Appendix V. Software and Tools

0) Process files in different format

0.1) sequence

• seqtk

• bbmap

0.2) alignment

• gffread

• samtools

• bamtools

0.3) interval

• bedtools

• bedtk

1) Homolog analysis

1.1) Sequence based search

• blast: 方便的网页工具
• blat: a blast like tool
• mmseqs: 比blast更现代的同源搜索工具，推荐本地进行大量计算时使用
• diamond: 蛋白的同源搜索工具

1.2) Profile based search

• hmmer: profile hmm based search for protein and nucleotide sequence
• infernal: profile SCFG based search for structured noncoding RNA
• hh-suite: profile hmm to profile hmm alignment

1.3) Multiple sequence alignment

• MAFFT
• clustal
• T-Coffee

2) Genome Browsers

• UCSD Genome Browser (@youtube @bilibili)
• IGV (@youtube @bilibili)

see more in our Tutorial

3) DNA-seq

(3.1) Mapping and QC

• Remove adaptor

  • cutadapt
  • TrimGalore: 对cutadapt进行封装，自动识别常见adaptor
  • Trimmomatic
  • fastp
• Mapping

  • bowtie2
  • bowtie
  • bwa
• QC

  • fastqc

(3.2) Variant Calling

• Mutation discovery

  • GATK
  • Varscan
• Mutation annotation

  • ANNOVAR

(3.3) Assembly

denovo assembly software

• SPAdes

  • the sub-utility metaSPAdes is designed for metagenome assembly

• megahit: designed for metagenome assembly

(3.4) CNV

• Whole genome Seq

  • Control-FREEC
• Whole exome Seq

  • CONTRA
  • ExomeCNV

(3.5) SV (structural variation)

• structural variation

  • lumpy
  • Breakdancer

4) RNA-seq

(4.1) RNA-seq

• Mapping

  • STAR

    • The sub-utility STARsolo is designed for mapping of single cell RNA-seq data

  • hisat2
• Expression Quantification

  • featureCounts
  • htseq-count
  • salmon
  • kallisto
• Differential Analysis

  • deseq2
  • edgeR
  • limma
• Alternative Splicing Analysis:

  • rMATS
  • MAJIQ
  • SUPPA
  • DEXSeq
• RNA Editing

  • RNAEditor
  • REDItools

(4.2) Single Cell RNA-seq (scRNA-seq)

• awesome-single-cell: a collection of single cell analysis tools
• seurat: a widely used R package
• scanpy: a widely used python package
• monocle: Trajectory analysis
• cellphonedb: Cell-cell interaction analysis
• scenic: Transcriptional regulatory network
• Tutorials

  • https://bioconductor.org/books/release/OSCA/

  • https://github.com/theislab/single-cell-tutorial

Nature Biotechnology 2020 38(3):254-257

Software name	Developer	Price structure	Platform-specific	Relevant stages of experiment
Cell Ranger	10X Genomics	Free download	10X Chromium	Raw read alignment, QC and matrix generation for scRNA-seq and ATAC-seq; data normalization; dimensionality reduction and clustering
Loupe Cell Browser	10X Genomics	Free download	10X Chromium	Visualization and analysis
Partek Flow	Partek	License	No	Complete data analysis and visualization pipeline for scRNA-seq data
Qlucore Omics Explorer	Qlucore	License	No	scRNA-seq data filtering, dimensionality reduction and clustering, visualization
mappa Analysis Pipeline	Takara Bio	Free download	Takara ICell8	Raw read alignment and matrix generation for scRNA-seq
hanta R kit	Takara Bio	Free download	Takara ICell8	Clustering and analysis of mappa data
Singular Analysis Toolset	Fluidigm	Free download	Fluidigm C1 or Biomark	Analysis and visualization of differential gene expression data for scRNA-seq
SeqGeq	FlowJo/BD Biosciences	License	No	Data normalization and QC, dimensionality reduction and clustering, analysis and visualization
Seven Bridges	Seven Bridges/BD Biosciences	License	BD Rhapsody and Precise	Cloud-based raw read alignment, QC and matrix generation
Tapestri Pipeline/Insights	Mission Bio	Free download	Mission Bio Tapestri	Analysis of single-cell genomics data
BaseSpace SureCell	Illumina	License	Illumina SureCell libraries	Raw read alignment and matrix generation
OmicSoft Array Studio	Qiagen	License	No	Raw read alignment, QC and matrix generation, dimensionality reduction and clustering

4.3 Assembly

• Trinity: 利用RNA-seq数据进行转录本组装

5) Interactome

(5.1) ChIP-seq

• MACS: peak calling
• homer: peak calling, motif finding, etc
• ChIPseeker: visualization and annotation

(5.2) CLIP-seq

• CTK
• Piranha
• PARalyzer
• clipper

(5.3) Motif analysis

sequence

1. MEME motif based sequence analysis tools http://meme-suite.org/
2. HOMER Software for motif discovery and next-gen sequencing analysis http://homer.ucsd.edu/homer/motif/

structure

1. RNApromo Computational prediction of RNA structural motifs involved in post transcriptional regulatory processes https://genie.weizmann.ac.il/pubs/rnamotifs08/
2. GraphProt modeling binding preferences of RNA-binding proteins http://www.bioinf.uni-freiburg.de/Software/GraphProt/

6) Epigenetic Data

(6.1) ChIP-seq

• Bisulfate sequencing:

  • Review: Katarzyna Wreczycka, et al. Strategies for analyzing bisulfite sequencing data. Journal of Biotechnology. 2017.
  • Mapping:

    • Bismark
    • BSMAP
  • Differential Methylation Regions (DMRs) detection

    • methylkit
    • ComMet
  • Segmentation of the methylome, Classification of Fully Methylated Regions (FMRs), Unmethylated Regions (UMRs) and Low-Methylated Regions (LMRs)

    • MethylSeekR
  • Annotation of DMRs

    • genomation
    • ChIPpeakAnno
  • Web-based service

    • WBSA
• IP data:

  • Overview to CHIP-Seq: https://github.com/crazyhottommy/ChIP-seq-analysis
  • peak calling: MACS2
  • Peak annotation and visualization

    • HOMER annotatePeak
    • ChIPseeker
  • Gene set enrichment analysis for ChIP-seq peaks

    • GREAT

(6.2) DNAase-seq

• review : Yongjing Liu, et al. Brief in Bioinformatics, 2019.
• Peak calling: F-Seq
• Peak annotation: ChIPpeakAnno
• Motif analysis: MEME-ChIP

(6.3) ATAC-seq

• Pipeline recommended by Harward informatics

(7) Microbe data analysis

• kraken2: k-mer based fast metagenome reads classification
• metaphlan: marker gene based microbe taxonomy abundance estimation
• motu: marker gene based microbe taxonomy abundance estimation
• maxbin: binning contigs into metagenome-assembled genomes (MAGs)
• mash: rapid estimation of distance between genome
• drep: pick representative genome from sample-wise assembly
• prodigal: prokaryote gene prediction
• prokka: pipeline for prokaryote genome annotation
• qiime2: 16S amplicon sequencing data analysis

More: Shared tools and scripts

• Scripts: Lu Lab | Zhi J. Lu
• Plots: Lu Lab | Zhi J. Lu

More: Software for the ages

Software	Purpose	Creators	Key capabilities	Year released	Citationsa
BLAST	Sequence alignment	Stephen Altschul, Warren Gish, Gene Myers, Webb Miller, David Lipman	First program to provide statistics for sequence alignment, combination of sensitivity and speed	1990	35,617
R	Statistical analyses	Robert Gentleman, Ross Ihaka	Interactive statistical analysis, extendable by packages	1996	N/A
ImageJ	Image analysis	Wayne Rasband	Flexibility and extensibility	1997	N/A
Cytoscape	Network visualization and analysis	Trey Ideker et al.	Extendable by plugins	2003	2,374
Bioconductor	Analysis of genomic data	Robert Gentleman et al.	Built on R, provides tools to enhance reproducibility of research	2004	3,517
Galaxy	Web-based analysis platform	Anton Nekrutenko, James Taylor	Provides easy access to high-performance computing	2005	309b
MAQ	Short-read mapping	Heng Li, Richard Durbin	Integrated read mapping and SNP calling, introduced mapping quality scores	2008	1,027
Bowtie	Short-read mapping	Ben Langmead, Cole Trapnell, Mihai Pop, Steven Salzberg	Fast alignment allowing gaps and mismatches based on Burrows-Wheeler Transform	2009	1,871
Tophat	RNA-seq read mapping	Cole Trapnell, Lior Pachter, Steven Salzberg	Discovery of novel splice sites	2009	817
BWA	Short-read mapping	Heng Li, Richard Durbin	Fast alignment allowing gaps and mismatches based on Burrows-Wheeler Transform	2009	1,556
Circos	Data visualization	Martin Krzywinski et al.	Compact representation of similarities and differences arising from comparison between genomes	2009	431
SAMtools	Short-read data format and utilities	Heng Li, Richard Durbin	Storage of large nucleotide sequence alignments	2009	1,551
Cufflinks	RNA-seq analysis	Cole Trapnell, Steven Salzberg, Barbara Wold, Lior Pachter	Transcript assembly and quantification	2010	710
IGV	Short-read data visualization	James Robinson et al.	Scalability, real-time data exploration	2011	335
N/A, paper not available in Web of Science.

From: The anatomy of successful computational biology software