Sam’s Notebook - Data Received – Jay’s Coral epiRADseq

Previously downloaded Jay’s epiRADseq data that was provided by the Genomic Sequencing Laboratory at UC-Berkeley. It was provided already demultiplexed (which is very nice of them!). To be completionists on our end, we requested the non-demultiplexed data set.

Downloaded the FASTQ files from the project directory to Owl/nightingales/Porites_spp:

<code>time wget -r -np -nc --ask-password ftp://gslftp@gslserver.qb3.berkeley.edu/160830_100PE_HS4KB_L4</code>

It took awhile:

<code>FINISHED --2016-09-19 11:39:21--
Total wall clock time: 4h 26m 21s
Downloaded: 11 files, 36G in 4h 17m 18s (2.39 MB/s)</code>

Here are the files:

JD001_A_S1_L004_R2_001.fastq.gz
JD001_A_S1_L004_R1_001.fastq.gz
JD001_A_S1_L004_I1_001.fastq.gz
160830_100PE_HS4KB_L4_Stats
- AdapterTrimming.txt
- ConversionStats.xml
- DemultiplexingStats.xml
- DemuxSummaryF1L4.txt
- FastqSummaryF1L4.txt

Generated MD5 checksums for each file:

<code>for i in *.gz; do md5 $i >> checksums.md5; done</code>

Calculate total number of reads for this sequencing run:

<code>totalreads=0; for i in *S1*R*.gz; do linecount=`gunzip -c "$i" | wc -l`; readcount=$((linecount/4)); totalreads=$((readcount+totalreads)); done; echo $totalreads
</code>

Total reads: 662,868,166 (this isn’t entirely accurate, as it is counting all three files; probably should’ve just counted the R1 and R2 files…)

Calculate read counts for each file and write the data to the readme.md file in the Owl/web/nightingales/Porites_spp directory:

<code>for i in *S1*R*.gz; do linecount=`gunzip -c "$i" | wc -l`; readcount=$(($linecount/4)); printf "%s\t%s\n" "$i" "$readcount" >> readme.md; done</code>

See this Jupyter notebook for code explanations.

Added sequencing info to [Next_Gen_Seq_Library_Database (Google Sheet)(https://docs.google.com/spreadsheets/d/1r4twxfBHpWfQoznbn2dAQhgMvmlZvQqW9I2_uVZX_aU/edit?usp=sharing) and the Nightingales Spreadsheet (Google Sheet) and Nightingales Fusion Table (Google Fusion Table).