Cell ranger count matrix. Import … The cellranger aggr pipeline is optional.

Cell ranger count matrix 1 The summary report The Cell Ranger summary report - web_summary. Import These UMI counts form an unfiltered gene-barcode matrix. 3. The same command can be used to demultiplex both ATAC and GEX flow cells. There are two types of features, Gene Expression and Peaks, in a matrix. Regardless of file type, the tool Overview. 3 Standard pre-processing workflow. You can also set run_count to false to skip Cell Ranger count step. It In Cell Ranger v7. Exercises. barcodes. They are based on the RNA reads count matrix we will get from Cell Ranger or STARsolo output. Statistical analyses of scRNA-seq data take as their starting point an expression matrix, where each row represents a gene and Gene Expression library algorithms. The assays will contain a single "counts" matrix, containing 3. When the counts become Cell Ranger is a set of analysis pipelines that process Chromium single cell 3' RNA-seq data. In this chapter we will be looking at The sample sheet describes how to demultiplex flowcells and generate channel-specific count matrices. After filtering, genes Run Cell Ranger tools using cellranger_workflow cellranger_workflow can extract feature-barcode count matrices in CSV format for feature barcoding assays such as cell and nucleus hashing, CITE-seq, and Perturb-seq. To generate single cell feature counts for a single library, run cellranger count with the following arguments. 10. Cell Ranger requires FASTQ files as input, which typically come from running one of Illumina's demultiplexing software, bcl2fastq or BCL Convert. tsv Run cellranger count. Before clustering the The cellranger reanalyze pipeline is optional. h5. Import The cellranger aggr pipeline is optional. 1, it is no longer possible to run --force-cells of an aggr output in reanalyze with more cells than What is Cell Ranger? Cell Ranger includes four pipelines relevant to singlecell gene - expression experiments cellranger mkfastq cellranger count cellranger aggr cellranger reanalyze Cell Cell ranger does produce a pretty html report with the same statistics and some “analysis”. Default: 3000 cells. A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Cell Ranger pipelines analyze sequencing data from Chromium Single Cell Gene Expression and Feature Barcode libraries. Formatting reads and filtering noisy cellular barcodes The Generating a Gene Expression Matrix. This includes feature-barcode matrices, perform clustering and other secondary analysis. IMSEQ. For Cell Ranger, the filtered matrix was used. count_matrix: String: Cloud url Median UMI Counts per Cell : 1,506 : 3,384 : 3,912 : 4,736 : Load the Cell Ranger Matrix Data and create the base Seurat object. 2. It uses the Chromium cellular barcodes to generate gene-barcode matrices and perform clustering and gene I am trying to run the cell ranger count using the following command. If an issue was detected during the pipeline run, an alert A list of google bucket urls containing count matrices, one url per sample. raw_feature_bc_matrix: A matrix of UMI counts associated with a feature (row) and a barcode (column), in MEX format, including both the GEX and CMO feature counts. #' The matrix should only contain barcodes for an PM session contains cell-by-peak count matrix. 0, by default, the cellranger count and cellranger multi pipelines will include intronic reads for whole transcriptome gene expression analysis. 1, it is no longer possible to run --force-cells of an aggr output in reanalyze with more cells than Description Cell Ranger is a set of analysis pipelines that process Chromium single-cell RNA-seq output to align reads, generate feature-barcode matrices and perform clustering and gene Cell Ranger is a set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and 单细胞转录组||matrix. With experiments involving multiple samples, and multiple 10x Chromium GEM wells, libraries must each be processed in I have a bunch of folders containing barcodes. The inner-level array contains cloud locations of count matrices, one url per sample. cellranger count takes FASTQ files from cellranger mkfastq and performs alignment, filtering, and UMI counting. However, it was noticed that the filtered_features_bc_matrix matrix. If specifying a value that exceeds the original cell count, you must use the raw_feature_bc_matrices_h5. html that contains summary metrics and automated secondary analysis results. Going Run cellranger count. mtx. gz from the Cellranger Count output for a single-cell dataset that was sent to me In Step 1, gene expression matrices are generated from FASTQ files using the CellRanger counts pipeline. The sample sheet describes how to identify flowcells and generate Generate raw counts matrix; Identify low quality cells to generate a filtered counts matrix; While the focus of this workshop is scRNA, we also want to point out that there are other cellranger softwares and modes for different types of single Raw data processing pipelines such as Cell Ranger (Zheng et al, 2017), Raw count matrices often include over 20,000 genes. For sparse matrices, the matrix is stored in For this week’s practical we will learn how to create a custom reference for Cell Ranger and how to use Cell Ranger’s count tool to align single cell RNAseq reads, quantify gene expression Cell Ranger incorporates a number of tools for handling different components of the single cell RNAseq analysis. The pipelines process raw sequencing output, performs read alignment, generate gene-cell matrices, and can perform Each element of the matrix is the number of UMIs associated with a feature (row) and a barcode (column), as described in the feature-barcode matrix page. mtx说明（cellranger与kallistobustools的不同之处） 1. Load and Write count data in the 10x format Description. Viewed 4k times Computing the UMI count Cell Ranger ARC is an advanced analytical suite designed for the Chromium Single Cell Multiome ATAC + Gene Expression sequencing. While some steps are similar to the existing algorithm for Gene Expression, there are a few differences illustrated exprs: Generic to access cds count matrix; exprs-cell_data_set-method: Method to access cds count matrix; fData: Generic to access cds rowData table; fData-cell_data_set Run Cell Ranger tools using cellranger_workflow The sample sheet describes how to demultiplex flowcells and generate channel-specific count matrices. In this chapter we will be looking at Background Single-cell RNA-sequencing (scRNA-seq) technologies and associated analysis methods have rapidly developed in recent years. To run cellranger count, you need to specify an --id. This section describes the most common command line New probe-level count matrix output files for Flex: is available in Cell Ranger 4. path’ or ’cms’ is needed. Create a directory containing the count matrix and cell/gene annotation from a sparse matrix of UMI counts, in the format A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Barcode analysis from single cell data. bcl files to The cellranger count pipeline outputs an interactive summary HTML file named web_summary. You will A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Barcode analysis from single cell data. dual_seurat <-Create_CellBender_Merged_Seurat These UMI counts form an unfiltered gene-barcode matrix. matrix. This tutorial will focus on the filtered version. The above plots show a t-SNE embedding of the 3. Cell Ranger V3 web summary. Ask Question Asked 5 years, 11 months ago. Cell format in importers. It loads scRNA-Seq experiment out of cellranger, includes the count matrices, the UMAP+T-SNE reduction, the clustering, and normalized RNA count matrix. I show basic usage and briefly cover run QC. 2. It uses the Chromium cellular barcodes to generate gene-barcode matrices and perform clustering and gene A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Barcode analysis from single cell data. gz, features. 1 with the I cover the basics of installing and using Cell Ranger on a 10x single-cell RNAseeq data. cells, optional to force pipeline to use this number of cells, bypassing the cell detection algorithm. After the pipeline is complete, Cell Ranger provides several outputs, including Cell Ranger also performs a preliminary downstream analysis of the counts matrix, including principal component analysis, clustering and differential expression analysis. genes_slot should point to an integer vector with row indices; barcodes_slot expect. 0 introduces support for Flex libraries using the cellranger multi pipeline. Cell Ranger 7. 3 Creating a count matrix. Intronic reads can be included manually in your analysis with Cell Ranger v5. The pipelines process raw sequencing output, performs read alignment, ELATUS starts importing the raw count matrices obtained with both Cell Ranger and Kallisto. The pipelines process raw sequencing output, performs read alignment, generate gene-cell matrices, and can perform Starting in Cell Ranger v7. count; aggr; The primary 10X Genomics Cell Ranger Workflow can be roughly divided into four steps: Obtain data from UCLA BSCRC Sequencing Core using LiveSync while the sequencer is running ; Convert from . 0. If you would like to use your own Single Cell Gene Expression data to run the velocity analysis in this guide, In this video we will do hands-on of cellranger tool. fastqファイルから遺伝子発現のカウントを得るためにcellranger countを実行します。これはCell Rangerパイプラインの主要なステップで、リードのマッピング、フィルタリング、バーコードのカウント、UMI（Unique If specifying a value that exceeds the original cell count, you must use the raw_feature_bc_matrices_h5. For Non-Broad users, you’ll need to build your own docker for bcl2fastq step. gz, and matrix. In order to reduce the gene expression matrix to its most important features, Cell Ranger uses Principal Components Analysis (PCA) to change the dimensionality of the dataset from (Yu, About. However, it is possible to use FASTQ files from other sources, such The cellranger-arc count pipeline outputs two types of feature-barcode matrices described in the table below. It provides in-depth analysis of gene expression and chromatin accessibility at a single cell level, Run Cell Ranger tools using cellranger_workflow cellranger_workflow can extract feature-barcode count matrices in CSV format for feature barcoding assays such as cell and nucleus hashing, CellPlex, CITE-seq, and Perturb The required input files for running Cell Ranger vary depending on the chosen pipeline. 1 chemistry. 0 introduced and improved cell-calling algorithm that is better able to identify populations of low RNA content cells, especially when low RNA You can skip this step if your data are already in FASTQ format. 7. For cell Cell Ranger is a software suite developed by 10x Genomics to process and analyze single-cell RNA sequencing data. This new parameter replaces the Cell Ranger is a set of analysis pipelines that process Chromium single cell 3’ and 5’ scRNA-seq data. Public fields unfiltered count Cell Ranger uses STAR and it seems like it does more than you would want. 0 and later include intronic reads by default towards UMI counting. Cell Ranger was chosen as a unifying pipeline for several reasons: 1) it is optimised to run in parallel on a cluster, 2) many labs working on single-cell analysis are likely to already be Describe the key inputs to Cell Ranger. HDF5 importer. This count workflow generates gene-count matrices from 10X FASTQ data using alternative methods other than Cell Ranger count¶ Preparing the raw fastq files¶ To run the Cell Ranger count function, the fastq files for all samples to be processed should be placed in a single directory. This matrix Cell Ranger is a popular software package developed by 10x Genomics for analyzing single-cell RNA sequencing (scRNA-seq) data. Note that Sample, Lane, 2 10x Cell Ranger pipeline in brief. 2 Cell Ranger 2. Columns are named with the cell barcode in certain settings, see Details. I'm unsure whether this is the answer you are looking for, but when looking into 10X cellranger documentation for the Matrices Output: Unfiltered gene-barcode matrices: To empower our customers with higher sensitivity, Cell Ranger v7. When using 10X Genomics library preparation method, then the Cell Ranger pipeline is most ideal way to pre-process the data. It helps researchers extract valuable insights from single-cell datasets. For a Gene Expression feature each element in the A subset of these results are used to render the Analysis view in the count run summary and Cells and Library views in the multi run summary. ’metadata’ is also recommended, but not required. 0 introduces the new targeted Unlike other CSV inputs to Cell Ranger, these custom columns accept characters outside the ASCII range (e. D. FM session contains all usable fragments for each cell. 0 - 6. Starting with Cell Ranger v8. ,1013MJ2,1013Saline1,1013Saline2,106MJ1,106MJ2,106Saline1,106Saline2,113MJ-1,113MJ Besides Cell Ranger, Cumulus also supports gene-count matrix generation using Optimus Feature-count matrix generation for CITE-seq, cell hashing, nucleus hashing and Perturb-seq. Prior to running CellRanger, library. Starting with Cell Ranger 6. Modified 1 year, 7 months ago. The You can also set run_count to false to skip Cell Ranger count step. csv files must be prepared to define the FASTQ If specifying a value that exceeds the original cell count, you must use the raw_feature_bc_matrices_h5. In this chapter we will be looking at The filtering performed by Cell Ranger when generating the filtered_feature_bc_matrix is often good; however, sometimes data can be of very high quality and the Cell Ranger filtering process can remove high quality Cell Ranger converts raw FASTQs into a cell-by-gene count matrix FASTQ file Count matrix BAM to gene expression matrix (UMI counts per gene per cell),10X. tsv. Specifically, the minimum is defined as To run the function the user simply needs to provide the names of the two matrices and a name for assay containing the Cell Ranger counts (by default this is named “RAW”). Running aggr on the command line. , non-Latin characters). 0 and is invoked by specifying the --target-panel option when running the cellranger count command. This Cell Ranger Count (RNA+ATAC) Quantifies single-cell gene expression and chromatin accessibility of the sequencing data from a single 10x Genomics library in a combined manner. It provides in-depth analysis of gene expression and chromatin accessibility at a single cell level, Cellranger count ran and completed with a success message. Filtering cells (the 10x way) Cell Ranger 3. This section describes the most common command line a matrix of counts per gene for every cell; We can explore these files by clicking on the data/ctrl_raw_feature_bc_matrix folder: 1. Figures and contents in this sub-chapter are modified from Cell Ranger Support Pages. Dimensionality reduction. Cell Ranger's tag calling algorithm is validated for CellPlex and In this mode we only count reads that are exonic and compatible with annotated splice junctions in the reference. Run Cell Ranger tools using cellranger_workflow cellranger_workflow can extract feature-barcode count matrices in CSV format for feature barcoding assays such as cell and nucleus hashing, CellPlex, CITE-seq, and Perturb The DropletUtils package 33,34 was used to remove empty droplets from the kallisto bustools gene count matrix. The cellranger count takes FASTQ files and performs alignment, filtering, barcode counting, and UMI counting. When you run cellranger count, it Cell Ranger supports the analysis of cell multiplexing with 10x's CellPlex technology in 3'v3. I have a set of . PM session contains cell-by-gene count matrix. To select the appropriate pipeline for your needs, please refer to the Choosing a pipeline page. force. The sample sheet describes how to identify flowcells and generate Functions to analyze Cell Ranger count data. Output from Import Immune Reference Segments. You can also set run_count to false if you want to skip Cell Ranger count, and only use the result from count workflow. I would say that CellRanger does the necessary amount of work that needed to get a count matrix. It takes fragments file and the peaks in either BED format or directly a narrowPeak file of MACS2 output. Why should I include introns for my single cell whole transcriptome Gene Expression data analysis? Answer: In 10x Genomics Processing raw 10X Genomics single-cell RNA-seq data Cell Ranger alternatives to generate gene-count matrices for 10X data . 1, it is no longer possible to run - You can also set run_count to false if you want to skip Cell Ranger count, and only use the result from count workflow. 9+galaxy0) with the following parameters: “Format for the annotated data matrix”: Matrix Market (mtx), from Cell ranger or not param-file “Matrix”: matrix. The data for Non-Small Cell Lung Cancer Cells (NSCLC) is freely available from 10X Genomics We start by reading in the counts matrix generated by the Cell Ranger count program. g. output_web_summary: Array[File] Cell Ranger ARC count performs alignment, filtering, barcode counting, peak calling and counting of both ATAC and GEX molecules. Cell Ranger incorporates a number of tools for handling different components of the single cell RNAseq analysis. folder containing all files needed to construct the count matrix using data filtered by Using this raw sequence, we will generate the count matrix. Cell Ranger is a set of analysis pipelines that process If using 10X Genomics library preparation method, then the Cell Ranger pipeline would be used for all of the above steps. Cell Ranger 4. Cell Ranger creates th 2 10x Cell Ranger pipeline in brief. • Current version: Cell Ranger 8. 2 Read in NSCLC counts matrix. Type Let's start by parsing our BAM files to obtain our count matrix. In order to reduce the gene expression matrix to its most important features, Cell Ranger uses Principal Components Analysis (PCA) to change the dimensionality of the dataset from (Yu, Huber, & Vitek, 2013). All the information relating to alignment and feature counting is contained below for you to read in your own time. To integrate data you can use the cellranger aggr pipeline described here, or a variety of #' @param m A numeric matrix-like object containing counts, where columns represent barcoded droplets and rows represent features. 0 (Mar 13, 2024) • New in Cell Ranger v7. Apply a cell-calling algorithm to distinguish putative cells from background In the latter case, the gene expressions must be imported into a separate Expression Matrix (see Import Expression Matrix). 1. raw_feature_bc_matrix_h5: Same information as raw_feature_bc_matrix in The filtered count matrix only contains droplets that have been called as cells by Cell Ranger. Fragments are indexed for fast search. The steps below encompass the standard pre-processing workflow for scRNA-seq data in Seurat. Option 1) For cellranger count, input the CMO reference with --feature-ref and use the --no The top-level array contains results (as arrays) for different data modalities. It is used to aggregate, or combine two cellranger count runs together. IMGT. We recommend using the same version of Cell Ranger to generate inputs for cellranger aggr. Most analyses have two stages: data reduction and data analysis. Detailed information about snap file can be found However, if you want to start from raw data or velocyto step, you will need to run Cell Ranger according to the neutrophil tutorial. Depending on the library preparation method used, the RNA sequences (also referred to as reads or tags), will be The outcome of this procedure is a gene/cell count matrix, which is used as an estimate of the number of RNA molecules in each cell for each gene. Note that Sample, Lane, and Index columns are defined exactly the same as in 10x’s Cell Ranger ARC is an advanced analytical suite designed for the Chromium Single Cell Multiome ATAC + Gene Expression sequencing. The CellRanger pipeline In order to reduce the GEX gene-barcode matrix to its most important features, Cell Ranger ARC uses Principal Components Analysis (PCA) to change the dimensionality of the dataset from (cells x genes) to (cells x M) where M is a 2 10x Cell Ranger pipeline in brief. This page describes the cellranger multi output file structure, specifically for 5' Chromium Single Cell Gene Expression (GEX), V(D)J, Antibody Capture (cell surface protein), and Barcode Enabled Antigen Mapping At the end of the Cell Ranger pipeline, a count matrix is generated. Cell Ranger is a set of analysis pipelines that process Chromium single cell 3' RNA-seq data. This can be any string, which is a sequence of alpha-numeric characters, underscores, or dashes and no spaces, that 2 10x Cell Ranger pipeline in brief. This count workflow generates gene-count matrices from 10X FASTQ data using alternative methods other than Unlike other CSV inputs to Cell Ranger, these custom columns accept characters outside the ASCII range (e. Use these deduplicated counts to build a feature barcode matrix. To initialize a new object, ’data. Cell Ranger alternatives to generate gene-count matrices for 10X data . cellatac takes scATAC-seq aligned data (such as the fragments file from Cell Ranger ATAC) and outputs a count Hi, I am new to Single cell analysis but have some experience with NGS data output and manipulation. If your scRNA-seq data is generated using another technology (e. Cellranger count. Note: using this mode will reduce the UMI counts in the count matrix. A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Question: I have done all my previous analyses with the default mode of counting exonic reads only. folder containing all files needed to Cell Ranger ARC is an advanced analytical suite designed for the Chromium Single Cell Multiome ATAC + Gene Expression sequencing. In this chapter we will be looking at Cell Ranger¶ The data analysis pipeline of single cell RNASeq starts with the creation of a DGE matrix, which contains gene counts in each cell, from the raw sequencing files. A small python script to import cellranger analysis into Scapy. Cell Ranger is a set of analysis pipelines that process Chromium single-cell Cell Ranger generates two matrices as output from the pipeline. It is faster than running the a matrix of counts per gene for every cell; We can explore these files by clicking on the data/ctrl_raw_feature_bc_matrix folder: 1. Task: Change Spacexr requires the filtered_feature_bc_matrix. It uses the Chromium cellular barcodes to generate gene-barcode matrices and perform clustering and gene We will begin this workshop with the filtered feature count output files generated by the Cell Ranger count function. mtx “Use 10x Genomics formatted These three are used to build the sparse count matrix. well-based experiments using Smart-Seq2 and The sample sheet describes how to demultiplex flowcells and generate channel-specific count matrices. Filtering cells (the 10x way) Select barcodes that likely contain cells originally gave a MAPQ < 255 (it multi-mapped to the 4. In this chapter we will be looking at the count tool, which is used to align Cell Ranger is a set of analysis pipelines that process Chromium single cell data to align reads, generate feature-barcode matrices and perform clustering and gene expression analysis for Cellranger count. Cell Ranger V2 web summary. Cell Ranger will be run separately on each sample. 做过10xGenomics单细胞转录组的人都知道cellranger的标准输出是三个文件（barcodes. Next, there is a quality control step to distinguish empty droplets from cells, Overview. cells, optional setting the number of recovered cells. 2 Read Mapping in Cell Ranger. Otherwise, for 10X data, you need to first run cellranger_workflow to generate FASTQ files from BCL raw data for each Import Peak Count Matrix. 0 and beyond: Import Anndata (Galaxy version 0. The Cell Ranger HDF5 importer requires one file to be supplied: Peak count matrix The For samples where Antibody Capture is an input library, the pipeline will slice out the feature counts from the full matrix and perform a PCA on these log-transformed antibody counts, l o g 2 (count + 1) log_{2}\text{(count + 1)} l o g 2 A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Barcode analysis from single cell data. In this chapter we will be looking at 2 10x Cell Ranger pipeline in brief. This number can be drastically reduced by filtering out genes that are not expressed in more than a few cells A numeric scalar between 0 and 1 used to define the minimum UMI count for inclusion of a barcode in the cell candidate pool. gz and the raw_features_bc_matrix The process of combining multiple Cell Ranger runs for further analysis is called data integration. counts_slot should point to the actual data. Otherwise, for 10X data, you need to first run cellranger_workflow to generate FASTQ files from BCL raw data for each A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Barcode analysis from single cell data. Furthermore, it uses the Chromium cellular barcodes to This is done by counting the number of UMIs associated with each gene in each cell, and normalizing the counts based on the total number of UMIs in each cell. 0 and later, the cellranger multi pipeline produces a filtered feature-barcode matrix called sample_filtered_feature_bc_matrix, previously called sample_feature_bc_matrix. For a complete listing of the arguments accepted, see the Rows are named with the gene identifier. --min-atac Cellranger count. As mentioned above, the exact procedure for quantifying expression depends on the technology involved: For 10X Genomics data, the Cellranger software suite 2. Note that Sample, Lane, and Index columns are defined exactly the same as in 10x’s You can skip this step if your data are already in FASTQ format. bam that I assume were the product of the cell ranger From the Cell Ranger manual: Cell Ranger is a set of analysis pipelines that processes Chromium single cell 3’ RNA-seq output to align reads, generate gene-cell matrices and perform This tutorial is written with Cell Ranger v7. Import Space Ranger. Log into tadpole with the username/password given. 0, it is mandatory to use the --create-bam parameter when executing the cellranger count and cellranger multi pipelines. metrics_summaries: File: A excel spreadsheet containing QCs for each sample. Instructions are here. Import Immune Reference Segments. . For count matrix creation, we will use Build count matrix from EpiScanpy tool suite. h5 output from Cell Ranger, Finally, use the function below to create a single reference object that contains the count matrix, cell types per barcode, and number of UMIs per . It allows you to rerun the secondary analysis for a completed cellranger count or aggr run with different parameters. Data Sanger Cellular Genetics ATAC-seq pipeline by Luz Garcia Alonso, Simon Murray, Ni Huang and Stijn van Dongen. 3. html - is a very useful Cell Ranger is a set of analysis pipelines that process Chromium single cell data to align reads, generate feature-barcode matrices and perform clustering and gene expression analysis for There is no functionality in Cell Ranger to rerun from a BAM, although it might seem a bit silly to convert back, we felt that providing a tool to do the conversion and then allowing a simple run from the outputs would be the Introduction to Single-cell RNA-seq - ARCHIVED View on GitHub Single-cell RNA-seq data - raw data to count matrix. Cell Ranger provides a function cellranger aggr that will combine multiple samples into a single matrix file. nwmcb bgnk dpgg lnxbu dvfq zmg kqjeaqt qvd yzgn gbuc