Bioinformatics Scripts
Command-line examples for common FASTQ, FASTA, SAM, BED, alignment, and quantification tasks in Linux.
- FASTQ quality control and trimming
- FASTA reference preparation
- Read alignment and raw-count generation
Explore SciBerg resources for Linux-based bioinformatics workflows, NGS data processing, FASTQ/FASTA manipulation, read alignment, raw-count generation, molecular biology fundamentals, and practical data-analysis training.
The current resource library is organized into practical Linux bioinformatics scripts, an NGS data analysis tutorial outline, and a molecular biology course outline.
Command-line examples for common FASTQ, FASTA, SAM, BED, alignment, and quantification tasks in Linux.
A structured outline for learning NGS data analysis, from Linux setup to DNA-seq, RNA-seq, bisulfite-seq, ChIP-seq, and metagenomics.
A course outline covering nucleic acids, proteins, transcription, translation, replication, genome structure, and genome instability.
These resources help users perform basic command-line operations that frequently appear in sequencing-data workflows.
Initial FASTQ quality checks and FastQC-style reports.
Open →Adapter trimming and read filtering workflows.
Open →Cleaning reference FASTA files before downstream analysis.
Open →Selecting sequences by header IDs or sequence lists.
Open →Creating RNA-class-specific references from transcriptome FASTAs.
Open →Basic command-line operations for FASTA and FASTQ files.
Open →Transforming genome annotation formats for interval workflows.
Open →Generating promoter or TSS FASTA files from genome references.
Open →Examples for mapping sequencing reads to reference sequences.
Open →Basic SAM-file operations for alignment-derived outputs.
Open →Raw-count generation and transcript quantification examples.
Open →The resources bridge the gap between biological questions and practical command-line data processing. For project-specific support, SciBerg can provide custom NGS analysis, clinical bioinformatics, and AI-enabled workflow development.
Understand core NGS data-processing concepts and what happens after sequencing data are delivered.
Learn Linux-based analysis steps through concrete examples for common file formats and tools.
Use the resource library to clarify workflows, expected deliverables, and project-specific analysis needs.
Contact SciBerg to integrate automated reporting, literature-context summaries, or private research assistants into your analysis process.
These pages provide learning outlines that can be expanded into lectures, tutorials, hands-on workshops, or internal training material.
Core topics for learning how to set up and perform basic NGS data-analysis workflows.
Foundational molecular biology topics relevant to sequencing, gene regulation, and genome analysis.
SciBerg can help with NGS data analysis, clinical bioinformatics, custom pipelines, automated reporting, and AI integration for academic, clinical, biotech, and industrial partners.