Tag: PCA

Hi there, I’m doing my first experiments with PCA and UMAP as dimensionality reductions to visualize a dataset I’ve been working on. Basically, I used the samples from the SGDP which I then mapped on the human pangenome for, finally, calling small variants with DeepVariant. I moved on with some…

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…

CRISPR/Cas9-induced homozygous knockout of nexn causes progressive cardiac dysfunction without affecting skeletal muscle function in zebrafish Several studies in different animal models and cardiomyopathy patients have shown that loss of NEXN is leading to DCM which is characterized by an impaired contractility of the heart6,10,12. Homozygous loss of NEXN mostly…

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…

Lung cancer ICB cohort Advanced non-small cell lung carcinoma patients who were treated with anti-PD-1/PD-L1 monotherapy at Samsung Medical Center, Seoul, Republic of Korea were enrolled for this study. The present study has been reviewed and approved by the Institutional Review Board (IRB) of the Samsung Medical Center (IRB no….

In this tutorial we walk through a typical single-cell RNA-seq analysis using Bioconductor packages. We will try to cover data from different protocols, but some of the EDA/QC steps will be focused on the 10X Genomics Chromium protocol. We start from the output of the Cell Ranger preprocessing software. This…

Ornamental plants, valued for their varied morphological characteristics, are increasingly used in urban greening initiatives such as rooftop greening. But this application presents challenges like limited soil depth and no irrigation, requiring plants such as the Phedimus species, known for their resilience to these conditions. Current research focuses on understanding the genetic…

Introduction Skin cutaneous melanoma (SKCM), as one of the most aggressive types of cancer due to its elevated degree of heterogeneity, has gained increasing attention during the past few decades.1 Also known as “the cancer that rises with the sun”,2 melanoma originates from cancerous melanocytes due to molecular or genetic…

Article Summary Box Efficient data preparation in RStudio hinges on automated data cleaning techniques, significantly reducing manual errors and streamlining the initial stages of analysis. Vectorized operations and the apply() family functions in RStudio dramatically enhance data manipulation efficiency, especially for large datasets. Utilizing multiple linear regression and PCA in…

Mouse breeding and husbandry All experimental procedures related to the use of mice were approved by the Institutional Animal Care and Use Committee of the AIBS, in accordance with NIH guidelines. Mice were housed in a room with temperature (21–22 °C) and humidity (40–51%) control within the vivarium of the AIBS…

Dynamic mRNA signatures in the early phase of epileptogenesis after Pilocarpine-induced SE To decipher transcriptional changes early after pilocarpine-induced SE in the hippocampal CA1 subfield, we compared mRNA expression profiles of pilocarpine-induced SE animals and non-SE controls in hippocampal CA1 at five different time points, i.e. 6, 12, 24, 36…

Identification of DRGs in PCa Figure 1a showed the flow chart of this study. To explore the role of DRGs in PCa, we analyzed the gene expression profiles of these 15 DRGs in PCa patients. As shown in Fig. 1b, for ACTN4, TLN1, IQGAP1, CD2AP, FLNA, MYH9, MYL6, and ACTB genes, the…

Chuo University’s Professor Y-h. Taguchi places focus on drug repositioning using multiple gene expression profiles In my previous manuscripts (1-3), I introduced our studies of in silico drug repositioning using gene expression profiles. Nevertheless, in these studies, we could use the single gene expression profile to perform in silico drug…

Mouse brain tissues All experimental procedures using live animals were approved by the Salk Institute Animal Care and Use Committee under protocol number 18-00006. Adult (P56) C57BL/6J male mice were purchased from the Jackson Laboratory at 7 weeks of age and maintained in the Salk animal barrier facility on 12-h dark–light…

Collection and handling of biospecimens obtained from participants in the randomized controlled clinical study of the efficacy of MDCF-2 The human study entitled ‘Community-based clinical trial with microbiota-directed complementary foods (MDCFs) made of locally available food ingredients for the management of children with primary moderate acute malnutrition (MAM)’ was approved…

Help me confirm if my reads are properly normalized and transformed or do I need to re-do 0 Hello, can you help me confirm whether or not my reads dataset were normalized properly prior to my work on them? The data source is 40 florets from Arabidopsis for 3 replicates…

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…

Hi. I have two different phenotypes to run GWAS quantitative analysis (–glm), which are bmi and hdl.  As for input, I have input phenotype file, genotype file and covariate file. The special circumstance here is that I have different number of participants for each different phenotype, meaning that some participants…

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…

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, cmdcolin, and was edited by…

Supervised Learning Platforms Supervised learning is a popular approach in machine learning where algorithms are trained on labeled data to make predictions or classify new data. These platforms provide a comprehensive set of tools and frameworks to enable developers and data scientists to build and deploy supervised learning models with…

What is a Machine Learning Engineer? A machine learning engineer is a trained professional who combines expertise in computer science, mathematics, and statistics to develop and implement machine learning models and algorithms. Machine learning engineers play a crucial role in the field of artificial intelligence, as they design systems that…

Hi everyone, When I started my analysis, I merged 3 samples. merged_seurat <- merge(x = PC9_1_raw_feature_bc_matrix, y = c(PC9_2_raw_feature_bc_matrix, PC9_3_raw_feature_bc_matrix), add.cell.id = c(“PC9_1”, “PC9_2”, “PC9_3”)) After cell filtering, I checked the cell cycle and batch effects (no batch effect, I won’t do integration). I split my Seurat object to do…

Username or Email Password Forgot your password? Sign In Cancel by RStudio Sign in Register Using Hierarchical Clustering & PCA for Market Segmentation and Targeting by davian rosales Last updated about 2 hours ago Hide Comments (–) Share Hide Toolbars × Post on: Twitter Facebook Google+ Or copy & paste…

Scanpy Pearson residual PCA error 2 I got a ValueError: Input contains NaN, infinity or a value too large for dtype(‘float32’). when trying to run this part of the code sc.pp.pca(adata, n_comps=50) n_cells = len(adata) sc.tl.tsne(adata, use_rep=”X_pca”) Not sure if the cause of error is becauseI I merge 4 10x…

Clinical features of WMI and nWMI groups From April 2022 to December 2022, the Affiliated Hospital of Guangdong Medical University enrolled a total of 83 subjects who met the inclusion criteria. The study finally included 71 cases after excluding 4 deaths, 6 patients who failed to complete MRI + DTI testing, 1…

Best way to normalize transcript reads data for PCA & correlation and further biostat analysis 0 Hello all, I would like your advice on how to normalize, a Log2 normalized values of transcripts from DEGs flowerets in eight consecutive stages of development across, each stage has 3 biological replicates with…

Machine Learning Engineer(3-7 years) Job in Quantiphi at Other Karnataka -Job Description #13562502 – Shine.com Hi Job Details About Us Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine & realize transformational opportunities at the heart of the business. We are passionate about our customers…

B cells undergo a series of programmed genomic alterations that enable the immunoglobulin light and heavy chain loci to generate high-affinity antibodies against invading pathogens. First, B cells undergo variability, diversity and joining (VDJ) recombination in the bone marrow with subsequent somatic hypermutation (SHM) and class switch recombination (CSR) occurring…

Introduction Leprosy is a disabling infectious disease that predominantly occurs in the skin and peripheral nerves and is transmitted by contact with pathogenic bacteria through the respiratory tract and broken skin. Leprosy is attributed to infection with Mycobacterium leprae (M. leprae)1 and the more recently discovered Mycobacterium lepromatosis.2 In addition,…

Dimensionality reduction on data sets with variable dimensions 1 My lab has some RNA secondary structure data on a number of virus RNA segments from a method called SHAPE-MaP, which gives each nucleotide in a sequence a reactivity value. We would like to make a 2D plot that clusters segments…

A novel collection of genomes from Cabinda, Angola and Maputo, Mozambique Genomic DNA was extracted using saliva samples collected with informed consent and sequenced using the Illumina HiSeq X™ platform to an average autosomal read depth of ~12X from 300 individuals sampled in Cabinda and 50 individuals sampled in Maputo…

Global impact of music on the human transcriptome We first aimed at quantifying the global effect of music on the transcriptomes of the two groups of donors separately. ACD patients exposed to music showed 2.3 times more DEGs (n = 2605) than controls (n = 1148); Table 2. Moreover, while the proportion up-regulated/down-regulated DEGs…

Identification of the SKCM necroptosis cluster The comprehensive analysis encompassed a total of 803 patients drawn from five distinct melanoma cohorts, namely, TCGA-SKCM, GSE65094, GSE53118, GSE54467, and GSE19234. Employing an unsupervised clustering algorithm, we stratified melanoma patients based on their NRG expression profiles. This facilitated a deeper exploration of the…

Introduction to RStudio R is widely used in quantitative finance due to its extensive statistical capabilities, data manipulation tools, and its active community that develops and maintains specialized packages for finance. It offers a wide range of functionalities that enable professionals in the finance industry to analyze data, build models,…

CircRNAs are widely found in eukaryotes and are a class of abundantly expressed, highly tissue-specific, and stable non-coding RNAs that have an essential role in regulating gene expression12. The abnormal expression of circRNAs has been reported in esophageal squamous cell carcinoma13, breast carcinoma14, gastric cancer15, and hepatocellular carcinoma16, which are…

Apologise for many posts this weeks. I am wondering in seurat, should I scale all genes for downstream analysis or just some features is okay? I am a bit unclear when it comes to scaling…. I have attached the code here. Also, how do I know which genes are noise/confounding…

Reagents miRNeasy Serum/Plasma Advanced Kit (Qiagen, Hilden, Germany, # 217204); TaqMan® Advanced miRNA cDNA Synthesis Kit (Applied Biosystems, Bedford, MA, USA, #A28007); TaqMan® Fast Advanced Master Mix (Applied Biosystems, Bedford, MA, USA, # 4444556); TaqMan® Advanced miRNA Assays Single-tube assays (Applied Biosystems, Bedford, MA, USA, # A25576: 478293_mir, Spike-In cel-miR-39-3p;…

Overview The Kenyan sequences were classified into 161 distinct RV types, of which 157 were known, and four types were unassigned, i.e., they did not meet the proposed threshold to any prototype strain. The countrywide study had the highest number of distinct types (n = 114), followed by the Kilifi HDSS (n = 78),…

Representation learning is the task of learning the most salient features in a given dataset by a deep neural network. It is usually an implicit task done in a supervised learning paradigm, and it is a crucial factor in the success of deep learning (Krizhevsky et al., 2012; He et…

SNPRelate: Parallel computing toolset for relatedness and principal component analysis of SNP data ====  [GNU General Public License, GPLv3](http://www.gnu.org/copyleft/gpl.html) [](http://www.bioconductor.org/packages/release/bioc/html/SNPRelate.html) [](http://www.bioconductor.org/packages/release/bioc/html/SNPRelate.html) [](https://github.com/zhengxwen/SNPRelate/actions/workflows/r.yml) ## Features Genome-wide association studies are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed SNPRelate (R…

Image generated with DALLE-3   Machine learning is becoming increasingly popular in the data space. But there’s often a notion that to become a machine learning engineer you need to have an advanced degree. This, however, is not completely true. Because skills and experience trump degrees, always. If you’re reading…

Hi, I am attempting to use the PCAtools R package. I have imported my own data matrix (pca.matrix) and metadata (metadata) files. When just running this code, everything works great and I get plots: p <- pca(pca.matrix, removeVar = 0.1) — removing the lower 10% of variables based on variance…

Doxo and Abe promote cellular senescence accompanied by an altered profile of senescence-related genes in breast cancer cells Doxo and Abe were used to treat breast cancer cells (human triple-negative breast cancer cell line MDA-MB-231 and human luminal A subtype breast cancer cell line MCF-7) for 24 h, without a robust…

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,…

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,…

Phenotype imputation increases effective sample size We focused on the deepest available measure of MDD in UK Biobank11, LifetimeMDD, which we derived by applying clinical diagnostic criteria in silico to MDD symptom data from the Patient Health Questionnaire 9 (PHQ9) and the Composite International Diagnostic Interview Short Form (CIDI-SF) in…

Unexpected separation of RNA-seq samples on PCA plot 0 Hello Biostars, I have been dealing with an interesting issue regarding 9 RNA-seq green algae samples. These samples come from three conditions, each having 3 biological replicates. To remove rRNA from the samples, rRNA was depleted with varying success in order…

How to remove batch effect in RNA-seq using control samples? 0 Hello, I recentrly started comparing two RNA-seq data from different conditions (vecle control vs treatment). Unfortunately, they were preped by different researches and also measured at different dates, so they have fuge batch effects, as seen in the PCA…

Clinical characteristics of study participants A total of 121 participants were included in the final analyses and were divided into three groups: healthy (n = 44), acute (n = 41), and remission (n = 39). First, the baseline demographic and clinical characteristics of this study are presented in Table 1. The results showed no statistical differences among…

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…

fastest UMAP method 5 I am trying to generate a Uniform Manifold Approximation and Projection (UMAP) for about 300,000 observations of 36 variables. So far I have been using the umap package in R but this seems prohibitively slow (for exploratory analyses and parameter optimisation). Can someone recommend an alternative…

Currently im doing image embedding visualisation and I want to use Tensorboard Projector PCA and T-SNE to see the image embedding similarity. I follow a website code to do the visualisation but I am unable to make the expected visualisation where the same images should clump together but it just…

Both MPH and ATX increase the locomotor activity of wild-type Drosophila To investigate the cell type-specific molecular mechanisms of ADHD drugs in the brain at single-cell resolution, we conducted behavioral experiments and scRNASEQ in wild-type (WT) adult male Drosophila melanogaster following exposure to MPH, ATX, and control treatment. Here, we…

This is great, thank you! Will this information be included in the PLINK2 documentation? The successful run we had included the log below. In the “Projecting random vectors” line, 21 steps are described, rather than the number 20 of requested principal components. I assume this is part of how the…

mRNA expressions of DDR-related genes are upregulated in CRPC compared to those in Pca To identify a cluster of upregulated genes in CRPC, we previously conducted directional RNA-seq analysis using clinical samples obtained from localized Pca and CRPC patients21. We used RNA samples obtained from prostate cancer patients by radical…

Unlocking the power of AI: How vector databases drive today’s technological revolution. The ability to analyze vast amounts of data is crucial in the field of artificial intelligence. For many decades, traditional databases have served as the foundation of information systems for storing and retrieving data. They have been the…

Female Asmt ft/ft mice exhibits anxiety- and depression-like behaviors We first examined the anxiety- and depression-like behaviors in mice. Our results showed that female Asmtft/ft mice had less distance in center (p < 0.001) and a smaller number of poking (p < 0.05) in the open field test (OFT, Fig. 1a–c). In the forced swim…

Is my data too noisy for DESeq? Should I model noise as unwanted variation? 0 I am trying to relate a factor (sensitivity) to gene expression. I have ~40 samples of breast cancer, each a different cell line, from a few lung cancer subtypes. When I model my known clinical…

help with weird PCA? (vcfR) 0 Hi everyone, very new to bioinformatics I have a SNP datasheet (.vcf) that I tried to make a PCA graph with using Rstudio (vcfR package) and it gave me interesting clustering. I then tried to filter the dataset using vcftools in Linux terminal (missing…

Summary DescriptionPrincipal component analysis (PCA) based on mitochondrial DNA (mtDNA) haplogroup frequencies of ancient and present-day Eurasian populations.png English: Principal component analysis (PCA) based on mitochondrial DNA (mtDNA) haplogroup frequencies of ancient and present-day Eurasian populations Date 5 November 2023 Source Ancient Mitochondrial Genomes Reveal Extensive Genetic Influence of the…

Seurat: Visualize individual cell clusters colored by meta.data variable 0 Hello, I am analyzing a public scRNA dataset using Seurat. My goal is to observe variation inside individual cell clusters according to a condition (e.g. the diet) in a visual way using a dimensional reduction plot, e.g. observing sub-clusters of…

Just a quick update – I used PLINK2.0 which allowed me to pass through the public1.bim file but now there is a problem with the public.fam file. (C) 2005-2023 Shaun Purcell, Christopher Chang   GNU General Public License v3Logging to public1_filtered.log.Options in effect:   –bfile public1  –extract snp_ids_only.txt  –make-bed  –out…

help with weird PCA? (vcftools, Rstudio (vcfR) 0 Hi everyone, very new to bioinformatics I have a SNP datasheet (.vcf) that I tried to make a PCA graph with using Rstudio (vcfR package) and it gave me interesting clustering. I then tried to filter the dataset using vcftools in Linux…

Hello, I am encountering an issue with the “Graphics API version mismatch” error when using the DESeq2 package in RStudio on Ubuntu 22.04. The error occurs when attempting to save plots using ggplot2 (ggsave) within DESeq2 functions like plotPCA. I have thoroughly investigated this issue, including checking package versions, graphics…

slingshot analysis on PCA but visualization on UMAP 1 Hi Bio-community, I am using slingshot for TI. I am wondering If I can use PCA as reducedDim argument in the slingshot function and for visualization the UMAP in embedCurves? Since I am getting biologically more reasonable results, if working in…

In a recent article published in the journal Development, researchers investigate the role of the ACTL7B gene in sperm formation using Actl7b-deficient mice. Study: Actl7b deficiency leads to mislocalization of LC8 type dynein light chains and disruption of murine spermatogenesis. Image Credit: Komsan Loonprom / Shutterstock.com Background ACTL7B, a testis-specific actin-related protein (Arp), shares up to…

Comment: Accounting for Batch effect reduces DEGs drastically by rohitsatyam102 &utrif; 20 I might have missed out one detail which might actually be relevant now that I revisited my code. Previously using old reference genome GRC… Comment: Accounting for Batch effect reduces DEGs drastically by rohitsatyam102 &utrif; 20 I don’t…

Ethics approval and consent to participate The study was approved by the Human Research Ethics Committees of the Children’s Hospital of Soochow University (Reference 2020CS017). All specimens were collected according to the guidelines set by the Children’s Hospital of Soochow University. All authors confirm that all methods were performed in…

deal with PCA and my samples 0 Hello everyone, I am writing to inquire about my PCA plot following the meta-analysis of three PCOS studies. I am concerned about the proximity of some normal samples to the PCOS samples in my PCA plot. I would like to understand whether this…

Harmony with PHATE 0 Hi Bio-community, I integrated my single cell dataset using Harmony. Now Harmony only provides a new slot for the cell.embeddings in the seurat object, like pca. How can I utilize this embedding in a PHATE plot? How can I combine Harmony with PHATE? Best, Tolga Phate…

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid cancer, constituting approximately one third of all cases [1]. Although immunochemotherapy cures ~60–75% of patients, a significant proportion of patients still experience relapse [2, 3]. Relapsed DLBCL patients have poor outcomes, with a median overall survival of only 6.3 months…

Global changes of the transcriptome during postnatal muscle growth The number of myofibers is thought to remain fixed following birth, muscle fiber hypertrophy growth is the primaryway of muscle growth. The average CSA is generally used to measure the hypertrophy of skeletal muscle fibers. To systematically identify the growth of postnatal…

Rename of assays for SingleCellExperiment object in R 1 Hi, I would like to ask a question related to the renaming of assays for the SingleCellExperiment object in R. My data as below: cortex_sc class: SingleCellExperiment dim: 30535 6460 metadata(9): Integrated_colors category2_colors … pca umap assays(2): **X** logcounts rownames(30535): MIR1302-2HG…

library(ggplot2) library(dplyr) plot_covariance_pca <- function(data, group_var) { “”” This function takes a data frame and a grouping variable as arguments and plots the covariance matrix as PCA with ggplot2 colors by group. Parameters: data (data.frame): The data frame containing the variables for the covariance matrix group_var (character): The name of…

Single-cell RNA sequencing reveals cellular heterogeneity among young and aged lungs post-influenza infection In order to investigate age-induced alterations in the host response to influenza A virus (IAV) infection, we infected groups of three young (16–18-week-old) and three aged (80–82-week-old) female C57Bl/6 mice intranasally with 50 PFU of the PR8…

Introduction Trafficking of proteins, lipids, and other molecules between cellular compartments is carried out by vesicular carriers. Material destined for transfer is packaged into a small trafficking vesicle at the donor compartment; the vesicle must then travel to its destination, before fusing with the target compartment to deliver the material…

Models for single-cell ATAC-seq data In single-cell ATAC-seq data, \(x_{ij}\) is the number of unique reads mapping to peak or region j in cell i. Although \(x_{ij}\) can take non-negative integer values, it is common to “binarize” the accessibility data (e.g., [19, 74, 133,134,135]), meaning that \(x_{ij} = 1\) when…

How to merge my vcf files (n=6) with existing Pf6 vcf file and do pca? 0 I sampled some Pf strains and got them WGS done. Now I want to merge them with existing Pf6 data. For this I downloaded Pf6 data for all 14 chromosomes. I then used bcftools…

1. Introduction Human population genetics benefitted from the completion of the human genome sequence [1], which was further advanced by creating the reference of global genome variation [2] and, finally, the establishment of regional references assessing fine details of local variation in whole-genome sequences. Although European populations are relatively well…

Gene expression atlas in fiber development To uncover the genetic regulation of gene expression in fiber development, we collected 376 diverse G. hirsutum accessions for genome and transcriptome analysis. A total of 13.5 Tb of genome resequencing data were generated, with an average depth of 15.6× (Supplementary Table 1). Accessions were…

image:  Experimental setup and phenotypic responses under common garden-conditions in Fragaria vesca plants after propagation at different temperatures for up to three asexual generations. view more  Credit: Horticulture Research As global warming continues to redefine ecosystems, plants are increasingly tasked with swift adaptation to ensure their survival. One primary mechanism…

Abstract: With the advancements in high-throughput sequencing technologies such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass spectrometry, large volumes of biological data in multiple formats can now be obtained through multi-omics analysis. Bioinformatics is constantly evolving and seeking breakthroughs to solve multi-omics problems, however it is challenging…

single cell RNAseq: From counts or RPKM > PCA > tSNE visualization of PCA 2 Hello! I am a beginner at RNA seq analysis, I was hoping someone would point me in the direction of how I can take a data set (~50K genes in rows + 200 cells in…

Principal components analysis A dataset in Excel titled protein has been uploaded in Canvas for this module. Using RStudio’s Excel file capability, load it into RStudio and call it Protein.data. (Don’t forget to check off that the columns have titles. Using the cor function create a matrix of correlations of…

Encuesta Nacional de Salud 2000 Since 1988, Mexico has established periodical National Health Surveys (Encuesta Nacional de Salud (ENSA), originally conceived as National Nutrition Surveys) for surveillance of Mexican population-based nutrition and health metrics. In this study, we use data and samples collected from the survey carried out in 2000,…

I have a question about how DESeq2 handles design models which include a parameter that only applies to a single sample in the dataset. For context, we are using DESeq2 to capture differential chromatin accessibility due to age differences (adult vs juvenile) using CUT&RUN data from the venom glands of…

SeqSQC can be used for sample QC of Whole Genome Sequencing Data 0 I am using the R librabry SeqSQC from Bioconductor to do sample QC of around 50 Whole Genome Sequencing samples. The vignette says Through incorporation a benchmark data assembled from the 1000 Genomes Project, it can accommodate…

Comment: deseq2 filter the low counts by Michael Love 40k You can’t filter the groups separately, you need to use a non-specific filter that doesn’t make use of information about which samples are … Comment: deseq2 filter the low counts by daiane.hemerichbrennan • 0 Hi Michael, I have another question…

Construct design To transcribe and translate sequenced DNA clusters on an Illumina flow cell, our DNA constructs contained the following elements: a P5 adaptor, followed by a 28 nt unique barcode, a 27 nt unstructured spacer (5p UNS v2), a ribosome binding site, start codon, protein coding region, TolAk short linker, 2×…

CRISPR/Cas9-induced mutants at OsFIE1 and OsFIE2 Among ~150 T0 plants transformed with the CRISPR/Cas9 vector targeting the two FIE genes (Fig. 1a), we focused on plants with normal pollen dehiscence, as heterozygous fie mutants and other Polycomb mutants are not expected to give pollen sterility in heterozygous condition7,8,9,10,11,12,13,14. Four plants…

Hello, I’m working on a project that involves paired (case-control) pool sequencing to investigate the genetic factors in trees. I’ve observed inflation in QQ plots and some inconsistencies in my results when using the Cochran-Mantel-Haenszel (CMH) test, and I’m seeking guidance and suggestions. Pooling Design & Sequencing: I have a…

Mapping eQTLs in patients with psoriasis We obtained longitudinal lesional and non-lesional skin biopsies from participants at baseline, during treatment, and at the time of psoriasis relapse after study medication withdrawal over a course of 22 months. We used genome-wide genotyping and RNA-seq to assay samples. After stringent quality control,…

Everything was running smoothly until I ran into the DESeqDataSetFromMatrix error. Error in DESeqDataSetFromMatrix(countData = Counts, colData = coldata, : ncol(countData) == nrow(colData) is not TRUE My code: Counts <- read.delim(“RiboTag_count_matrix_10-05-2023.csv”, header = TRUE, sep=”,”) Counts # dimension is 24421 rows x 13 columns; first column is GeneID Counts <-…

Animals and husbandry details Six-week-old healthy male SD rats were used in accordance with the Guidelines for the Care and Use of Laboratory Animals of the Institute of Laboratory Animal Resources, Institutional Animal Care and Use Committee of Beijing University of Chinese Medicine. The study is reported in accordance with…

Introduction Extraction of useful information from high-dimensional datasets is made easier by Principal component analysis, (PCA) a popular dimensionality reduction method. It does this by re-projecting data onto a different axis, where the highest variance can be captured. The complexity of the dataset is reduced while its basic structure is preserved…

Hi! Some personal thoughts/opinions: integration is about finding the similar cell types/states across data sets (either with or without batch effect). An experimental batch corresponds to a set of samples that were processed simultaneously in the same manner and, thus, reducing the effect of technical artifacts/noise. As I see your…

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DESeq2 : standardising variation between treatments 0 @4d9298e2 Last seen 6 hours ago United Kingdom Hi, I have dataset with transcripts from 3 population in 3 treatments and 2 replicates, totalling 18 samples. The aim of this analysis are: Identify differentially expressed genes (DEGs) between pairs of treatments for each…

Adding means cluster from fvis_cluster on the PCA 0 Hi everyone, I created a PCA that shows the sample metadata. Shape , size and colour for genotype, gender and batch respectively. I also created cluster plot using fviz_cluster. I only need to add the cluster frames created by fviz_cluster on…