Compare · 11 tools
Sequencing read analysis tools you can run online
Tools across the primary sequencing analysis lifecycle, spanning raw read quality control, reference alignment, genomic arithmetic, variant and peak calling, and downstream transcriptomic quantification.
What sequencing read analysis tools do
High-throughput sequencing analysis transforms raw, uncalibrated base calls from sequencing instruments into biological measurements such as variants, genomic enrichment peaks, and gene expression estimates. Raw sequencing files frequently contain low-quality base calls, platform-specific artefacts, and adapter contamination that must be trimmed or filtered prior to downstream processing. Following quality control, sequence reads are mapped back to a reference genome, producing coordinate-aligned representations that describe the origin of every read across chromosomes or contigs.
Once alignments are established, specialised utilities extract higher-order genomic signals. Alignment files are sorted, indexed, and manipulated to identify genetic variants, compute coverage across specific intervals, detect transcription factor binding peaks, or assign overlapping reads to annotated features such as exons and genes. Downstream methods then take these quantification matrices or interval sets to perform comparative analyses, such as motif discovery or transcriptomic deconvolution.
Compared
- RectangleTranscriptomicsEstimates cell-type proportions in bulk and spatial transcriptomic data using single-cell RNA sequencing references.See its pageAs a job
- samtoolsRead alignment and variantsA command-line toolsuite for reading, writing, sorting, indexing, and viewing SAM, BAM, and CRAM alignment files.See its pagePreinstalled
- bcftoolsRead alignment and variantsA toolkit to call, filter, merge, query, and summarise genetic variants in VCF, gVCF, and BCF2 files.See its pagePreinstalled
- Bowtie 2Read alignment and variantsAligns sequencing reads to long reference genomes using memory-efficient FM indexing.See its pagePreinstalled
- BWARead alignment and variantsA sequence alignment package that maps DNA sequencing reads against large reference genomes using FM-indexing.See its pagePreinstalled
- bedtoolsGenomic intervalsA command-line suite for intersecting, merging, and analysing genomic intervals across standard bioinformatics formats.See its pagePreinstalled
- MACS3Genomic intervalsA peak caller identifying enriched genomic regions from bulk and single-cell ChIP-seq, ATAC-seq, and DNA assays.See its pagePreinstalled
- HOMERGenomic intervalsDiscovers sequence motifs and analyses functional genomics sequencing data such as ChIP-seq and RNA-seq.See its pagePreinstalled
- fastpRead quality controlQuality control and preprocessing software that trims, filters and profiles short-read FASTQ sequencing data in one pass.See its pagePreinstalled
- TrimmomaticRead quality controlA Java tool for trimming sequencing adapters and low-quality bases from single-end and paired-end Illumina NGS reads.See its pagePreinstalled
- featureCountsTranscriptomicsAssigns mapped sequencing reads to genomic features such as genes, exons, and promoters for expression analysis.See its pagePreinstalled
How to choose
For read quality control and trimming, fastp and Trimmomatic handle short-read FASTQ files. fastp acts as an all-in-one preprocessor, executing adapter detection, sliding-window trimming, quality filtering, deduplication, and quality profiling in a single execution step, while outputting HTML and JSON reports. Trimmomatic executes user-specified sequences of operations in strict command-line order, requiring manual specification of trimming steps and explicit thread management on high-performance computing clusters to avoid memory oversubscription. However, Trimmomatic provides dedicated palindrome trimming for read-through adapters in short insert libraries and separates surviving singletons into dedicated unpaired files.
For aligning reads against reference genomes, Bowtie 2 and BWA both rely on Burrows-Wheeler transform and FM-index structures. Bowtie 2 aligns reads ranging from 50 bases to thousands of base pairs, using around 3.2 GB of RAM for the human genome and supporting local, gapped, and paired-end modes. BWA (specifically BWA-MEM) handles reads from 70 base pairs up to multiple megabases, accommodates error rates over 20% for Oxford Nanopore reads with specialised parameters, and supports reference genomes exceeding four gigabases. However, BWA cannot handle individual chromosomes exceeding two gigabases and struggles with memory spikes when processing coordinate-sorted FASTQ files with centromeric reads.
For alignment handling and variant calling, samtools and bcftools work together via HTSlib. samtools focuses exclusively on sequence alignment files, providing facilities to read, write, sort, index, and summarise SAM, BAM, and CRAM files. bcftools operates downstream on variation formats (VCF, gVCF, BCF2), providing native variant calling from alignments as well as querying, filtering, and merging routines. bcftools is limited to single nucleotide polymorphisms and short indels, excluding structural variants.
For interval operations and peak analysis, bedtools provides a general arithmetic suite across BED, GFF, VCF, and BAM formats, using sweep-line algorithms on sorted files or R-Tree indexing for unsorted inputs. For biological enrichment, MACS3 identifies peaks from ChIP-seq and ATAC-seq data, modelling fragment lengths and strand orientation with or without matched controls, and exports single-cell counts into AnnData objects. HOMER takes identified intervals, gene lists, or FASTA files to discover enriched de novo sequence motifs between 8 and 20 base pairs across model organisms. For expression quantification, featureCounts maps SAM/BAM reads directly to annotated genes and exons, while Rectangle operates further downstream on bulk RNA-seq and spatial transcriptomics to deconvolute cell-type proportions against single-cell reference datasets.
Questions
Can I run these tools without a GPU or installing anything?
Yes. The research agent runs each of these on a machine of its own — some are preinstalled, others are set up the first time a task needs them — and reads the results back to you.
Which tool should I use for general coordinate comparisons and interval overlaps?
bedtools is designed specifically for genomic arithmetic, allowing you to intersect, merge, count, complement, and shuffle intervals across BED, GFF, VCF, and BAM files. For maximum scalability and low memory usage, pre-sorted files should be used with the -sorted option.
Can BCFtools call large structural variants from alignment files?
No. Variant calling in bcftools is restricted to single nucleotide polymorphisms (SNPs) and short indels. It does not call structural variants.
Do I need to supply adapter sequences when trimming reads with fastp?
Not for paired-end reads. fastp automatically identifies and trims adapter sequences in paired-end data through overlap analysis. However, automatic adapter detection is disabled if data is fed through standard input (STDIN).
What is the difference in functionality between featureCounts and Rectangle?
featureCounts quantifies gene and exon expression by counting mapped reads from SAM or BAM alignment files against genomic annotations. Rectangle does not process raw alignments; it performs cell-type deconvolution on bulk or spatial transcriptomic expression data using an annotated single-cell RNA-seq reference.
Can MACS3 run on Windows systems?
No. MACS3 does not currently support Windows operating systems and requires a Python environment running version 3.12 or newer.
Written from each tool's own documentation, as summarised on its page here. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.