<p>You can easily do it via Notepad++ or even Excel. Just don't forget to save the output file as a <code>.csv</code> file (comma-separated value). 
The info inside should look like (my working example):</p>

<pre><code>id,state
lar_control141,control
lar_control142,control
lar_control143,control
lar_probiotic142,probiotic
lar_probiotic143,probiotic
lar_probiotic144,probiotic
lar_probiotic145,probiotic
lar_probiotic146,probiotic
</code></pre>

<p>That should work</p>

CC BY-SA 4.0
2020-05-02T09:43:24.900Z
2020-05-02T09:43:24.900Z
Dmitrii Trubetskoy
<p>I am trying to reproduce the work of <a href="https://www.nature.com/articles/nprot.2016.095" rel="nofollow noreferrer">this paper</a>
<a href="https://www.nature.com/articles/nprot.2016.095" rel="nofollow noreferrer">[1]</a>, and I have run StringTie successfully, but after that I have to run Ballgown but could not understand this command:</p>

<pre><code>&gt;pheno_data = read.csv("geuvadis_phenodata.csv")
</code></pre>

<p>Actually, I dont know how to make the .csv file of my samples. What phenotype information should this csv contain?</p>

<p>I have checked the supplementary data of this research article but didn't find any .csv file.</p>

<p>How I can make the .csv file for my samples to load the phenotype data for ballgown?</p>

<blockquote>
  <ol start="8">
  <li><p>Load the phenotype data for the samples. An example file called
  geuvadis_phenodata.csv is included with the data files for this protocol
  (ChrX_data). In general, you will have to create this file yourself. It contains
  information about your RNA sequencing samples, formatted as illustrated in
  this csv (comma-separated values) file. Each sample should be described on
  one row of the file and each column should contain one variable. To read this
  file into R we use the command read.csv. In this file the values are
  separated by commas, but if the file were tabdelimited you could use the
  function read.table.</p>
  
  <blockquote>
    <p>pheno_data = read.csv("geuvadis_phenodata.csv")</p>
  </blockquote></li>
  </ol>
</blockquote>

<hr>

<ol>
<li>Pertea <em>et al</em>, Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown, <em>Nature Protocols</em> volume 11, pages 1650–1667 (2016) </li>
</ol>

<rna-seq><bioconductor><differential-expression>
load the phenotype data for ballgown
# load the phenotype data for ballgown

(Asked by: username_0 on 2019-03-28)

I am trying to reproduce the work of this paper
[1], and I have run StringTie successfully, but after that I have to run Ballgown but could not understand this command:
>pheno_data = read.csv("geuvadis_phenodata.csv")

Actually, I dont know how to make the .csv file of my samples. What phenotype information should this csv contain?
I have checked the supplementary data of this research article but didn't find any .csv file.
How I can make the .csv file for my samples to load the phenotype data for ballgown?


Load the phenotype data for the samples. An example file called
  geuvadis_phenodata.csv is included with the data files for this protocol
  (ChrX_data). In general, you will have to create this file yourself. It contains
  information about your RNA sequencing samples, formatted as illustrated in
  this csv (comma-separated values) file. Each sample should be described on
  one row of the file and each column should contain one variable. To read this
  file into R we use the command read.csv. In this file the values are
  separated by commas, but if the file were tabdelimited you could use the
  function read.table.

pheno_data = read.csv("geuvadis_phenodata.csv")





Pertea et al, Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown, Nature Protocols volume 11, pages 1650–1667 (2016)

**Tags:** rna-seq, bioconductor, differential-expression

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## 1 answers

### Answer by username_1 on 2020-05-02. Score: 1

You can easily do it via Notepad++ or even Excel. Just don't forget to save the output file as a .csv file (comma-separated value). 
The info inside should look like (my working example):
id,state
lar_control141,control
lar_control142,control
lar_control143,control
lar_probiotic142,probiotic
lar_probiotic143,probiotic
lar_probiotic144,probiotic
lar_probiotic145,probiotic
lar_probiotic146,probiotic

That should work


---

