGE object containing tumor and control RNA seq samples. Tumor n=126 and Control=390. I want to filter low expressed genes before starting limma analysis. I want to know how to set the threshold of…
Choice for statistical test (and R package)
Choice for statistical test (and R package) 0 Hi all, I have a dataset of single cell RNA sequencing (to be precise, single cell RNA profiling using the probe-based 10X RNA FLEX assay). I had cells that I split and treated identically, but one set got Interferon gamma (IFNg). I…
Identification of molecular mechanisms causing skin lesions of cutaneous leishmaniasis using weighted gene coexpression network analysis (WGCNA)
Data information We downloaded all the data used in this research from National Center for Biotechnology Information Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo/). We used the data set GSE1278317 to construct a co-expression network by Differential Gene Expression analysis (DGEs) and Weighted Gene Co-expression Network Analysis (WGCNA). The Data was obtained from…
Using different filtering steps in different iterations of DEseq2
Using different filtering steps in different iterations of DEseq2 0 @9c8b15cf Last seen 1 hour ago Canada Hi all, I have a bit of a theoretical question here. I’m using DEseq2 for DGE analysis between controls and a disease group. Within both groups, I have males and females. I’ve done…
Limma returned only positive logFC values
Limma returned only positive logFC values 0 I want to obtain the upregulated and downregulated genes using limma. However, all the DEGs returned by my code have positive LogFC and none are downregulated (negative LogFC). This observation is consistent across multiple distinct dataframes. Is there something wrong with my code?…
Emerging Methodologies for the Molecular Analysis of Soil Microbiota from Polluted Soil Sites
Anderson IC, Campbell CD, Prosser JI (2003) Diversity of fungi in organic soils under a moorland–Scots pine (Pinus sylvestris L.) gradient. Environ Microbiol 5(11):1121–1132. doi.org/10.1046/j.1462-2920.2003.00522.x Aria M, Cuccurullo C (2017) Bibliometrix: an R-tool for comprehensive science mapping analysis. J Informetr 11(4):959–975. doi.org/10.1016/j.joi.2017.08.007 CrossRef Google Scholar Artursson V, Jansson JK (2003)…
Transcriptional patterns of sexual dimorphism and in host developmental programs in the model parasitic nematode Heligmosomoides bakeri | Parasites & Vectors
Mapping of bulk RNA-seq data and differential gene expression (DGE) Using the splice-aware aligner STAR, we mapped the RNA-seq reads to the H. bakeri genome assembly obtained from WormBase ParaSite (PRJEB15396). Among all the datasets, 93.26–95.62% of the reads uniquely mapped to the reference genome (Table 1), reflecting the high…
rna seq design matrix
rna seq design matrix 0 Hi all, I have RNA-seq data and it is composed of one control group and two knockout groups, to simplify my samples are detailed below; Control_1 Control_2 AKT_KO_g1_1 AKT_KO_g1_2 AKT_KO_g2_1 AKT_KO_g2_2 These are my samples (in duplicates), so to compare all KO samples with controls…
What Did the Earliest Animals Look Like? Chromosomal Clues Unearth the Origins of Animal Evolution
A new study used a unique approach based on chromosome structure to determine that comb jellies, also known as ctenophores, were the first lineage to diverge from the animal tree of life, with sponges following as the next branch. Previously, it was unclear whether sponges or comb jellies were the…
On “wings” in volcano plots…
On “wings” in volcano plots… 0 Apparent “wings” in volcano plots (for example, as seen here) are evidence for the relationship between fold change and p-value when expression is low in one condition and there are few replicates. If one wishes to remove or minimize these, that can be done…
Genetic Linkages Illuminate Earliest Animal Evolution
A study by MBARI and collaborating scientists used gene linkages to establish that comb jellies, not sponges, are the most distantly related animal to all other animals, helping to clarify a fundamental question about animal evolution that dates back over 700 million years. Mapping gene linkages provides clear-cut evidence for…
What did the earliest animals look like?
Scientists have long debated whether comb jellies (left) or sponges (right) are the sister group to all other animals. A detailed comparison of the chromosomes of these and other animals to the chromosomes of three single-celled non-animal groups finally resolves the question. (Photos courtesy of MBARI) For more than a…
Beyond Alphafold: AI Excels At Creating New Proteins
Ian Haydon Proteins designed with an ultra-rapid software tool called ProteinMPNN were much more likely to fold up as intended. Over the past two years, machine learning has revolutionized protein structure prediction. Now, three papers in Science describe a similar revolution in protein design. In the new papers, biologists at…
Methanol fixation is the method of choice for droplet-based single-cell transcriptomics of neural cells
hiPSC cell culture and differentiation hiPSCs were maintained on 1:40 matrigel (Corning, #354277) coated dishes in supplemented mTeSR-1 medium (StemCell Technologies, #85850) with 500 U ml−1 penicillin and 500 mg ml−1 streptomycin (Gibco, #15140122). For the differentiation of cortical neurons the protocol described previously21 was followed with slight modifications. Briefly, hiPSC colonies were seeded…
How do you select DEGs for further validation?
How do you select DEGs for further validation? 1 Perhaps this a silly question, but I’m overwhelmed with the different ways to give context to results after DGE analysis (RNA sequencing in a disease vs healthy control context). Of course I know that one should establish criteria for significance and/or…
Can I consider these values as differentially expressed?
Hello! I’m needing some help from the more experienced ones! n_n’ I’m doing a transcriptome expression comparison using DESeq2 and I would like to be sure I’m using the right parameters. This doubt came after seeing that a gene increased the expression between different sampling points but was not included…
How to perform t-test to check if cancer samples (3 replicates ) are significantly different from normal samples (3 replicates) on R?)?
How to perform t-test to check if cancer samples (3 replicates ) are significantly different from normal samples (3 replicates) on R?)? 0 How to perform t-test to check if cancer samples (3 replicates ) are significantly different from normal samples (3 replicates) on R?)? t-test DGE R • 25…
How does cell number in clusters affect the number of DE genes?
scRNA-seq: How does cell number in clusters affect the number of DE genes? 0 Hi, I’m new to scRNA-seq and bioinformatics, and have some questions, which I presume might be rather basic but would hopefully help out others like me who are just starting out – couldn’t find any past…
Bioconductor – pairedGSEA
DOI: 10.18129/B9.bioc.pairedGSEA Paired DGE and DGS analysis for gene set enrichment analysis Bioconductor version: Release (3.17) pairedGSEA makes it simple to run a paired Differential Gene Expression (DGE) and Differencital Gene Splicing (DGS) analysis. The package allows you to store intermediate results for further investiation, if desired. pairedGSEA comes…
Having problem on doing edgeR anlysis- cant create the DGE list through readbismark2DGE function.
I am facing a problem on getting the DGElist from the function of readbismark2dGE(). It didn’t show any error. output of bismark2DGE only shows Hashing, counting. I am using google colab to get more system RAM. I am using R version R4.2.3 and BiocManager 3.16. if (!requireNamespace(“BiocManager”, quietly = TRUE))…
enrichKEGG function error
enrichKEGG function error 1 @d4a334e3 Last seen 4 hours ago Germany Hello, I was trying to check kegg enrichment analysis for my Bulk RNAseq DGE results, and I am getting this error –> No gene can be mapped…. –> Expected input gene ID:–> return NULL… could you kindly tell what…
coef /makeContrasts very different results
I have a situation where I have a factoral independant variable ‘suicide’ with three levels ‘non_suicide’, suicide, and ‘unkown’. I have been setting up my analysis thus: suicide.non.undet <- as.factor(df$suicide) CauseofDeath.recode <- as.factor(df$CauseofDeath) Sex <- as.factor(df$Sex) Smoking <- as.factor(df$Smoking) Ethanol <- as.factor(df$Ethanol) svseq1 <- as.numeric(df$svseq1) design1 <- model.matrix(~ suicide +…
View all rows in R studio RNASeq
View all rows in R studio RNASeq 0 This is definitely a basic question, but I can’t seem to find a straight answer online. I am running DGE through R Studio and just calculated my normalization values, however, I have 12 lines of samples the the “e” command is only…
The Biostar Herald for Monday, April 10, 2023
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 contribution from Istvan Albert, Pavel, and was edited by…
Up-regulation of ubiquitin
Up-regulation of ubiquitin 0 Hello, I have created two deletion S. pombe strains where I specifically deleted some of the mRNA decay factor genes. After doing a DGE analysis I found ubi4 gene coding for ubiquitin is the most up-regulated gene in both deletion strains. Is this a normal cellular…
RNA-seq analysis without replicates
RNA-seq analysis without replicates 1 We have RNA-seq data for 12 samples for 12 conditions. Unfortunately, we do not have any replicates and each sample corresponds to one condition. For differential gene expression analysis, I will need at least 3 replicates (or patients) for each condition to be able to…
Bioinformatics Analysis of Small RNA Sequencing
Small RNAs are important functional molecules in organisms, which have three main categories: microRNA (miRNA), small interfering RNA (siRNA), and piwi-interacting RNA (piRNA). They are less than 200 nt in length and are often not translated into proteins. Small RNA generally accomplishes RNA interference (RNAi) by forming the core of…
Corset -D parameter
Corset -D parameter 0 Hello everyone, My input was 633.679 transcripts (from Trinity.fasta) made from 10 samples, no groups defined. I run corset with default parameters and got 51.556 clusters. What bothered me is that multiple transcripts were assigned to the same cluster-ID so in the end I have 46.698…
limma with or without intercept gives different results
My data has two variables: treatment (untreated vs treated) and exon number (control, 1 and 9), each with 3 replicates. So 18 samples total but 6 unique groups (untreated-ctrl, treated-ctrl, untreated-1, treated-1, untreated-9, treated-9). I started by coding everything into one design matrix, then making contrasts for all the comparisons…
Time change in expression vs time change in phenotype
Time change in expression vs time change in phenotype 0 Hello everyone; We have a prospective study for which at two time points (t1,t2) we collected blood samples and some quantitative traits Q. Using DESeq2, we can ask if the blood gene expression E at t1 or t2 is associated…
differential gene analysis
differential gene analysis 0 hello! i am working on differential gene expression of cell free RNA… In this process i have created the count matrix then calculated the log of count per matrix further calculated the Z_score and calculate the variance using log and created the boxplots…so these 2 boxplots…
RevGel-seq: instrument-free single-cell RNA sequencing using a reversible hydrogel for cell-specific barcoding
RevGel-seq sample preparation workflow Experiments were performed with the RevGel-seq protocol, capable of analyzing 10,000 input cells per sample with the specially designed gelation device (Fig. S3). The individual steps shown in Fig. 1A, from cell-barcoded bead coupling to library preparation for sequencing, are more fully described below: Cell labeling Cells…
Is it possible to do DGE analysis using log 2 normalized data with EdgeR ?
Is it possible to do DGE analysis using log 2 normalized data with EdgeR ? 2 Hello everyone, I intend to analyze differential gene expression using a GEO dataset. The value is log2 normalized signal intensity. I know edgeR’s workflow involves log normalization. However, can I skip the normalization steps…
Stringtie does not work with NCBI GTF file?
Stringtie does not work with NCBI GTF file? 1 Hi all, I wanted to rerun my DGE analysis to see if there were any differences between HTseq-count -> edgeR and StringTie-Ballgown. However, when I tried to run my stringtie command using the same BAM file, I got an error: “Error:…
differential expression analysis of tRFs
differential expression analysis of tRFs 0 Hello everyone! I have a question regarding the processing pipeline of tRFs in rat samples. I have three groups control and two stressed conditions (unfortunately too little samples each group) I am interested in doing DGE analysis and I need to take into account…
Pseudo-bulk celltype comparison across conditions from multiple-sources
Pseudo-bulk celltype comparison across conditions from multiple-sources 1 @84e617fb Last seen 6 hours ago United Kingdom Hi all, I am aiming to merge my dataset with other available online. Data will be SCTv2 normalised, and visual integration will be done by Harmony. For DGE analysis, I would like to perform…
Normalization of RNA seq data before DESeq2 and PCA in case of strong batch effects
Normalization of RNA seq data before DESeq2 and PCA in case of strong batch effects 1 @b99e3575 Last seen 4 hours ago India I have a dataset having 4 rna seq healthy tissue samples prepared with unstranded Illumina library and another dataset with 8 rna seq healthy tissue samples prepared…
Will filter cell by highly variable genes (HVG) selection marks DGE for the filtered out low variable genes in further analysis?
Will filter cell by highly variable genes (HVG) selection marks DGE for the filtered out low variable genes in further analysis? 1 I want to compare DGE between treated group and control group of single-cell Seq experiment. The genes of my interest are considered to be house keeping genes. In…
Differential expression vs tissue specific expression
Differential expression vs tissue specific expression 1 I came across an article benchmarking different tissue-specific gene expression identifying methods. I am wondering why is it not a common practice to use differential expression analysis methods, like DESeq2, to identify tissue specific genes? Practically, it can be really a time-consuming task,…
DGE/DEG Analysis for comparing multiple cell lines
Hello community, I’m relatively new to DGE/DEG analysis using RNA-Seq data, for which I’ve seen that DESeq2 is one of the go-tos for differential gene analysis. I am a bit confused about the list of genes I am obtaining and which type of normalization methods are best to use (variance…
How to use gseapy after scanpy?
Hello, I analyzed some data using scanpy and now I want to do some pathway analysis. I have done DE analysis between each cluster and the rest and I want to do the pathway analysis for each cluster but I have a few questions. I initially followed the instructions from…
RNAseq for DE purpose
RNAseq for DE purpose 0 Hi all, I am totally new in the bioinformatic analysis. I am working on a project that looks at DGE among different time treatments. Besides, there is no reference genome (meaning that I need a de novo assembly step). So far, after struggling and navigating…
Estimating Fold-Changes of Lowly Expressed Genes
Estimating Fold-Changes of Lowly Expressed Genes 1 @vm-21340 Last seen 6 hours ago Brazil I am doing a DGE analysis using RNAseq data to compare three conditions. I am using a standard pipeline (Create DGEList > Filter very lowly expressed genes > TMM normalize > DGE). Since there is a…
Phylogeny and Genetic Diversity of Philippine Native Pigs (Sus scrofa) as Revealed by Mitochondrial DNA Analysis
Ai H, Fang X, Yang B, Huang Z, Chen H, Mao L, Zhang F, Zhang L, Cui L, He W, Yang J, Yao X, Zhou L, Han L, Li J, Sun S, Xie X, Lai B, Su Y, Lu Y, Yang H, Huang T, Deng W, Nielsen R, Ren J,…
rna seq – R – [DESeq2] – How use TMM normalized counts (from EdgeR) in inputs for DESeq2?
I have several RNAseq samples, from different experimental conditions. After sequencing, and alignment to reference genome, I merged the raw counts to get a dataframe that looks like this: > df_merge T0 DJ21 DJ24 DJ29 DJ32 Rec2 Rec6 Rec9 G10 421 200 350 288 284 198 314 165 G1000 17208…
How to reduce the impact of one varaible in Deseq2 or edgeR for multivariate value analysis?
Hello, everyone, I’m recently meeting this problem with my analysis, which i’ve done a lots of research and asked people around but their answers are quite confusing, so if I can get more opinions, that’d be terrific and thanks at advance. So I’m doing an analysis of DEGs using Deseq2…
Active Motif Incorporated Announces the Acquisition of Amaryllis Nucleics and their proprietary RNASeq workflow
CARLSBAD, Calif., Jan. 27, 2022 /PRNewswire/ — Active Motif Incorporated, a company with the vision of bringing epigenetics more deeply into precision medicine, announced that it has purchased Amaryllis Nucleics, a Bay Area-based start-up company focused on proprietary RNA Sequencing methods. Amaryllis Nucleics provides Active Motif with a streamlined, low-cost…
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…