Page Comparison

...

idev -m 120180 -N 1 -A OTH21164 -r CoreNGS-Tue       # or -A TRA23004 
# -or-
idev -m 90120 -N 1 -A OTH21164 -p development   # or -A TRA23004 

Data staging

Set ourselves up to process some yeast data data in $SCRATCH, using some of best practices for organizing our workflow.

# Create a $SCRATCH area to work on data for this course,
# with a sub-directory for pre-processing raw fastq files
mkdir -p $SCRATCH/core_ngs/fastq_prep

# Make symbolic links to the original yeast data:
cd $SCRATCH/core_ngs/fastq_prep
ln -s -f $CORENGS/yeast_stuff/Sample_Yeast_L005_R1.cat.fastq.gz
ln -s -f $CORENGS/yeast_stuff/Sample_Yeast_L005_R2.cat.fastq.gz

# or
ln -s -f ~/CoreNGSsf /work/projects/BioITeam/projects/courses/Core_NGS_Tools/yeast_stuff/Sample_Yeast_L005_R1.cat.fastq.gz
ln -s -f ~/CoreNGSsf /work/projects/BioITeam/projects/courses/Core_NGS_Tools/yeast_stuff/Sample_Yeast_L005_R2.cat.fastq.gz

Illumina sequence data format (FASTQ)

GSAF gives you paired end sequencing data in two matching FASTQ format files, containing reads for each end sequenced. See where your data really is and how big it is.

# the #-l oroptions lnsays -sf /work/projects/BioITeam/projects/courses/Core_NGS_Tools/yeast_stuff/Sample_Yeast_L005_R1.cat.fastq.gz
ln -sf /work/projects/BioITeam/projects/courses/Core_NGS_Tools/yeast_stuff/Sample_Yeast_L005_R2.cat.fastq.gz

Illumina sequence data format (FASTQ)

GSAF gives you paired end sequencing data in two matching FASTQ format files, containing reads for each end sequenced. See where your data really is and how big it is.

# the -l options says "long listing" which shows where the link goes,
# but doesn't show details of the real file
ls -l

#"long listing" which shows where the link goes,
# but doesn't show details of the real file
ls -l

# the -L option says to follow the link to the real file, 
#     -l means long listing (includes size) 
#     -h says "human readable" (e.g. MB, GB)
ls -Llh

...

Exercise: What character in the quality score string in the FASTQ entry above represents the best base quality? Roughly what is the error probability estimated by the sequencer?

About compressed files

...

Exercise: About how big are the compressed files? The uncompressed files? About what is the compression factor?

...

With no options, gzip compresses the file you give it in-place. Once all the content has been compressed, the original uncompressed file is removed, leaving only the compressed version (the original file name plus a .gz extension). The gunzip function works in a similar manner, except that its input is a compressed file with a .gz file and produces an uncompressed file without the .gz extension.

# if the $CORENGS environment variable is not defined
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools

# make sure you're in your $SCRATCH/core_ngs/fastq_prep directory
cd $SCRATCH/core_ngs/fastq_prep

# Copy over a small, uncompressed fastq file
cp $CORENGS/misc/small.fq .

# check the size, then compress it in-place
ls -lh small*
gzip small.fq

# check the compressed file size
ls -lh small*

# uncompress it again
gunzip small.fq.gz
ls -lh small*

...

...

One of the challenges of dealing with large data files, whether compressed or not, is finding your way around the data – finding and looking at relevant pieces of it. Except for the smallest of files, you can't open them up in a text editor because those programs read the whole file into memory, so will choke on sequencing data files! Instead we use various techniques to look at pieces of the files at a time. (Read more about commands for Displaying file contents)

The first technique is the use of pagers – we've already seen this with the more command. Review its use now on our small uncompressed file:

# Setup (if needed) needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
cp $CORENGS/misc/small.fq .

...

If you start less with the -N option, it will display line numbers Numbers. Using the -I options allows pattern searches to be case-Insensitive.

Exercise: What line of small.fq contains the read name with grid coordinates 2316:10009:100563?

...

# Setup (if needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools 
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
cp $CORENGS/misc/small.fq .

...

cat -n small.fq | tail

...

The pipe operator ( | ) connects one program's standard output to the next program's standard input. The power of the Linux command line is due in no small part to the power of piping. (Read more about about Piping and Standard Unix I/O streams)

...

• When you execute the head -100 small.fq | more command, head starts writing lines of the small.fq file to standard output.
• Because of the pipe, the output does not go to the Terminal, but is connected to the standard input  of the more command.
• Instead of reading lines from a file you specify as a command-line argument, more obtains its input from standard input.
• The more command writes a page of text to standard output, which is displayed on the Terminal.
  
  

...

But what's really cool about tail is its -n +NN syntax. This displays all the lines starting at line NN. Note this syntax: the -n option switch follows by a plus sign ( + ) in front of a number – the plus sign is what says "starting at this line"! Try these examples:

# Setup (if needed) (if needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools 
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
cp $CORENGS/misc/small.fq .

...

# shows the last 10 lines
tail small.fq

# shows the last 100 lines -- might want to pipe this to more to see a bit at a time
tail -100 small.fq | more

# shows all the lines starting at line 900 -- better pipe it to a pager!
# cat -n adds line numbers to its output so we can see where we are in the file
cat -n small.fq | tail -n +900 | more

# shows 15 lines starting at line 900 because we pipe to head -15
tail -n +900 small.fq | head -15

Read more about head and tail in Displaying file contents.

zcat and gunzip -c tricks

...

# Setup (if needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools 
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
cp $CORENGS/misc/small.fq .

...

zcat Sample_Yeast_L005_R1.cat.fastq.gz | more
zcat Sample_Yeast_L005_R1.cat.fastq.gz | less -N
zcat Sample_Yeast_L005_R1.cat.fastq.gz | head
zcat Sample_Yeast_L005_R1.cat.fastq.gz | tail
zcat Sample_Yeast_L005_R1.cat.fastq.gz | tail -n +901 | head -8

# include original line numbers
zcat Sample_Yeast_L005_R1.cat.fastq.gz | cat -n | tail -n +901 | head -8

...

...

# Setup (if needed)
 Setup (if needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools 
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
cp $CORENGS/misc/small.fq .

...

echo $((2368720 / 4))

Here's another trick: backticks backtick evaluation. When you enclose a command expression in backtick quotes ( ` ) the enclosed expression is evaluated and its standard output substituted into the string. (Read more about Quoting in the shell)

Here's how you would combine this math expression with zcat line counting on your file using the magic of backtick evaluation. Notice that the wc -l expression is what is reading from standard input.

# Setup (if needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools 
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
ln -sf $CORENGS/yeast_stuff/Sample_Yeast_L005_R1.cat.fastq.gz
ln -sf $CORENGS/yeast_stuff/Sample_Yeast_L005_R2.cat.fastq.gz

...

A better way to do math

Well, doing math in bash is pretty awful – there has to be something better. There is! It's called awk, which is a powerful scripting language that is easily invoked from the command line.

In the code below we pipe the output from wc -l (number of lines in the FASTQ file) to awk, which executes its body (the statements between the curly braces ( {  } ) for each line of input. Here the input is just one line, with one field – the line count. The awk body just divides the 1st input field ($1) by 4 and writes the result to standard output. (Read more about awk in Advanced Some Linux commands: awk)

# Setup (if needed)
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
ln -sf $CORENGS/yeast_stuff/Sample_Yeast_L005_R1.cat.fastq.gz
ln -sf $CORENGS/yeast_stuff/Sample_Yeast_L005_R2.cat.fastq.gz

(if needed)
export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools 
mkdir -p $SCRATCH/core_ngs/fastq_prep

cd 

...

The bash shell treats dollar sign ( $ ) as an evaluation operator, so will normally attempt to evaluate the environment variable name following the $ and substitute its value in the output (e.g. echo $SCRATCH). But we don't want that evaluation to be applied to the {print $1 / 4} script argument passed to awk; instead we want awk to see the literal string {print $1 / 4} as its script. To achieve this result we surround the script argument with single quotes ( ' ' ), which tells the shell to treat everything enclosed by the quotes as literal text, and not perform any metacharacter evaluation.

Processing multiple compressed files

You've probably figured out by now that you can't easily use filename wildcarding along with zcat and piping to process multiple files. For this, you need to code a for loop in bash. Fortunately, this is pretty easy. Try this:

for fname in *.gz; do
  echo "Processing $fname"
  echo "..$fname has `zcat $fname | wc -l | awk '{print $1 / 4}'` sequences"
done

...

Each time through the for loop, the next item in the evaluation expression (here *.gz) is assigned to the formal argument (here fname). Note that items in the evaluation expression are separated by spaces – not Tabs.

# One line for each clause, no semicolons
for <variable name> in <expression>
do 
  <something>; <something else>
done

# All on one line, with semicolons separating clauses
for <variable name> in <expression>; do <something>; <something else>; done$SCRATCH/core_ngs/fastq_prep
ln -sf $CORENGS/yeast_stuff/Sample_Yeast_L005_R1.cat.fastq.gz
ln -sf $CORENGS/yeast_stuff/Sample_Yeast_L005_R2.cat.fastq.gz

cd $SCRATCH/core_ngs/fastq_prep
zcat Sample_Yeast_L005_R1.cat.fastq.gz | wc -l | awk '{print $1 / 4}'

Note that $1 means something different in awk – the 1st whitespace-delimited input field – than it does in bash, where it represents the 1st argument to a script or function (technically, the 1 environment variable). This is an example of where a metacharacter- the dollar sign ( $ ) here – has  a different meaning for two different programs. (Read more about Literal characters and metacharacters)

The bash shell treats dollar sign ( $ ) as an evaluation operator, so will normally attempt to evaluate the environment variable name following the $ and substitute its value in the output (e.g. echo $SCRATCH). But we don't want that evaluation to be applied to the {print $1 / 4} script argument passed to awk; instead we want awk to see the literal string {print $1 / 4} as its script. To achieve this result we surround the script argument with single quotes ( ' ' ), which tells the shell to treat everything enclosed by the quotes as literal text, and not perform any metacharacter processing. (Read more about Quoting in the shell)

Processing multiple compressed files

You've probably figured out by now that you can't easily use filename wildcarding along with zcat and piping to process multiple files. For this, you need to code a for loop in bash. Fortunately, this is pretty easy. Try this:

cd $SCRATCH/core_ngs/fastq_prep
for fname in *.gz; do
  echo "Processing $fname"
  echo "..$fname has `zcat $fname | wc -l | awk '{print $1 / 4}'` sequences"
done

Each time through the for loop, the next item in the argument list (here the files matching the wildcard glob *.gz) is assigned to the for loop's formal argument (here the variable fname). The actual filename is then referenced as$fname inside the loop. (Read more about Bash control flow)