add sequence tutorial

Author: danielle-pinto

cookbook/sequences.md

@@ -33,7 +33,8 @@ The template of a sequence record is:
 ```
 
 ### FASTQ files
-FASTQ files are also text-based files that contain sequences, along with a name and description. However, they also store sequence quality information (the Q is for quality!).
+FASTQ files are also text-based files that contain sequences, along with a name and description.   
+However, they also store sequence quality information (the Q is for quality!).
 
 The template of a sequence record is:
 ```
@@ -43,6 +44,14 @@ The template of a sequence record is:
 {qualities}
 ```
 
+Here is an example record:
+```
+@FSRRS4401BE7HA
+tcagTTAAGATGGGAT
++
+###EEEEEEEEE##E#
+```
+
 ### FAI files
 
 FAI (FASTA index) files are used in conjuction with FASTA/FASTQ files.   
@@ -89,11 +98,76 @@ In this case, there is only one sequence.
 
 Let's try reading in a larger fastq file. 
 
+The raw reads for a Staphylococcus aureus isolate was sequenced with Pac-Bio and uploaded to NCBI [here](https://trace.ncbi.nlm.nih.gov/Traces/?run=SRR12147540).   
+The link to download the raw fastq's can be found [here](https://trace.ncbi.nlm.nih.gov/Traces/?run=SRR12147540).
+
+The biosample ID for this sample is `SAMN14830786`.
+This ID refers to the physical bacterial isolate.  
+
+The SRA sample accession number (an internal value used within Sequence Read Archive) is `SRS6947643`.    
+
+Both values correspond to one another and are helpful identifiers. 
+
+The SRR (sample run accession number) is the unique identifier within SRA   
+and corresponds to the specific sequencing run within SRA. 
+
+In a later tutorial, we will discuss how we can download this file within julia with the SRR.
+
+But for now, the file can be downloaded using curl 
+
+
+```
+curl -L --retry 5 --retry-delay 2 \
+  "https://trace.ncbi.nlm.nih.gov/Traces/sra-reads-be/fastq?acc=SRR12147540" \
+  | gzip -c > SRR12147540.fastq.gz
+```
+This file is gzipped, so we'll need to account for that as we are reading it in.
+
+Instead of printing out every record (this isn't super practical because it's a big file), let's save all the records into a vector.
+
 ```julia
+using CodecZlib
 
+records = []
 
+FASTQReader(GzipDecompressorStream(open("assets/SRR12147540.fastq.gz"))) do reader
+           for record in reader
+               push!(records, record)
+           end
+       end
+```
+
+We can see how many reads there are by looking at the length of `records`.
 
+```julia
+julia> length(records)
+163528
 ```
 
+Let's take a look at what the first 10 reads look like:
+
+```
+julia> records[1:10]
+10-element Vector{Any}:
+ FASTX.FASTQ.Record("SRR12147540.1  length=43", "TTTTTTTTCCTTTCTTTCT…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.2  length=40", "TTTGTTTTTTTTTGTTTTC…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.3  length=32", "TTTTTTTTTGTTCTTTGGT…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.4  length=40", "TTTTCTTTTCCTTCTTTTC…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.5  length=55", "TGTTGTTTGTGTCTCGTTT…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.6  length=166", "TTTCCTTTTTTTTCCTCTC…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.7  length=338", "TGACCACCTTAGAACTTGG…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.8  length=245", "ACGCCGCGGCCAAAGAACG…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.9  length=157", "TTTGTTTGCGCGGTCTCTT…", "$$$$$$$$$$$$$$$$$$$…")
+ FASTX.FASTQ.Record("SRR12147540.10  length=100", "TTCTTTCGCCTTTTTGCCT…", "$$$$$$$$$$$$$$$$$$$…")
+ ```
+
+ All of the nucleotides in all of the reads have a quality score of `$`, which corresponds to a probabilty of error of 0.50119.  
+ More information about how to convert ASCII values to quality scores [here](https://people.duke.edu/~ccc14/duke-hts-2018/bioinformatics/quality_scores.html).  
+ This would be quite poor if we were looking at Illumia data.  
+ However, because of how Pacbio chemistry works,  
+ the quality scores are often flattened and there is simply a placeholder value on this line.  
+ This does not mean our reads are trash!  
+ Now that we've learned how to read files in and manipulate them a bit,  
+let's see if we can align the mecA gene to the Staphylococcus aureus genome.