How to use STAR output with quantification tools?

Prepare STAR Output for Quantification

• Ensure you have completed the STAR alignment, producing output files such as "Aligned.out.sam" or "Aligned.sortedByCoord.out.bam".

 

• Install necessary quantification tools such as RSEM, featureCounts, or HTSeq, depending on your preference and analysis requirements.

Convert SAM to BAM format if Necessary

• If your STAR output is in SAM format, use tools like Samtools to convert it to BAM format. This can be done using the command: samtools view -Sb Aligned.out.sam > Aligned.out.bam.

 

• Sort and index the BAM file with Samtools: samtools sort -o Aligned.sortedByCoord.out.bam Aligned.out.bam and samtools index Aligned.sortedByCoord.out.bam.

Prepare Annotation Files

• Download the appropriate annotation file (GTF/GFF) for your organism from a reliable database such as Ensembl or UCSC Genome Browser.

 

• Ensure the annotation file corresponds to the reference genome version used in the STAR alignment.

Perform Quantification with HTSeq

• Run HTSeq to count reads mapping to each gene: htseq-count -f bam -s no Aligned.sortedByCoord.out.bam annotation.gtf > counts.txt.

 

• Use options such as -s yes if your data is strand-specific, or adjust other parameters based on your experimental design.

Perform Quantification with featureCounts

• Run featureCounts for efficient read counting: featureCounts -a annotation.gtf -o counts.txt Aligned.sortedByCoord.out.bam.

 

• Consider appropriate parameters such as -g gene\_id if you need gene-level summarization, or adjust for paired-end data if applicable.

Perform Quantification with RSEM

• If using RSEM, first prepare the reference using rsem-prepare-reference with your reference sequence and GTF annotation.

 

• Run RSEM using STAR's BAM output: rsem-calculate-expression --bam Aligned.sortedByCoord.out.bam ref_name output_prefix.

Analyze and Interpret Quantification Results

• Extract useful insights from counts files generated by your chosen quantification tool, which typically need normalization to account for factors like sequencing depth.

 

• Consider using additional tools like DESeq2 or EdgeR for differential expression analysis on processed count data.

Document and Share Findings

• Ensure all steps and command-line instructions are documented to enhance reproducibility and comprehension for collaborators or reviewers.

 

• Prepare figures or tables summarizing quantification results, highlighting significant findings or potential biological implications.