Category Archives: Miscellaneous

TrimGalore/FastQC/MultiQC – Trim 10bp 5’/3′ ends C.virginica MBD BS-seq FASTQ data

Steven found out that the Bismarck documentation (Bismarck is the bisulfite aligner we use in our BS-seq pipeline) suggests trimming 10bp from both the 5′ and 3′ ends. Since this is the next step in our pipeline, we figured we should probably just follow their recommendations!

TrimGalore job script:

Standard error was redirected on the command line to this file:

MD5 checksums were generated on the resulting trimmed FASTQ files:

All data was copied to my folder on Owl.

Checksums for FASTQ files were verified post-data transfer (data not shown).

Results:

Output folder:

FastQC output folder:

MultiQC output folder:

MultiQC HTML report:

Hey! Look at that! Everything is much better! Thanks for the excellent documentation and suggestions, Bismarck!

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DNA Isolation & Quantification – Metagenomics Water Filters

Isolated DNA from the following two filters:

DNA was isolated with the DNeasy Blood & Tissue Kit (Qiagen), following a modified version of the Gram-Positive Bacteria protocol:

  • filters were unfolded and unceremoniously stuffed into 1.7mL snap cap tubes
  • did not perform enzymatic lysis step
  • filters were incubated with 400μL of Buffer AL and 50μL of Proteinase K (both are double the volumes listed in the kit and are necessary to fully coat the filter in a 1.7mL snap cap tube)
  • 56oC incubations were performed overnight
  • 400μL of 100% ethanol was added to each after the 56oC incubation
  • samples were eluted in 50μL of Buffer AE
  • all spins were performed at 20,000g

Samples were quantified with the Roberts Lab Qubit 3.0 and the Qubit 1x dsDNA HS Assay Kit.

Used 10μL of each sample for measurement (see Results for update).

Results:

Raw data (Google Sheet): 20180411_qubit_metagenomics_filters

Sample Concentration(ng/μL) Initial_volume(μL) Yield(ng)
filter 5/22 #7 pH8.2 20.8 50 1040
filter 5/26 #7 pH8.2 11.6 50 580

NOTE: For “filter 5/22 #7 pH8.2″ the initial quantification using 10μL ended up being too concentrated. Re-ran using 5μL.

Both samples have yielded DNA. This is, obviously, an improvement over the previous attempts to isolate DNA from ammonium bicarbonate filter rinses that Emma supplied me with.

Will discuss with Steven and get an idea of which filters to isolate additional DNA from.

Samples were stored Sam gDNA Box #2, positions G6 & G7. (FTR 213, #27 (small -20oC frezer)

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TrimGalore/FastQC/MultiQC – 2bp 3′ end Read 1s Trim C.virginica MBD BS-seq FASTQ data

Earlier today, I ran TrimGalore/FastQC/MultiQC on the Crassostrea virginica MBD BS-seq data from ZymoResearch and hard trimmed the first 14bp from each read. Things looked better at the 5′ end, but the 3′ end of each of the READ1 seqs showed a wonky 2bp blip, so decided to trim that off.

I ran TrimGalore (using the built-in FastQC option), with a hard trim of the last 2bp of each first read set that had previously had the 14bp hard trim and followed up with MultiQC for a summary of the FastQC reports.

TrimGalore job script:

Standard error was redirected on the command line to this file:

MD5 checksums were generated on the resulting trimmed FASTQ files:

All data was copied to my folder on Owl.

Checksums for FASTQ files were verified post-data transfer (data not shown).

Results:

Output folder:

FastQC output folder:

MultiQC output folder:

MultiQC HTML report:

Well, this is a bit strange, but the 2bp trimming on the read 1s looks fine, but now the read 2s are weird in the same region!

Regardless, while this was running, Steven found out that the Bismarck documentation (Bismarck is the bisulfite aligner we use in our BS-seq pipeline) suggests trimming 10bp from both the 5′ and 3′ ends. So, maybe this was all moot. I’ll go ahead and re-run this following the Bismark recommendations.

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TrimGalore/FastQC/MultiQC – 14bp Trim C.virginica MBD BS-seq FASTQ data

Yesterday, I ran TrimGalore/FastQC/MultiQC on the Crassostrea virginica MBD BS-seq data from ZymoResearch with the default settings (i.e. “auto-trim”). There was still some variability in the first ~15bp of the reads and Steven wanted to see how a hard trim would change things.

I ran TrimGalore (using the built-in FastQC option), with a hard trim of the first 14bp of each read and followed up with MultiQC for a summary of the FastQC reports.

TrimGalore job script:

Standard error was redirected on the command line to this file:

MD5 checksums were generated on the resulting trimmed FASTQ files:

All data was copied to my folder on Owl.

Checksums for FASTQ files were verified post-data transfer (data not shown).

Results:

Output folder:

FastQC output folder:

MultiQC output folder:

MultiQC HTML report:

OK, this trimming definitely took care of the variability seen in the first ~15bp of all the reads.

However, I noticed that the last 2bp of each of the Read 1 seqs all have some wonky stuff going on. I’m guessing I should probably trim that stuff off, too…

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TrimGalore/FastQC/MultiQC – Auto-trim C.virginica MBD BS-seq FASTQ data

Yesterday, I ran FastQC/MultiQC on the Crassostrea virginica MBD BS-seq data from ZymoResearch. Steven wanted to trim it and see how things turned out.

I ran TrimGalore (using the built-in FastQC option) and followed up with MultiQC for a summary of the FastQC reports.

TrimGalore job script:

Standard error was redirected on the command line to this file:

MD5 checksums were generated on the resulting trimmed FASTQ files:

All data was copied to my folder on Owl.

Checksums for FASTQ files were verified post-data transfer.

Results:

Output folder:

FastQC output folder:

MultiQC output folder:

MultiQC HTML report:

Overall, the auto-trim didn’t alter things too much. Specifically, Steven is concerned about the variability in the first 15bp (seen in the Per Base Sequence Content section of the MultiQC output). It was reduced, but not greatly. Will perform an independent run of TrimGalore and employ a hard trim of the first 14bp of each read and see how that looks.

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FastQC/MultiQC – C. virginica MBD BS-seq Data

Per Steven’s GitHub Issues request, I ran FastQC on the Eastern oyster MBD bisulfite sequencing data we recently got back from ZymoResearch.

Ran FastQC locally with the following script: 20180409_fastqc_Cvirginica_MBD.sh


#!/bin/bash
/home/sam/software/FastQC/fastqc 
--threads 18 
--outdir /home/sam/20180409_fastqc_Cvirginica_MBD 
/mnt/owl/nightingales/C_virginica/zr2096_10_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_10_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_1_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_1_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_2_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_2_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_3_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_3_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_4_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_4_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_5_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_5_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_6_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_6_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_7_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_7_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_8_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_8_s1_R2.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_9_s1_R1.fastq.gz 
/mnt/owl/nightingales/C_virginica/zr2096_9_s1_R2.fastq.gz

MultiQC was then run on the FastQC output files.

All files were moved to Owl after the jobs completed.

Results:

FastQC Output folder: 20180409_fastqc_Cvirginica_MBD/

MultiQC Output folder: 20180409_fastqc_Cvirginica_MBD/multiqc_data/

MultiQC report (HTML): 20180409_fastqc_Cvirginica_MBD/multiqc_data/multiqc_report.html

Everything looks good to me.

Steven’s interested in seeing what the trimmed output would look like (and, how it would impact mapping efficiencies). Will initiate trimming.

See the GitHub issue linked above for the full discussion.

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More RNA extractions

Continued RNA extractions of Anthopleura elegantissima samples using the Qiagen RNeasy kit. Further information on these samples can be found in this post. Qiashredder columns were again used for sample homogenization, and the Qubit RNA HS assay for quantification. Here are the results:

Species Sample RNA (ng/ul) Total vol (ul) Notes
A. elegantissima A4-001 96 40
A. elegantissima A5-416 59 40
A. elegantissima A6-B22 >100 40
A. elegantissima H4-415 >100 40
A. elegantissima H1-518 >100 40
A. elegantissima H2-019 >100 40
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DNA Isolation & Quantification – Geoduck larvae metagenome filter rinses

This is another attempt to isolate DNA from two more of the geoduck hatchery metagenome samples Emma delivered on 20180313.

The previous attempt, using DNAzol, did not yield any DNA.

I isolated DNA from the following two samples:

  • MG 5/19 #4
  • MG 5/26 #4

I used the DNA Stool Kit (Qiagen), following the “Stool Human DNA” protocol with the following changes:

  • Incubated @ 95oC for 5mins after initial addition of Buffer ASL. This is a lysis step that might help increase yields (see the “Stool Pathogen Detection” protocol)
  • Did not add InhibitEX Tablet. Deemed unnecessary, since these weren’t stool samples.
  • Eluted in 50μL of Buffer AE

I opted to follow the “Stool Human DNA” protocol, as it processes a larger portion of the initial sample, compared to the “Stool Pathogen Detection” protocol (600μL vs. 200μl)

Samples were quantified using the Roberts Lab Qubit 3.0 with the Qubit High Sensitivity dsDNA Kit (Invitrogen).

10μL of each sample were used.

Results:

Neither sample yielded any detectable DNA. Will discuss with Steven.

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Titrations – Yaamini’s Seawater Samples

All data is deposited in the following GitHub repo:

Sample sizes: ~50g

LabX Method:

Daily pH calibration data file:

Daily pH log file:

Titrant batch:

CRM Batch:

Daily CRM data file:

Sample data file(s):

See metadata file for sample info (including links to master samples sheets):

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Titrations – Yaamini’s Seawater Samples

All data is deposited in the following GitHub repo:

Sample sizes: ~50g

LabX Methods:

Daily pH calibration data file:

Daily pH log file:

Titrant batch:

CRM Batch:

Daily CRM data file:

Sample data file(s):

See metadata file for sample info (including links to master samples sheets):

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