Awesome bioinfomatics tools

Jeason

457字约2分钟

2024-05-10

相关信息

收集方便使用的生物信息学软件

gtf

  • GffRead: GFF/GTF utility providing format conversions, region filtering, FASTA sequence extraction and more

genome

  • genomepy genomepy is designed to provide a simple and straightforward way to download and use genomic data. This includes (1) searching available data, (2) showing the available metadata, (3) automatically downloading, preprocessing and matching data and (4) generating optional aligner indexes. All with sensible, yet controllable defaults. Currently, genomepy supports Ensembl, UCSC, NCBI and GENCODE.
  • mosdepth 快速计算测序深度

Annotation

  • eggNOG-mapper Fast genome-wide functional annotation through orthology assignment

Single cell

Analysis toolkit

  • singleCellTK R interface to several popular single-cell RNA-sequencing (scRNAseq) data preprocessing, quality control, analysis, and visualization tools.
  • SnapATAC2 A Python/Rust package for single-cell epigenomics analysis
  • scDIOR single-cell data transformation between platforms of R and Python based on Hierarchical Data Format Version 5
  • cNMF inferring gene expression programs from scRNA-Seq
  • SCEVAN R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.
  • Scanorama batch-correction and integration of heterogeneous scRNA-seq datasets
  • cellqc standardized quality control pipeline of single-cell RNA-Seq data

Annotation cell type

  • scCATCH Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data

Metabolism

  • Compass In-Silico Modeling of Metabolic Heterogeneity using Single-Cell Transcriptomes

Spatial omics

CHIP-seq & ATAC-seq

  • SICER 针对 broad peak 的识别工具

Machine learning

  • Lazy Predict Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Analyis

  • GSEApy Gene Set Enrichment Analysis in Python.
  • CPTAC Python packaging for CPTAC data

Visualization

  • CORAL 绘制标记颜色激酶树的shiny app
  • Chromoscope 人类基因组结构变异的交互式多尺度可视化
  • SparK 绘制出版级别的track plot
  • shinyCircos 在线绘制Ciros图的shiny app