1. Text Utilities

Sort Data: Organise and sort tabular data by one or more columns.

Merge Columns: Combine columns from one or more files into a single, cohesive table.

Cut Column: Extract specific columns from a dataset for focused analysis.

Transpose Tabular Data: Swap rows and columns to suit your analysis.

Paste Two Files Side by Side: Join two files column-wise into a single view for comparison.

2. FASTA / FASTQ Manipulation

Concatenate Dataset: Merge multiple FASTA or FASTQ files into one dataset.

Split Dataset: Divide a large FASTA or FASTQ file into smaller, manageable pieces.

Unique Sequence Count: Identify and count unique sequences for diversity analysis.

Count Reads: Report the number of reads in a FASTQ file.

FASTQ to FASTA: Convert reads to FASTA, dropping the quality scores.

Filter by Length: Keep reads above or below a chosen length.

Filter by Quality: Keep reads that meet a chosen quality threshold.

Interleave Reads: Interleave paired-end reads into a single file.

Rename IDs: Rename sequence identifiers in bulk.

Reverse Complement: Produce the reverse complement of sequences.

Sub Sample Reads: Draw a random subset of reads for quick tests.

3. General Feature Format (GFF)

Extract Feature from GFF: Isolate specific features from a GFF file based on your criteria.

Filter GFF Data by Attribute: Filter a GFF file by attribute values relevant to your research.

Count Feature: Count the number of each feature type in a GFF file.

4. Quality Check

FastQC: Assess sequencing read quality, including per-base quality and adapter content, for insight into data integrity.

Qualimap: Quality control for alignment (BAM) files, reporting coverage, mapping quality, and other alignment metrics.

5. Trimming

fastp: Trim adapters and low-quality bases in a single fast pass, with a quality report.

Porechop: Find and remove adapters from Oxford Nanopore long reads.

6. Genome Alignment & Mapping

Build Genome Index: Build the reference index required before alignment, once per genome.

BWA-MEM2 Alignment: Align short DNA reads to a reference genome with BWA-MEM2.

Bowtie2 Alignment: Align short reads to a reference genome with Bowtie2.

7. SAM / BAM Tools

SAM to BAM: Convert a SAM alignment into the compressed BAM format.

BAM to FASTQ: Extract reads from a BAM back into FASTQ.

BAM to FASTA: Extract sequences from a BAM into FASTA.

BAM Flagstat: Report alignment statistics, such as the mapping rate.

BAM Depth: Report read depth at each position.

BAM Index: Index a sorted BAM for fast random access.

BAM Merge: Merge several BAM files into one.

BAM Sort: Sort a BAM by genomic coordinate.

BAM Markdup: Mark or remove duplicate reads.

BAM Extract Reads: Pull out reads from a chosen region.

BAM Idxstats: Report mapped read counts per reference sequence.

8. Variant Calling & SNP Analysis

BCFtools mpileup: Gather read evidence at each position from a BAM.

bcftools Call: Call SNPs and indels from the mpileup output.

bcftools Filter: Filter variants by quality, depth, or custom expressions.

bcftools View: Subset, convert, or view a VCF.

bcftools Query: Extract chosen fields from a VCF into a table.

bcftools csq: Predict variant consequences in a haplotype-aware manner.

bcftools Stats: Summarise a VCF, counting SNPs and indels.

bcftools Merge: Merge several VCFs into a multi-sample VCF.

GATK: Call variants with the Genome Analysis Toolkit as an alternative caller.

9. Read Counting & Gene Expression

featureCounts: Count reads per gene from a BAM and a GFF or GTF annotation to build the count matrix for DESeq2 or edgeR.

DESeq2 Analysis: Test for differentially expressed genes from a count matrix using DESeq2.

edgeR Analysis: Test for differentially expressed genes from a count matrix using edgeR.

10. Visualization & Plots

Volcano Plot: Plot fold change against significance to highlight changed genes.

MA Plot: Plot fold change against mean expression.