Answers.Body: <p>The first 6 column in standard featureCounts output represent what is in the column names. All columns after than (starting at 7) represent the counts for the sample(s). If you use a single bam file as input then it's one column, if you use many bams as input then it is one column per bam. If the counts are gene level, exon transcript or anything else depends on how you run the tool. Typically, with default settings, it is usually the raw gene level counts.</p>
  <p>Generally, you can sum up technical replicates (=lane/sequencing replicates to increase depth) prior to running normalization.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-29T14:20:00.847Z
Answers.Text: Thank you so much I appreciate your help!
  My other question is that since I didn't know that I could give multiple bam files to the feature count I instead ran the feature count on each bam file and then merged column 7 of the output text files and made my final count table in which rows are genes and columns are samples and cells are the raw gene counts. Now, as I know I should do normalization at this step, would TPM be a good method? if it's so off the table can you please let me know the sources I should use to learn how to proceed?
  Thanks a lot!
Answers.UserDisplayName: ToTheMoon
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Answers.CreationDate: 2024-01-29T14:48:11.200Z
Answers.Text: You simple list all bam files to be processed.
  
  featureCounts (options...) one.bam two.bam / or just *.bam
  
  Read manuals of edgeR or DESeq2, use these normalizations. TPM is poor. Many posts on this at biostars.org why that is.
Answers.UserDisplayName: ATpoint
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Answers.CreationDate: 2024-01-29T17:48:39.000Z
Answers.Text: Thanks, ATpoint!
Answers.UserDisplayName: ToTheMoon
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Answers.CreationDate: 2024-01-28T12:46:15.673Z
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Body: <p>After running this command:</p>
  <pre><code>featureCounts -p -s 2 -a <span class="math-container">$genome -o $</span>dir&quot;/&quot;<span class="math-container">$specie"/count_table/"$</span>value&quot;.txt&quot; $output_loc -T 8
  </code></pre>
  <p>on the BAM output of HISAT (<code>output_loc</code>), I got this output:</p>
  <p><a href="https://i.sstatic.net/3mbFg.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/3mbFg.png" alt="enter image description here" /></a></p>
  <p>Now, does the last column of this file show the gene count value?
  And if I merge the same column of different samples, how should I go through the normalization step?</p>
  <p>Thanks a lot for your help!</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-24T18:35:58.123Z
Comments.Text: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.
Comments.UserDisplayName: Community
Tags: <rna-seq><gene-expression><read-mapping><featurecounts>
Title: Featurecount output .txt file from bam file
ThreadText: # Featurecount output .txt file from bam file
  
  (Asked by: username_0 on 2024-01-24)
  
  After running this command:
  
  ```
  featureCounts -p -s 2 -a $genome -o $dir"/"$specie"/count_table/"$value".txt" $output_loc -T 8
  
  ```
  
  on the BAM output of HISAT (`output_loc`), I got this output:
  
  [![enter image description here](https://i.sstatic.net/3mbFg.png)](https://i.sstatic.net/3mbFg.png)
  
  Now, does the last column of this file show the gene count value?
  And if I merge the same column of different samples, how should I go through the normalization step?
  
  Thanks a lot for your help!
  
  **Tags:** rna-seq, gene-expression, read-mapping, featurecounts
  
  > **Comments:**
  > **username_1**: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2024-01-28. Score: 3 | Accepted answer
  
  The first 6 column in standard featureCounts output represent what is in the column names. All columns after than (starting at 7) represent the counts for the sample(s). If you use a single bam file as input then it's one column, if you use many bams as input then it is one column per bam. If the counts are gene level, exon transcript or anything else depends on how you run the tool. Typically, with default settings, it is usually the raw gene level counts.
  
  Generally, you can sum up technical replicates (=lane/sequencing replicates to increase depth) prior to running normalization.
  
  > **Comments:**
  > **username_0**: Thank you so much I appreciate your help! My other question is that since I didn't know that I could give multiple bam files to the feature count I instead ran the feature count on each bam file and then merged column 7 of the output text files and made my final count table in which rows are genes and columns are samples and cells are the raw gene counts. Now, as I know I should do normalization at this step, would TPM be a good method? if it's so off the table can you please let me know the sources I should use to learn how to proceed? Thanks a lot!  
  > **username_2**: You simple list all bam files to be processed.  featureCounts (options...) one.bam two.bam / or just *.bam  Read manuals of edgeR or DESeq2, use these normalizations. TPM is poor. Many posts on this at biostars.org why that is.  
  > **username_0**: Thanks, username_2!  
  
  ---
  
  