Tag: deseq2

Bioconductor – BioNERO

DOI: 10.18129/B9.bioc.BioNERO     This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see BioNERO. Biological Network Reconstruction Omnibus Bioconductor version: 3.15 BioNERO aims to integrate all aspects of biological network inference in a single package, including data preprocessing, exploratory analyses, network inference, and analyses…

Continue Reading Bioconductor – BioNERO

FASTQ to FASTA Converter

About the tool The FASTA format is a text-based format for representing nucleotide or peptide sequences. The FASTQ format additionally includes the corresponding quality scores. This tool allows you to convert FASTQ files to FASTA. The resulting FASTA file will contain only the sequence data from the input FASTQ file….

Continue Reading FASTQ to FASTA Converter

Running Deseq2 with all samples vs samples for each comparison separately

Running Deseq2 with all samples vs samples for each comparison separately 1 @52b8b937 Last seen 5 hours ago Portugal Hello, I am currently using Deseq2 to perform differential analysis on my data. I have feature count data for 24 samples and 4 comparisons to do ( for each comparison I…

Continue Reading Running Deseq2 with all samples vs samples for each comparison separately

Deseq2 output and robust PCA (PcaGrid and PcaHubert)

Deseq2 output and robust PCA (PcaGrid and PcaHubert) 0 Hello there, I followed the deseq2 file to get the list of differentially expressed genes of a dataset I am working on. The Pca graph I got was not enough to show which one of the replicate is an outlier. A…

Continue Reading Deseq2 output and robust PCA (PcaGrid and PcaHubert)

DESeq2 (zeros in the taxa table) – Other Bioinformatics Tools

komal (Komalk) January 19, 2024, 12:02pm 1 Hi this is regarding DESeq2. I first created a phyloseq object from qiime2 artifacts and then subjected it to Deseq2. At one step I got a errorError in estimateSizeFactorsForMatrix(counts(object), locfunc = locfunc, :every gene contains at least one zero, cannot compute log geometric…

Continue Reading DESeq2 (zeros in the taxa table) – Other Bioinformatics Tools

Deleting a column from data frame and then running DESeq2

Forgive me if this post is messy, I’m new to this! I’m analyzing RNA Seq data and found that one of my samples is an outlier (sample AV17). I’m trying to exclude it from my analysis, but whenever I do, using this code: dds = subset(countData, select = -c(AV17) ),…

Continue Reading Deleting a column from data frame and then running DESeq2

Troubleshooting RNA-seq data with DNA contamination

Troubleshooting RNA-seq data with DNA contamination 0 Hi everyone, If there has been DNA contamination in the RNA samples and RNA-seq was conducted. After RNA-seq, I tried using SeqMonk and I estimated contamination levels, which were highly variable between samples, ranging from 1.7% to 10.5%. My initial step was to…

Continue Reading Troubleshooting RNA-seq data with DNA contamination

Quantile normalisation on RNAseq with substantial differences on sample size

Quantile normalisation on RNAseq with substantial differences on sample size 0 I tried vst and rlog from DESEq2 for my RNA seq data. But i suspect the largest group (condition 1 with 60 samples) has affected the variance from other groups (condition2 with 20 samples, condition 3 and 4 with…

Continue Reading Quantile normalisation on RNAseq with substantial differences on sample size

installing DESeq2 on Windows

installing DESeq2 on Windows 0 I have a problem with installing DESeq2 on Windows. The problem started with installing libraries that DESeq2 uses so I’m installing them individually. I do it by: ‘BiocManager::install(‘zlibbioc’)’ . I got an error that suggests that is something wrong with compilation: C:\rtools43\x86_64-w64-mingw32.static.posix\bin\windres.exe: can’t popen `C:\rtools43\x86_64-w64-mingw32.static.posix\bin\gcc.exe…

Continue Reading installing DESeq2 on Windows

Should SVs be calculated on normalized data?

Hello, I’m trying to use SVA to calculate SVs in my DESeq2 analysis. In a couple of examples, I’ve seen people generate model matrices using the raw data, but actually calculate SVs on normalized data. For example, this post: Designing of model.matrix for batch correction of Time Course data ?…

Continue Reading Should SVs be calculated on normalized data?

No genes mapped in clusterprofiler gseGO

Hello! I’m having issues generating an adequate geneList for running gseGO in clusterProfiler, using keytype = “GO” Similar issues have been described here: No gene mapped gseGO code is: gse <- gseGO(geneList = gene_List, ont = “ALL”, #ont one of “BP”, “MF”, “CC” or “ALL” OrgDb = OrgDb, minGSSize =…

Continue Reading No genes mapped in clusterprofiler gseGO

Plasma cell-free DNA 5-hydroxymethylcytosine and whole-genome sequencing signatures for early detection of esophageal cancer

Waters JK, Reznik SI. Update on management of squamous cell esophageal cancer. Curr Oncol Rep. 2022;24:375–85. Article  PubMed  Google Scholar  Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185…

Continue Reading Plasma cell-free DNA 5-hydroxymethylcytosine and whole-genome sequencing signatures for early detection of esophageal cancer

scRNA-seq as pseudobulk for DEseq2: does AggregateExpression() normalize counts?

scRNA-seq as pseudobulk for DEseq2: does AggregateExpression() normalize counts? 1 @03836aaf Last seen 5 hours ago United States Hi, I’m using AggregateExpression() function to convert my scRNA-seq data into pseudobulk for differential expression with Deseq2. I’m wondering whether AggregateExpression() simply sums the counts for each gene in each cell, or…

Continue Reading scRNA-seq as pseudobulk for DEseq2: does AggregateExpression() normalize counts?

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…

Continue Reading Batch and Sample correction for downstream analysis using DESeq2

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…

Continue Reading DESeq2 interaction term + sva

what is the best way to build my design model with DESeq2

Hello all, Hope you’re well. I would really appreciate it if you take some time and give me feedback on my experimental design. It is valuable to me. I am doing single nucleus RNA sequencing and using DESeq2 package for my DE analysis. My sample information is as below: Case:…

Continue Reading what is the best way to build my design model with DESeq2

Bioconductor – airway

DOI: 10.18129/B9.bioc.airway     This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see airway. RangedSummarizedExperiment for RNA-Seq in airway smooth muscle cells, by Himes et al PLoS One 2014 Bioconductor version: 3.15 This package provides a RangedSummarizedExperiment object of read counts in genes for…

Continue Reading Bioconductor – airway

Identification of Differentially Expressed Genes in Human Colorectal Cancer Using RNASeq Data Validated on the Molecular Level with Real-Time PCR

Allam RM, Al-Abd AM, Khedr A, Sharaf OA, Nofal SM, Khalifa AE, Mosli HA, Abdel-Naim AB (2018) Fingolimod interrupts the cross talk between estrogen metabolism and sphingolipid metabolism within prostate cancer cells. Toxicol Lett 291:77–85 Article  CAS  PubMed  Google Scholar  Andrews S et al (2010) FastQC: a quality control tool…

Continue Reading Identification of Differentially Expressed Genes in Human Colorectal Cancer Using RNASeq Data Validated on the Molecular Level with Real-Time PCR

downstream analysis on the output of nf-core/rnaseq pipeline

downstream analysis on the output of nf-core/rnaseq pipeline 1 Hello everyone, I ran nf-core/rnaseq pipeline successfully, now I want to do downstream analysis like machine learning on the generated output files from this pipeline. Should I use salmon.merged.gene_counts.tsv for that and apply log transformation to normalize it before doing downstream…

Continue Reading downstream analysis on the output of nf-core/rnaseq pipeline

ggplot2 – How do I add p.adj values from a DESeq2 experiment to a bar graph plot in R?

I’ve conducted a DESeq2 analysis on a large volume of data and I’m trying to make box plots that compare the counts of specific genes, which are sorted into 2 groups, and include statistical significance. Using the plotCounts() function works fine, but I’m struggling to add the p.adj values calculated…

Continue Reading ggplot2 – How do I add p.adj values from a DESeq2 experiment to a bar graph plot in R?

Correlation methods giving very different results (WGCNA)

Hi all, I’ve come back to WGCNA after some years and have run into a bit of a quirky result when looking at my soft power thresholds depending correlation the methods I use. Generally, this topic has been discussed a fair bit – but was looking to see if anyone…

Continue Reading Correlation methods giving very different results (WGCNA)

Using STAR’s readspergene.tab.out outputs to make gene-level count matrix for DESeq2 using tximport

Using STAR’s readspergene.tab.out outputs to make gene-level count matrix for DESeq2 using tximport 1 @e0db819c Last seen 1 day ago United States Hi, I am new to RNA-seq analysis. I have finished RNA alignment using STAR, and got ReadsPerGene.out.tab outputs. I am trying to use tximport to build a gene-level…

Continue Reading Using STAR’s readspergene.tab.out outputs to make gene-level count matrix for DESeq2 using tximport

Linear Model Fitting and Colinearity

Linear Model Fitting and Colinearity 1 @7220be07 Last seen 9 hours ago United States Hello All, I have an RNAseq experiment with paired samples (before and after treatment). For each sample, I also have metadata on the patient such as sex. The only comparison that I care about is the…

Continue Reading Linear Model Fitting and Colinearity

Small RNA-seq Analysis DESEQ2 : Unexpected Significance

Hello everyone, I’ve been working extensively with a small RNA-seq dataset comprising 47 samples, each associated with a specific date and categorized into ‘ON’ or ‘OFF’ conditions, with three replicates per condition (except for one condition with two replicates only). This dataset encompasses the counts of 77,000 small RNA molecules…

Continue Reading Small RNA-seq Analysis DESEQ2 : Unexpected Significance

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…

Continue Reading removeBatchEffect with non-linear model fit

Using Metagenome Samples for HNSCC analysis

Using Metagenome Samples for HNSCC analysis 0 So I’m trying to analyze the floor-of-mouth HNSCC(Head and Neck Squamous Cell Carcinoma) and controls. I’m going to be using SRA files. The issue I’ve encountered is that I could only find 2 controls. The 2 controls were tumor-adjacent normals. For floor-of-mouth, there…

Continue Reading Using Metagenome Samples for HNSCC analysis

Interaction terms in DESeq2

Hi, I am hoping this isn’t a stupid question as I am really lost here. I have extensively read the manual and other forum posts but am struggling to find a solution. I am using DESeq2 to analyse my data set but running into problems with an interaction term in…

Continue Reading Interaction terms in DESeq2

Finding differentially expressed genes between Seurat clusters

Good afternoon, I am working with a dataset of 7 patients. I have merged all raw counts to one count object with JoinLayers: Now I would like to know whether there are certain genes differentially expressed between my Seurat clusters. For that I ran markers_all<-FindAllMarkers(kid.filtered_new, test.use=”DESeq2″, slot=”counts”) However, it does…

Continue Reading Finding differentially expressed genes between Seurat clusters

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…

Continue Reading Normalization of RNA captureSeq data (

Opinion on miRNA pipeline

Opinion on miRNA pipeline 0 Dear colleagues, I am currently in the process of evaluating miRNA Seq data and would like to present my pipeline for your review. Given the absence of a dedicated bioinformatician in my department, particularly for this specific use case, I am eager to gather feedback…

Continue Reading Opinion on miRNA pipeline

Differential expression using Bowtie2

Differential expression using Bowtie2 0 Hi, I have a gene and I want to investigate its expression in different organs. I’m not sure how best to do this though. I am thinking of using Bowtie2 to either: Align the transcript of the gene to the transcriptome for a cell in…

Continue Reading Differential expression using Bowtie2

Multi-factor designs in DiffBind

Multi-factor designs in DiffBind 1 Dears, I’m trying to analyze some ChIPseq data using DiffBind. Samples has been processed in two different times SampleID Name Factor IP Condition Replicates 5 PBS_Pol2 S3 Batch1 Pol2 PBS 1 6 PBS_Pol2 S9 Batch2 Pol2 PBS 2 7 C26_Pol2 S4 Batch1 Pol2 C26 1…

Continue Reading Multi-factor designs in DiffBind

A chromosome-level genome assembly for the Silkie chicken resolves complete sequences for key chicken metabolic, reproductive, and immunity genes

Friedman-Einat, M. & Seroussi, E. Avian leptin: bird’s-eye view of the evolution of vertebrate energy-balance control. Trends Endocrinol. Metab. 30, 819–832 (2019). Article  CAS  PubMed  Google Scholar  International Chicken Genome Sequencing C. Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature 432, 695–716 (2004)….

Continue Reading A chromosome-level genome assembly for the Silkie chicken resolves complete sequences for key chicken metabolic, reproductive, and immunity genes

stat or lfcshrink for GSEA analysis

DESeq2 : stat or lfcshrink for GSEA analysis 1 @0318a29a Last seen 19 hours ago France Hi, I see the advantage of using lfcshrink in DESeq2 analysis for getting a more “realistic” FC that takes into account the variance of the data. I have a question regarding what variable generated…

Continue Reading stat or lfcshrink for GSEA analysis

Ambient RNA removal method that generates whole (integer) counts

Ambient RNA removal method that generates whole (integer) counts 0 I am envisioning a project that requires removal of ambient RNA counts from cell-containing droplets. On the other hand, I will also need to aggregate counts from individual mice into “pseudobulk” profiles, to use as input to between-condition DE analysis…

Continue Reading Ambient RNA removal method that generates whole (integer) counts

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…

Continue Reading Bioconductor – octad (development version)

contrast file in DESeq2 bioconductor

contrast file in DESeq2 bioconductor 1 Hi everyone, I have 3 time points and want to do deseq2 for comparing these 3 time points: is it correct to build my contrast file like below? results(dds, contrast = c(“timepoints”, “TS”,”EOT”, “FU”)) I can also take TS (Therapy start) as control and…

Continue Reading contrast file in DESeq2 bioconductor

How does Deseq2 deal with the row with zero when calculating size factors

How does Deseq2 deal with the row with zero when calculating size factors 0 @7dbff853 Last seen 1 hour ago United States Hi, I am confused about the calculation of the size factors when the gene has at least one zero count in the samples when using the default params….

Continue Reading How does Deseq2 deal with the row with zero when calculating size factors

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…

Continue Reading Genetic risk converges on regulatory networks mediating early type 2 diabetes

Organ-specific characteristics govern the relationship between histone code dynamics and transcriptional reprogramming during nitrogen response in tomato

A supply of nitrate triggers organ-specific changes of histone modifications at specific gene loci To investigate the organ specificity of dynamic histone modifications in response to N changes, we treated 3-week-old tomato seedlings (Solanum lycopersicum, cultivar M82) with four days of N starvation, followed by N-supply (2.8 mM NO3−; +N) or…

Continue Reading Organ-specific characteristics govern the relationship between histone code dynamics and transcriptional reprogramming during nitrogen response in tomato

A genome assembly for Orinus kokonorica provides insights into the origin, adaptive evolution and further diversification of two closely related grass genera

Jiao, Y. N. et al. Ancestral polyploidy in seed plants and angiosperms. Nature 473, 97–100 (2011). Article  PubMed  Google Scholar  Levin, D. A. Polyploidy and novelty in flowering plants. Am. Nat. 122, 1–25 (1983). Article  Google Scholar  Soltis, P. S. & Soltis, D. E. Ancient WGD events as drivers of…

Continue Reading A genome assembly for Orinus kokonorica provides insights into the origin, adaptive evolution and further diversification of two closely related grass genera

New Paper “Transformer-based tool recommendation system in Galaxy”

New BMC Bioinformatics Paper on “Transformer-based tool recommendation system in Galaxy” Abstract: Background: Galaxy is a web-based open-source platform for scientific analyses. Researchers use thousands of high-quality tools and workflows for their respective analyses in Galaxy. Tool recommender system predicts a collection of tools that can be used to extend…

Continue Reading New Paper “Transformer-based tool recommendation system in Galaxy”

Salpa genome and developmental transcriptome analyses reveal molecular flexibility enabling reproductive success in a rapidly changing environment

Loeb, V. et al. Effects of sea-ice extent and krill or salp dominance on the Antarctic food web. Nature 387, 897–900 (1997). Article  ADS  CAS  Google Scholar  Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature…

Continue Reading Salpa genome and developmental transcriptome analyses reveal molecular flexibility enabling reproductive success in a rapidly changing environment

WO2017055487A2 – A METHOD FOR DIAGNOSING A DISEASE BY DETECTION OF circRNA IN BODILY FLUIDS

“Current Protocols in Molecular Biology“, 1991, JOHN WILEY & SONS, pages: 6.3.1 – 6.3.6 “Quantitative monitoring of gene expression patterns with a complementary DNA microarray.“, SCIENCE, vol. 270, no. 5235, 1995, pages 467 – 70 ALTSCHUL ET AL., J. MOL. BIOL., vol. 215, 1990, pages 403 – 410 ALTSCHUL ET…

Continue Reading WO2017055487A2 – A METHOD FOR DIAGNOSING A DISEASE BY DETECTION OF circRNA IN BODILY FLUIDS

MSL2 ensures biallelic gene expression in mammals

Materials Animals All of the mice were kept in the animal facility of the Max Planck Institute of Immunobiology and Epigenetics. The mice were maintained under specific-pathogen-free conditions, with 2 to 5 mice housed in individually ventilated cages (Techniplast). The cages were equipped with bedding material, nesting material, a paper…

Continue Reading MSL2 ensures biallelic gene expression in mammals

How to do KEGG pathway analysis when I have a gene with multiple entrez IDs?

How to do KEGG pathway analysis when I have a gene with multiple entrez IDs? 0 Hello, I did DESeq2 on my samples and I have a list of DEGs that I would like to do kegg pathway analysis on. For DESeq2 I used biomart and tximport to assign external…

Continue Reading How to do KEGG pathway analysis when I have a gene with multiple entrez IDs?

Transformer-based tool recommendation system in Galaxy | BMC Bioinformatics

Kumar A, Rasche H, Grüning B, Backofen R. Tool recommender system in Galaxy using deep learning. GigaScience. 2021. doi.org/10.1093/gigascience/giaa152. Article  PubMed  PubMed Central  Google Scholar  The galaxy community: the galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Res 50(W1):W345-W35104 2022. (2022). doi.org/10.1093/nar/gkac247 Gil Y, Ratnakar…

Continue Reading Transformer-based tool recommendation system in Galaxy | BMC Bioinformatics

Generate Read counts from bam file

Generate Read counts from bam file 2 Currently i am working on a project related to LHON disease (rare mitochondrial disorder which leads to progressive visual loss). I have 9 RNA-seq fastq files out of which 3 are for carriers, 3 for affected and 3 for control. Data downloaded is…

Continue Reading Generate Read counts from bam file

p-value combination methods

A major problem in meta-analysis is combining p-values from different datasets, particularly in domains like genomics where high-dimensional data is frequently handled. Here’s a summary of how to use a negative binomial-generalized linear model (NB-GLM) in your case with RNA-seq data: First, individual analysis: Typically, you want to run the…

Continue Reading p-value combination methods

Comparing 3 Data Sets using DeSeq and Heatmaps

Hi all, I am new to bioinformatics analysis, so I’d appreciate if someone could check my code for the goal I am trying to achieve. I have 3 samples – Wild Type (WT) FoxP3-TCF-HEB (I have 3 replicates of this) TCFKO I have defined these in the sample information csv…

Continue Reading Comparing 3 Data Sets using DeSeq and Heatmaps

DEseq2 input

DEseq2 input 1 Hello Guys, @Michael Love I have a transcriptomics dataset and did rnaseq/nf-core pipeline by salmon-star. my output of the salmon-star folder is as follows: salmon.merged.gene_counts.tsv salmon.merged.gene_counts_length_scaled.tsv salmon.merged.gene_counts_scaled.tsv salmon.merged.gene_lengths.tsv salmon.merged.gene_tpm.tsv salmon.merged.transcript_counts.tsv salmon.merged.transcript_lengths.tsv salmon.merged.transcript_tpm.tsv tx2gene.tsv my question is: which one of these files should be an input for Deseq2…

Continue Reading DEseq2 input

multiple condition and time course in RNA-seq

In my experiment, I have three groups of plants: wild-type (WT), induced (IN), and uninduced (UN). These groups have been established to explore the effects of a specific gene, which I refer to as gene DM, that I can induce with ethanol (EtOH) treatment. The IN group is composed of…

Continue Reading multiple condition and time course in RNA-seq

Using DESeq2 statistical framework with to identify differentially expressed loci instead of genes

Using DESeq2 statistical framework with to identify differentially expressed loci instead of genes 0 @4b83ad99 Last seen 1 day ago Canada Hello, This question is crossposted from Biostars as I wasn’t sure which platform is the more appropriate one for asking it. I am studying the gene expression of a…

Continue Reading Using DESeq2 statistical framework with to identify differentially expressed loci instead of genes

Adipose cDC1s contribute to obesity-associated inflammation through STING-dependent IL-12 production

Ward, Z. J. et al. Projected U.S. state-level prevalence of adult obesity and severe obesity. N. Engl. J. Med. 381, 2440–2450 (2019). Article  PubMed  Google Scholar  Khaodhiar, L., McCowen, K. C. & Blackburn, G. L. Obesity and its comorbid conditions. Clin. Cornerstone 2, 17–31 (1999). Article  CAS  PubMed  Google Scholar …

Continue Reading Adipose cDC1s contribute to obesity-associated inflammation through STING-dependent IL-12 production

Complex design with a mixture of male and female mice

DEseq2 : Complex design with a mixture of male and female mice 0 @2bfe541c Last seen 4 hours ago France Hello everyone, I’m working on a scientific project that poses a particular problem. The experimental design includes 3 times and 2 conditions (WT and KO). Each time*condition has 3 mice….

Continue Reading Complex design with a mixture of male and female mice

Immune-privileged tissues formed from immunologically cloaked mouse embryonic stem cells survive long term in allogeneic hosts

Mice C57BL/6N (strain 005304), C3H/HeJ (strain 000659), FVB/NJ (strain 001800), BALB/cJ (strain 000651) and NSG mice (stock 005557) were purchased from the Jackson Laboratory. CD-1 (stock 022) mice were purchased from Charles River. Mice (6–20-week-old) of each strain/background were used for teratoma assays. Mice were housed in a pathogen-free facility…

Continue Reading Immune-privileged tissues formed from immunologically cloaked mouse embryonic stem cells survive long term in allogeneic hosts

High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2

Plasmid construction All the constructs used in this study were generated with standard cloning strategies, including PCR, overlapping PCR, oligo annealing, digestion and ligation. Primers were purchased from Genewiz. The plasmid sequence was verified by Sanger sequencing. The pCAG-spike(D614G)-GFP11-mCherry plasmid was modified from Addgene plasmid 158761. Briefly, GFP11 and mCherry…

Continue Reading High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2

DESeq2 estimateSizeFactors iterate takes too long

Hello, The data is related to my previous post. We decided to remove 3 genes from the sample count matrix as they were also present in negative controls in very high count. When running DESeq(dds), we got the following error – estimating size factors Error in estimateSizeFactorsForMatrix(counts(object), locfunc = locfunc,…

Continue Reading DESeq2 estimateSizeFactors iterate takes too long

Identifying differentially expressed loci for gene duplicates using DESeq2

Identifying differentially expressed loci for gene duplicates using DESeq2 0 Hello, I am studying the gene expression of a species that has undergone a duplication event. I have a synteny table of gene duplicates for multiple tissue types, which was derived using the genome of a related ancestral species (that…

Continue Reading Identifying differentially expressed loci for gene duplicates using DESeq2

Functional filter for whole-genome sequencing data identifies HHT and stress-associated non-coding SMAD4 polyadenylation site variants >5 kb from coding DNA

Summary Despite whole-genome sequencing (WGS), many cases of single-gene disorders remain unsolved, impeding diagnosis and preventative care for people whose disease-causing variants escape detection. Since early WGS data analytic steps prioritize protein-coding sequences, to simultaneously prioritize variants in non-coding regions rich in transcribed and critical regulatory sequences, we developed GROFFFY,…

Continue Reading Functional filter for whole-genome sequencing data identifies HHT and stress-associated non-coding SMAD4 polyadenylation site variants >5 kb from coding DNA

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…

Continue Reading Limma/DESeq2 for unbalanced nested design (paired samples)

Help doing differential expression analysis -experimental design and gProfiler TF interpretation-

Help doing differential expression analysis -experimental design and gProfiler TF interpretation- 0 Hi! I’m trying to do a differential expression analysis using breast cancer TCGA data. Firstly, I split the breast cancer cohort into two groups based on the expression level in z-score of a particular gene I’m interested in,…

Continue Reading Help doing differential expression analysis -experimental design and gProfiler TF interpretation-

Comparison of single clinical sample to 4 normals using tumour cohort to infer dispersion of single sample

DESeq2: Comparison of single clinical sample to 4 normals using tumour cohort to infer dispersion of single sample 1 @e3bc7671 Last seen 54 minutes ago United Kingdom Hello, This is a question related to RNAseq expression and the need to extract biologically relevant results at single patient level. For context,…

Continue Reading Comparison of single clinical sample to 4 normals using tumour cohort to infer dispersion of single sample

Deseq2 5 level condition – building contrast

Deseq2 5 level condition – building contrast 0 Hello I need your help with my analysis. So i have an bulk Rna-seq dataset which contains data from ips cells which develop into neurons in 5 days For each time point I have 7 replicates So now with deseq2 I have…

Continue Reading Deseq2 5 level condition – building contrast

Salmon (or other pseudo-mappers) for multi-species RNAseq read filtering

Hello all, Background: I’ve inherited a new RNAseq data set and am thinking about updating my approaches (last time I did this I was using HISAT and Cuffdiff). I’d like some opinions on best strategies to disentangle/filter out parasite microbe reads from infected host reads before preforming a differential gene…

Continue Reading Salmon (or other pseudo-mappers) for multi-species RNAseq read filtering

Functional convergence of genomic and transcriptomic architecture underlies schooling behaviour in a live-bearing fish

Krause, J. & Ruxton, G. D. Living in Groups (Oxford Univ. Press, 2002). Réale, D., Reader, S. M., Sol, D., McDougall, P. T. & Dingemanse, N. J. Integrating animal temperament within ecology and evolution. Biol. Rev. 82, 291–318 (2007). Article  PubMed  Google Scholar  Gartland, L. A., Firth, J. A., Laskowski,…

Continue Reading Functional convergence of genomic and transcriptomic architecture underlies schooling behaviour in a live-bearing fish

A single pseudouridine on rRNA regulates ribosome structure and function in the mammalian parasite Trypanosoma brucei

Cell growth and transfections Procyclic form (PCF) T. brucei, strain 29-1354, which carries integrated genes for the T7 polymerase and the tetracycline repressor, was grown in SDM-79 medium supplemented with 10% fetal calf serum, in the presence of 50 μg/ml hygromycin. Cells were grown in the presence of 15 μg/ml G418 for…

Continue Reading A single pseudouridine on rRNA regulates ribosome structure and function in the mammalian parasite Trypanosoma brucei

Intrinsic deletion at 10q23.31, including the PTEN gene locus, is aggravated upon CRISPR-Cas9-mediated genome engineering in HAP1 cells mimicking cancer profiles

Introduction The CRISPR-Cas system is a widely used genome engineering technology because of its simple programmability, versatile scalability, and targeting efficiency (Wang & Doudna, 2023). Although researchers are rapidly developing CRISPR-Cas9 tools, the biggest challenge remains to overcome undesired on- and off-targeting outcomes. Previous studies have reported unintended genomic alterations,…

Continue Reading Intrinsic deletion at 10q23.31, including the PTEN gene locus, is aggravated upon CRISPR-Cas9-mediated genome engineering in HAP1 cells mimicking cancer profiles

coupling Cufflinks results with RSEM

coupling Cufflinks results with RSEM 0 Hello! I am opening this post to ask if I can use the transcript-level assembly obtained with Cufflinks (using a reference genome) to independently quantify the abundance levels of these sequences with RSEM (transcript-level quantification), specifically designed to quantify isoforms. Subsequently, I would perform…

Continue Reading coupling Cufflinks results with RSEM

Three questions about datasets

Three questions about datasets 2 Hello, I have three questions about Rna-seq and datasets: Is it fine to combine datasets? Suppose I am doing a project comparing control tongue epithelial tissue vs. tumor tongue epithelial tissue through DESEQ2 analysis. I have 5 control sra files from one experiment and 5…

Continue Reading Three questions about datasets

Batch effect correction between Bulk RNA-Seq and scRNA-Seq’s clusters

Batch effect correction between Bulk RNA-Seq and scRNA-Seq’s clusters 1 Hello, I need to compare some samples from different bulk RNA-Seq with some clusters of a scRNA-Seq (not whole sample) to find DEGs. We have undifferentiated samples performed by bulk RNA-Seq and fully differentiated samples (mature ones) are 2-3 clusters…

Continue Reading Batch effect correction between Bulk RNA-Seq and scRNA-Seq’s clusters

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 %*%…

Continue Reading Predicting missing values splines DESeq2

Installation of DESeq2 package while utilizing free Posit cloud – General

Help! I’m trying to install DEseq2 to perform differential gene expression analysis R Studio. I’m using the free R Studio on Posit Cloud. R Sudio version is 4.3.2, BiocManager is 3.1.8. This is my issue with the error: library(BiocManager)Bioconductor version 3.18 (BiocManager 1.30.22), R 4.3.2 (2023-10-31)BiocManager::install(“DESeq2”)‘getOption(“repos”)’ replaces Bioconductor standard repositories,…

Continue Reading Installation of DESeq2 package while utilizing free Posit cloud – General

DESeq2 installation failures

DESeq2 installation failures 0 Help! I’m trying to install DEseq2 to perform differential gene expression analysis R Studio. I’m using the free R Studio on Posit Cloud. R Sudio version is 4.3.2, BiocManager is 3.1.8. This is my issue with the error: library(BiocManager) Bioconductor version 3.18 (BiocManager 1.30.22), R 4.3.2…

Continue Reading DESeq2 installation failures

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…

Continue Reading Transgenerational epigenetic effects imposed by neonicotinoid thiacloprid exposure

Primate-specific ZNF808 is essential for pancreatic development in humans

Subjects The study was conducted in accordance with the Declaration of Helsinki and all subjects or their parents/guardian gave informed written consent for genetic testing. DNA testing and storage in the Beta Cell Research Bank was approved by the Wales Research Ethics Committee 5 Bangor (REC 17/WA/0327, IRAS project ID…

Continue Reading Primate-specific ZNF808 is essential for pancreatic development in humans

Downstream analysis with DEseq2 normalization

Downstream analysis with DEseq2 normalization 0 Hi All, I am trying to integrate RNA-seq with Proteomics dataset. I used the DEseq2 for normalization dataset. I have 2 questions for next step: I aim to compute z-score for RNA-seq data. I understand that the normalization from DEseq2 does not take the…

Continue Reading Downstream analysis with DEseq2 normalization

Normalization function in DEseq2

Normalization function in DEseq2 1 Hi all, I am try to work with normalization count data using DEseq2. I am trying their tutorial, until the normalization part. dds <- estimateSizeFactors(dds) There are different output from their code: counts(dds, normalized=TRUE) with when I compute manually: counts(dds, normalized=FALSE) / sizeFactors(dds) The author…

Continue Reading Normalization function in DEseq2

Does DESeq2 correct for library size when importing the counts with DESeqDataSetFromMatrix?

Does DESeq2 correct for library size when importing the counts with DESeqDataSetFromMatrix? 0 Hello, I normally run DESeq2 by importing the data with tximport. However, this time I was given a counts csv file and imported the counts with DESeqDataSetFromMatrix. I noticed that when I create the dds object with…

Continue Reading Does DESeq2 correct for library size when importing the counts with DESeqDataSetFromMatrix?

Diffbind low p-value but high FDR

Diffbind low p-value but high FDR 0 I guess my issue is related to this post support.bioconductor.org/p/85487/#85490. Here is the dba.report(DBA,th=1, bCounts=TRUE) results. One of the peaks clearly shows a significant difference in IGV (And we also expected it to be changed) and has a small p.vaule but the FDR…

Continue Reading Diffbind low p-value but high FDR

Deconvolution using cibersortx, help with real example

Hello Biostars, I have been stuck on an issue for quite some time now, and I hope someone can help me or point me in the right direction. I’ve received my bulk RNA fastq files and analyzed it in R using DESeq2. I have found an article that provide snRNA-seq…

Continue Reading Deconvolution using cibersortx, help with real example

DESeq2 and determining effects of treatment on a priori/candidate genes from a bulk-RNAseq experiment

DESeq2 and determining effects of treatment on a priori/candidate genes from a bulk-RNAseq experiment 0 @724e8e11 Last seen 3 hours ago Australia Hi everyone, first time poster. I have resorted to this because I can’t seem to find substantive answers to my question (or don’t exactly fit my question), nor…

Continue Reading DESeq2 and determining effects of treatment on a priori/candidate genes from a bulk-RNAseq experiment

DESeq2 design with unbalance data and a multifactor design

Dear all, I am doing a DGEA with DESeq2 and data imported with tximport. I have an unbalanced dataset as reported below. With the counts and the metadata that I have I would like to answer different questions. I would like to look at the differential expressed genes between the…

Continue Reading DESeq2 design with unbalance data and a multifactor design

Single-cell CRISPR screens in vivo map T cell fate regulomes in cancer

Mice The research conducted in this study complied with all of the relevant ethical regulations. The animal protocols were approved by and performed in accordance with the Institutional Animal Care and Use Committee of St. Jude Children’s Research Hospital. C57BL/6, OT-I50, pmel51 and Rosa26-Cas9 knock-in52 mice were purchased from The…

Continue Reading Single-cell CRISPR screens in vivo map T cell fate regulomes in cancer

DESeq2 with unbalanced dataset and multifactor design

Dear all, I am doing a DGEA with DESeq2 and data imported with tximport. I have an unbalanced dataset as reported below. With the counts and the metadata that I have I would like to answer different questions. I would like to look at the differential expressed genes between the…

Continue Reading DESeq2 with unbalanced dataset and multifactor design

Help understanding DESEq2 and nbinomWaldTest

Help understanding DESEq2 and nbinomWaldTest 0 Hi, I just want to understand first, when you put confounders in your DESeq object model, are they regressed out or just accounted for. Second, why is the nbinomwald test used when in DESeq2 is already is getting you log2 fold changes with p…

Continue Reading Help understanding DESEq2 and nbinomWaldTest

Bioconductor – DESeq2 (development version)

DOI: 10.18129/B9.bioc.DESeq2   This is the development version of DESeq2; for the stable release version, see DESeq2. Differential gene expression analysis based on the negative binomial distribution Bioconductor version: Development (3.19) Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model…

Continue Reading Bioconductor – DESeq2 (development version)

Bioconductor – CAGEr

DOI: 10.18129/B9.bioc.CAGEr     This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see CAGEr. Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining Bioconductor version: 3.9 Preprocessing of CAGE sequencing data, identification and…

Continue Reading Bioconductor – CAGEr

Same sequencing sample in multiple lanes. How to analyse it?

Same sequencing sample in multiple lanes. How to analyse it? 1 Hi, I have the following samples: Lane 1: 184631_S1_L001_trimmed_R1.fastq 184631_S1_L001_trimmed_R2.fastq Lane 2: 184631_S1_L001_trimmed_R1.fastq 184631_S1_L001_trimmed_R2.fastq I would like to align these fastq files to the reference library. Bowtie2 is the tool I am using. As you can see, the same…

Continue Reading Same sequencing sample in multiple lanes. How to analyse it?

rna seq – How to incorporate negative controls in DESeq2

We are doing a comparison between two outcomes (positive and negative). We could not have any positive controls as we do not have any “control” data to set as baseline, either from literature or otherwise. No spike-ins have been used. We have some samples which had no resolved outcome, hence…

Continue Reading rna seq – How to incorporate negative controls in DESeq2

filtering lowly expressed exons

filtering lowly expressed exons 0 To reduce false positive testing in differential expression, genes with zero or low counts are pre-filtered. I’m wondering what the equivalent is for this with DEXSeq. the ‘minCount’ argument in estimateDispersions does not work with the latest available release (3.18) on bioconductor. It’s also recommended…

Continue Reading filtering lowly expressed exons

The Imageable Genome | Nature Communications

For the Imageable Genome project, we developed a data pipeline that identifies texts containing radiotracers, recognizes and extracts names of radiotracers from texts, filters for clinically relevant radiotracers and their associated targets, and translates protein names, i.e. of radiotracer targets, to names of the coding genes. We then downloaded the…

Continue Reading The Imageable Genome | Nature Communications

DESeq2 for microbiome data: raw counts or percentages?

DESeq2 for microbiome data: raw counts or percentages? 1 @antonkratz-8836 Last seen 9 hours ago Japan, Tokyo, The Systems Biology Insti… Given an OTU table (rows are microbiota and columns are samples) and I want to compare treatment vs placebo sample groups using DESeq2. It is not clear to me…

Continue Reading DESeq2 for microbiome data: raw counts or percentages?

DESEQ2 design in DESeqDataSetFromMatrix: cell and treatment

DESEQ2 design in DESeqDataSetFromMatrix: cell and treatment 0 Hello, I have RNAseq coming from CDX models that were treated with DMSO and another compound (condition). I have 12 CDX models in total, 6 were implanted with cell1 (4 DMSO, 2 treated) and 6 with cell2 (3DMSO, 3 treated). I would…

Continue Reading DESEQ2 design in DESeqDataSetFromMatrix: cell and treatment

Bioconductor – GenomicRanges

    This package is for version 2.14 of Bioconductor; for the stable, up-to-date release version, see GenomicRanges. Representation and manipulation of genomic intervals Bioconductor version: 2.14 The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyze high-throughput sequencing…

Continue Reading Bioconductor – GenomicRanges

Effect of Bootstrapping/Gibbs Sampling in Salmon Counts

Effect of Bootstrapping/Gibbs Sampling in Salmon Counts 2 Hi Everyone, I am a bit confused about the difference between Gibbs Sampling and Bootstrapping when it comes to Salmon and how these procedures affect downstream analysis. For context, I am trying to do analysis of 49 matched cancer vs. normal RNAseq…

Continue Reading Effect of Bootstrapping/Gibbs Sampling in Salmon Counts

Bioconductor – phyloseq

DOI: 10.18129/B9.bioc.phyloseq     Handling and analysis of high-throughput microbiome census data Bioconductor version: Release (3.6) phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data. Author: Paul J. McMurdie <joey711 at gmail.com>, Susan Holmes <susan at stat.stanford.edu>, with…

Continue Reading Bioconductor – phyloseq

DESeq2 interaction between one continuous variable and one categorical variable

DESeq2 interaction between one continuous variable and one categorical variable 0 @02d6ef77 Last seen 13 hours ago Singapore Hello, I’m new in RNA-seq analysis and would like to seek some guidance on the data analysis. My experiment design has two variables “Concentration” and “Addition”. I have 8 samples in total….

Continue Reading DESeq2 interaction between one continuous variable and one categorical variable

Biological and genetic characterization of a newly established human external auditory canal carcinoma cell line, SCEACono2

Ethic statement The Clinical Research Ethics Review Committee of Kyushu University Hospital approved the study (permit no. 29-43, 30-268, and 700-00). Written informed consent for the current research project was obtained before the tumor tissue, and a blood sample were harvested. This study was also conducted according to the principles…

Continue Reading Biological and genetic characterization of a newly established human external auditory canal carcinoma cell line, SCEACono2

Transcriptomic analysis reveals that RasGEF1b deletion alters basal and LPS-induced expression of genes involved in chemotaxis and cytokine responses in macrophages

Rojas, J. M. & Santos, E. Ras-Gefs and Ras Gaps. In RAS Family GTPases Vol. 4 (Springer, 2006). Google Scholar  Broek, D. et al. The S. cerevisiae CDC25 gene product regulates the RAS/adenylate cyclase pathway. Cell 48, 789–799 (1987). Article  CAS  PubMed  Google Scholar  van Dam, T. J. P., Rehmann,…

Continue Reading Transcriptomic analysis reveals that RasGEF1b deletion alters basal and LPS-induced expression of genes involved in chemotaxis and cytokine responses in macrophages