본문영역 바로가기 하단 바로가기

국내 유일의 클라우드 기반 통합 데이터 분석 서비스

공개된 프로그램 및 파이프라인 열람을 통한 분석 기초 정보 확인

분석 파이프라인

Bio-Express에는 총 2개의 파이프라인이 등록되어 있습니다.

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
  • 카테고리Single-Cell-RNA-Sequencing
  • 버전0.1
  • 참조Single-Cell-RNA-Sequencing-Pipeline
  • 등록자bioex
  • 생성일2022-08-10
  • 수정일2023-04-14
#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
실행 2 건 분석활용
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
  • 카테고리Whole-Genome-Sequencing
  • 버전1.0
  • 참조kobic.re.kr/bioexpress
  • 등록자bioex
  • 생성일2021-08-31
  • 수정일2022-10-20
#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
실행 5 건 분석활용