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Check the basic analysis information by viewing the open programs and pipelines.

Analysis Pipeline

There are a total of 3 Pipelines registered in Bio-Express.

Bio-express's Single-cell-RNA-Sequencing-Pipeline is an extensible toolkit for analyzing single-cell gene expression data using the Scanpy pipeline. It includes methods for preprocessing, visualization, clustering, differential expression testing. Its Python-based implementation efficiently deals with data sets of more than one million cells. we present ANNDATA, a generic class for handling annotated data matrices. This pipeline features 1) We regress out confounding variables, normalize, and identify highly variable genes. 2) TSNE and graph-drawing (Fruchterman–Reingold) visualizations show cell-type annotations obtained by comparisons with bulk expression. 3) Cells are clustered and plotted using the Louvain algorithm. It also supports clustering using various algorithms. 4) Ranking the differentially expressed genes in clusters identifies marker genes that match the bulk label
  • IDBX02-20240318-5605
  • CategorySingle-Cell-RNA-Sequencing
  • Version0.1
  • ReferenceSingle-Cell-RNA-Sequencing-Pipeline
  • Registrantbioex
  • Create Date2024-03-18
  • Update Date2024-03-18
#Single-cell RNA sequencing#Next-generation sequencing#Bioinformatics#Single-cell genomics#Human Cell Atlas#Cell_Biology#Genomics#transcriptome#Biotechnology#heterogeneity#Multiomics#scRNA-seq#scATAC-seq#Epigenetics
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Bio-express's Single-cell-RNA-Sequencing-Pipeline is an extensible toolkit for analyzing single-cell gene expression data using the Scanpy pipeline. It includes methods for preprocessing, visualization, clustering, differential expression testing. Its Python-based implementation efficiently deals with data sets of more than one million cells. we present ANNDATA, a generic class for handling annotated data matrices. This pipeline features 1) We regress out confounding variables, normalize, and identify highly variable genes. 2) TSNE and graph-drawing (Fruchterman–Reingold) visualizations show cell-type annotations obtained by comparisons with bulk expression. 3) Cells are clustered and plotted using the Louvain algorithm. It also supports clustering using various algorithms. 4) Ranking the differentially expressed genes in clusters identifies marker genes that match the bulk label
  • IDBX02-20220810-2636
  • CategorySingle-Cell-RNA-Sequencing
  • Version0.1
  • ReferenceSingle-Cell-RNA-Sequencing-Pipeline
  • Registrantbioex
  • Create Date2022-08-10
  • Update Date2024-02-21
#Single-cell RNA sequencing#Next-generation sequencing#Bioinformatics#Single-cell genomics#Human Cell Atlas#Cell_Biology#Genomics#transcriptome#Biotechnology#heterogeneity#Multiomics#scRNA-seq#scATAC-seq#Epigenetics
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The whole-genome-sequencing pipeline is a modular pipeline for processing WGS data. This pipeline takes a fastq file as input and provides haplotype call results and annotations and visualizations based on GATK pipeline. First, raw read data with well-calibrated base error estimates in fastq format are mapped to the reference genome. The BWA mapping application is used to map reads to the human genome reference, allowing for two mismatches in 30-base seeds, and generate a technology-independent SAM/BAM reference file format. Next, duplicate fragments are marked and eliminated with Picard(http://picard.sourceforge.net), mapping quality is assessed and low-quality mapped reads are filtered, and paired read information is evaluated to ensure that all mate-pair information is in sync between each read. We then refine the initial alignments by local realignment and identify suspicious regions. Using this information as a covariate along with other technical covariates and known sites of variation, the GATK base quality score recalibration (BQSR) is carried out. Call germline SNPs and indels via local re-assembly of haplotypes using the recalibrated and realigned BAM files. Finally, we provide somalier, a tool to quickly assess relevance from sequencing data in BAM, CRAM or VCF format.
  • IDBX02-20210831-0034
  • CategoryWhole-Genome-Sequencing
  • Version1.0
  • Referencekobic.re.kr/bioexpress
  • Registrantbioex
  • Create Date2021-08-31
  • Update Date2023-11-24
#Whole Genome Sequencing#WGS#Genomics#Next Generation Sequencing#Precision Medicine#Clinical Genomics#noncoding genome#GATK#fastp#Cutadapt#BWA#SortSam#MarkDuplicates#CountBase#BaseRecalibrator#ApplyBQSR#HaplotypeCaller#somalier
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