Posts by Year

2020

Primer Design and In-Silico Testing - Geoduck Reproduction Primers

  • 1 min read

Shelly asked that I re-run the primer design pipeline that Kaitlyn had previously run to design a set of reproduction-related qPCR primers. Unfortunately, Kaitlyn’s Jupyter Notebook wasn’t backed up and she accidentally deleted it, I believe, so there’s no real record of how she designed the primers. However, I do know that she was unable to run the EMBOSS primersearch tool, which will check your primers against a set of sequences for any other matches. This is useful for confirming specificity.

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Metagenomics - Data Extractions Using MEGAN6

  • 1 min read

Decided to finally take the time to methodically extract data from our metagenomics project so that I have the tables handy when I need them and I can easily share them with other people. Previously, I hadn’t done this due to limitations on looking at the data remotely. I finally downloaded all of the RMA6 files from 20191014 after being fed up with the remote desktop connection and upgrading the size of my hard drive (5 of the six RMA6 files are >40GB in size).

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Sequence Extractions - C.bairdi Transcriptomes v2.0 and v3.0 Excluding Alveolata with MEGAN6 on Swoose

  • ~1 min read

Continuing to try to identify the best C.bairdi transcriptome, we decided to extract all non-dinoflagellate sequences from cbai_transcriptome_v2.0 (RNAseq shorthand: 2018, 2019, 2020-GW, 2020-UW) and cbai_transcriptome_v3.0 (RNAseq shorthand: 2018, 2019, 2020-UW). Both of these transcriptomes were assembled without any taxonomic filter applied. DIAMOND BLASTx and conversion to MEGAN6 RMA6 files was performed yesterday (20200604).

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Transcriptome Assembly - C.bairdi All Pooled Arthropoda-only RNAseq Data with Trinity on Mox

  • 2 min read

For completeness sake, I wanted to create an additional C.bairdi transcriptome assembly that consisted of Arthropoda only sequences from just pooled RNAseq data (since I recently generated a similar assembly without taxonomically filtered reads on 20200518). This constitutes samples we have designated: 2018, 2019, 2020-UW. A de novo assembly was run using Trinity on Mox. Since all pooled RNAseq libraries were stranded, I added this option to Trinity command.

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Transcriptome Assembly - P.trituberculatus (Japanese blue crab) NCBI SRA BioProject PRJNA597187 Data with Trinity on Mox

  • 3 min read

After generating a number of C.bairdi (Tanner crab) transcriptomes, we decided we should compare them to evaluate which to help decide which one should become our “canonical” version. As part of that, the Trinity wiki offers a list of tools that one can use to check the quality of transcriptome assemblies. Some of those require a transcriptome of a related species.

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SRA Library Assessment - Determine RNAseq Library Strandedness from P.trituberculatus SRA BioProject PRJNA597187

  • 3 min read

We’ve produced a number of C.bairid transcriptomes utilizing different assembly approaches (e.g. Arthropoda reads only, stranded libraries only, mixed strandedness libraries, etc) and we want to determine which of them is “best”. Trinity has a nice list of tools to assess the quality of transcriptome assemblies, but most of the tools rely on comparison to a transcriptome of a related species.

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Transcriptome Assembly - C.bairdi All Pooled RNAseq Data Without Taxonomic Filters with Trinity on Mox

  • 2 min read

Steven asked that I assemble a transcriptome with just our pooled C.bairdi RNAseq data (not taxonomically filtered; see the FastQ list file linked in the Results section below). This constitutes samples we have designated: 2018, 2019, 2020-UW. A de novo assembly was run using Trinity on Mox. Since all pooled RNAseq libraries were stranded, I added this option to Trinity command.

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GO to GOslim - C.bairdi Enriched GO Terms from 20200422 DEGs

  • 6 min read

After running pairwise comparisons and identify differentially expressed genes (DEGs) on 20200422 and finding enriched gene ontology terms, I decided to map the GO terms to Biological Process GOslims. Additionally, I decided to try another level of comparison (I’m not sure how valid it is), whereby I will count the number of GO terms assigned to each GOslim and then calculate the percentage of GOterms that get assigned to each of the GOslim categories. The idea being that it might help identify Biological Processes that are “favored” in a given set of DEGs. I decided to set up “fancy” pyramid plots to view a given set of GO-GOslims for each DEG comparison.

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qPCR - C.bairdi RNA Check for Residual gDNA

  • 1 min read

Previuosly checked existing crab RNA for residual gDNA on 20200226 and identified samples with yields that were likely too low, as well as samples with residual gDNA. For those samples, was faster/easier to just isolate more RNA and perform the in-column DNase treatment in the ZymoResearch Quick DNA/RNA Microprep Plus Kit; this keeps samples concentrated. So, I isolated more RNA on 20200306 and now need to check for residual gDNA.

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Trimming/MultiQC - Methcompare Bisulfite FastQs with fastp on Mox

  • 3 min read

Steven asked me to trim a set of FastQ files, provided by Hollie Putnam, in preparation for methylation analysis using Bismark. The analysis is part of a coral project comparing DNA methylation profiles of different species, as well as comparing different sample prep protocols. There’s a dedicated GitHub repo here:

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RNA Isolation and Quantification - C.bairdi RNA from Hemolymph Pellets in RNAlater

  • ~1 min read

Based on qPCR results testing for residual gDNA from 20200225, a set of 24 samples were identified that required DNase treatment and/or additional RNA. I opted to just isolate more RNA from all samples, since the kit includes a DNase step and avoids diluting the existing RNA using the Turbo DNA-free Kit that we usully use. Isolated RNA using the Quick DNA/RNA Microprep Kit (ZymoResearch; PDF) according to the manufacturer’s protocol for liquids/cells in RNAlater.

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DNA Isolation, Quantification, and Gel - C.bairdi gDNA Sample 6129_403_26

  • 1 min read

In order to do some genome sequencing on C.bairid and Hematodinium, we need hihg molecular weight gDNA. I attempted this twice before, using two different methods (Quick DNA/RNA Microprep Kit (ZymoResearch) on 20200122 and the E.Z.N.A Mollusc DNA Kit (Omega) on 20200108) using ~10yr old ethanol-preserved tissue provided by Pam Jensen. Both methods yielded highly degrade gDNA. So, I’m now attempting to get higher quality gDNA from the RNAlater-preserved hemolymph pellets from this experiment.

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Gene Expression - Hematodinium MEGAN6 with Trinity and EdgeR

  • 2 min read

After completing annotation of the Hematodinium MEGAN6 taxonomic-specific Trinity assembly using Trinotate on 20200126, I performed differential gene expression analysis and gene ontology (GO) term enrichment analysis using Trinity’s scripts to run EdgeR and GOseq, respectively. The comparison listed below is the only comparison possible, as there were no reads present in the uninfected Hematodinium extractions.

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Gene Expression - C.bairdi MEGAN6 with Trinity and EdgeR

  • 2 min read

After completing annotation of the C.bairdi MEGAN6 taxonomic-specific Trinity assembly using Trinotate on 20200126, I performed differential gene expression analysis and gene ontology (GO) term enrichment analysis using Trinity’s scripts to run EdgeR and GOseq, respectively, across all of the various treatment comparisons. The comparison are listed below and link to each individual SBATCH script (GitHub) used to run these on Mox.

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RNA Isolation and Quantification - C.bairdi Hemocyte Pellets in RNAlater Troubleshooting

  • 1 min read

After the failure to obtain RNA from any C.bairdi hemocytes pellets (out of 24 samples processed) on 20200117, I decided to isolate RNA from just a subset of that group to determine if I screwed something up last time or something. Also, I am testing two different preparations of the kit-supplied DNase I: one Kaitlyn prepped and a fresh preparation that I made. Admittedly, I’m not doing the “proper” testing by trying the different DNase preps on the same exact sample, but it’ll do. I just want to see if I get some RNA from these samples this time…

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2019

Trimming/FastQC/MultiQC - C.bairdi RNAseq FastQ with fastp on Mox

  • 2 min read

Grace/Steven asked me to generate a de novo transcriptome assembly of our current C.bairdi RNAseq data in this GitHub issue. As part of that, I needed to quality trim the data first. Although I could automate this as part of the transcriptome assembly (Trinity has Trimmomatic built-in), I would be unable to view the post-trimming results until after the assembly was completed. So, I opted to do the trimming step separately, to evaluate the data prior to assembly.

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Data Wrangling - Rename Pgenerosa_v074 Files and Scaffolds

  • ~1 min read

Continuing to organizing files for a manuscript dealing with the geoduck genome assembly/annotation we’ve done, we decided to rename the files as well as rename the scaffolds, to make the naming consistent and a bit easier to read (both for humans and computers).

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Data Wrangling - Splitting BAM by Size for Upload to OSF

  • ~1 min read

We’re in the process of organizing files for a manuscript dealing with the geoduck genome assembly/annotation we’ve done. As part of that, we need the Stringtie BAM file that was used with GenSAS for Pgenerosa_v074 annotation to upload to the Open Science Foundation repository for this project. Unfortunately, at 73GB, the file far exceeds the individual file size limit for OSF (5GB). So, I split it into 5GB chunks. See the following notebook for deets:

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Data Wrangling - Panopea generosa Genome Feature Sequence Lengths

  • 1 min read

In preparation for a paper we’re writing, we needed some summary stats on the various genome assembly feature sequences. I determined the max/min, mean, and median sequence lengths for all the GFF feature files we currently have for Pgenerosa_v070, Pgenerosa_v070_top18_scaffolds, and Pgenerosa_v074. This info will be compiled in to a table for the manuscript. See our Genomic Resources wiki for more info on GFFs:

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Genome Comparison - Pgenerosa_v074 vs Pgenerosa_v070 with MUMmer Promer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer 3.23 (specifically, promer for protein level comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs S.glomerata NCBI with MUMmer Promer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer 3.23 (specifically, promer for protein level comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs M.yessoensis NCBI with MUMmer Promer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer 3.23 (specifically, promer for protein level comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs H.sapiens NCBI with MUMmer Promer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer 3.23 (specifically, promer for protein level comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs C.virginica NCBI with MUMmer Promer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer 3.23 (specifically, promer for protein level comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs C.gigas NCBI with MUMmer Promer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer 3.23 (specifically, promer for protein level comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs Pgenerosa_v070 with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs Pgenerosa_v074 with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs S.glomerata NCBI with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs M.yessoensis NCBI with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs H.sapiens NCBI with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs C.gigas NCBI with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Genome Comparison - Pgenerosa_v074 vs C.virginica NCBI with MUMmer on Mox

  • 3 min read

In continuing to further improve our geoduck genome annotation, I’m attempting to figure out why Scaffold 1 of our assembly doesn’t have any annotations. As part of that I’ve decided to perform a series of genome comparisons and see how they match up, with an emphasis on Scaffold 1, using MUMmer (v4) (specifically, nucmer for nucleotide comparisons). This software is specifically designed to do this type of comparison.

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Data Summary - P.generosa Transcriptome Assemblies Stats

  • 1 min read

In our continuing quest to wrangle the geoduck transcriptome assemblies we have, I was tasked with compiling assembly stats for our various assemblies. The table below provides an overview of some stats for each of our assemblies. Links within the table go to the the notebook entries for the various methods from which the data was gathered. In general:

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Genome Annotation - Pgenerosa_v074 Transcript Isoform ID with Stringtie on Mox

  • 4 min read

After annotating Pgenerosa_v070 and comparing feature counts, there was a drastic difference between the two genome versions. Additionally, both of those genomes ended up with no CDS/exon/gene/mRNA features identified in the largest scaffold. So, to explore this further by seeing where (if??) sequencing reads map to the scaffold, and to obtain transcript isoforms for the genome, I ran Stringtie. A Hisat2 index was prepared earlier.

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Genome Annotation - Pgenerosa_v070 Transcript Isoform ID with Stringtie on Mox

  • 3 min read

After annotating Pgenerosa_v074 and comparing feature counts, there was a drastic difference between the two genome versions. Additionally, both of those genomes ended up with no CDS/exon/gene/mRNA features identified in the largest scaffold. So, to explore this further by seeing where (if??) sequencing reads map to the scaffold, and to obtain transcript isoforms for the genome, I ran Stringtie. A Hisat2 index was prepared earlier.

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Genome Annotation - Pgenerosa_v070 and v074 Top 18 Scaffolds Feature Count Comparisons

  • 1 min read

After annotating Pgenerosa_v074 on 20190701, we noticed a large discrepancy in the number of transcripts that MAKER identified, compared to Pgenerosa_v070. As a reminder, the Pgenerosa_v074 is a subset of Pgenerosa_v070 containing only the top 18 longest scaffolds. So, we decided to do a quick comparison of the annotations present in these 18 scaffolds Pgenerosa_v070 and Pgenerosa_v074.

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Genome Annotation - Pgenerosa_v071 Using GenSAS

  • 3 min read

In our various attempts to get the Panopea generosa genome annotated in such a manner that we’re comfortable with (the previous annotation attempts we’re lacking any annotations in almost all of the largest scaffolds, which didn’t seem right), Steven stumbled across GenSAS, a web/GUI-based genome annotation program, so we gave it a shot.

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Genome Annotation - Pgenerosa_v074 Using GenSAS

  • 4 min read

In our various attempts to get the Panopea generosa genome annotated in such a manner that we’re comfortable with (the previous annotation attempts we’re lacking any annotations in almost all of the largest scaffolds, which didn’t seem right), Steven stumbled across GenSAS, a web/GUI-based genome annotation program, so we gave it a shot.

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Genome Annotation - Olurida_v081 with MAKER and Tissue-specific Transcriptomes on Mox

  • 10 min read

I previously annotated our Olurida_v081 genome with MAKER using our “canonical” transcriptome, Olurida_transcriptome_v3.fasta as the EST evidence utilized by MAKER. A discussion on one of our Slack channels related to the lack of isoform annotation (I think it’s a private channel, sorry) prompted Katherine Silliman to suggest re-running the annotation using tissue-specific transcriptome assemblies that she has generated as EST evidence, instead of a singular transcriptome. Since I already had previous versions of the MAKER script that I’ve used for annotations, re-running was rather straightforward. While this was running, I used Stringtie on 20190625to produce a GTF that maps out potential isoforms, as I don’t believe MAKER will actually predict isoforms, since it didn’t do so the first time, nor has it with other annotations we’ve run on geoduck assemblies.

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FastQC-MultiQC - Additional C.gigas WGBS Sequencing Data from Genewiz Received 20190501

  • ~1 min read

Earlier today, we received the additional G.gigas sequencing data from Genewiz. Wanted to run through FastQC again and get an updated report for each data set. Admittedly, it probably won’t look much different from the initial FastQC run on 20190415, due to the fact that the additional sequencing was simply appended to the previous data. Since FastQC examines a subset of the data in each file, I’d fully expect the FastQC report to look the same. However, we’ll have a greater number of sequences in each file. This should, in turn, increase the number of reads retained after quality trimming.

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Data Analysis - C.virginica MBD Sequencing Coverage

  • 2 min read

A while ago, Steven tasked me with assessing some questions related to the sequencing coverage we get doing MBD-BSseq in this GitHub issue. At the heart of it all was really to try to get an idea of how much usable data we actually get when we do an MBD-BSseq project. Yaamini happened to have done an MBD-BSseq project relatively recently, and it’s one she’s actively working on analyzing, so we went with that data set.

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Metagenomics Gene Prediction - P.generosa Water Samples Using MetaGeneMark on Mox to Compare pH Treatments

  • 2 min read

Continuing with a relatively quick comparison of pH treatments (pH=7.1 vs. pH=8.2), I wanted to run gene prediction on the MEGAHIT assemblies I made yesterday. I ran MetaGeneMark on the two pH-specific assemblies on Mox. This should be a very fast process (I’m talking, like a couple of minutes fast), so it enhances the annotation with very little effort and time.

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Metagenome Assemblies - P.generosa Water Samples Trimmed HiSeqX Data Using Megahit on Mox to Compare pH Treatments

  • 2 min read

A report involving our work on the geoduck water metagenomics is due later this week and our in-depth analysis for this project using Anvi’o is likely to require at least another week to complete. Even though we have a broad overview of the metagenomic taxa present in these water samples, we don’t have data in a format for comparing across samples/treatments. So, I initiated our simplified pipeline (MEGAHIT > MetaGeneMark > BLASTn > KronaTools) for examining our metagenomic data of the two treatments:

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RNA Isolation and Quantification - Crab Hemolypmh Using Quick-DNA-RNA Microprep Plus Kit

  • 1 min read

In the continuing struggle to isolate RNA from the Chionoecetes bairdi hemolymph preserved in RNAlater, Pam managed to find the Quick-DNA-RNA Microprep Plus Kit (ZymoResearch) as a potential option. We received a free sample of the kit and so I gave it a shot. Grace pulled 10 samples she’d previously used to isolate RNA (and was unable to get anything out of virtually all of them using the RNeasy Plus Micro Kit (Qiagen)) for me to try out this new kit:

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Transcriptome Assembly - Geoduck Tissue-specific Assembly Larvae Day5 EPI99 with HiSeq and NovaSeq Data on Mox

  • 2 min read

I previously assembled and annotated P.generosa larval Day 5 transcriptome (20190318 - mislabeled as Juvenile Day 5 in my previous notebook entries) using just our HiSeq data from our Illumina collaboration. This was a an oversight, as I didn’t realize that we also had NovaSeq RNAseq data. So, I’ve initiated another de novo assembly using Trinity incorporating both sets of data.

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Data Management - Data Migration and Drive Expansion on Gannet

  • 1 min read

A little while ago, we installed some additional hard drives in Gannet (Synology RS3618XS) with the intention of expanding the total storage space. However, the original set of HDDs were set up as RAID10. As it turns out, RAID10 configurations cannot be expanded! So, the new set of HDDs were configured as a separate volume (Volume 2) in a RAID6 configuration. After backing up the /volume1/web directory (via rsync) to our UW Google Drive, I begane the data migration.

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Genome Assessment - BUSCO Metazoa on P.generosa v071 on Mox

  • 6 min read

Ran BUSCO on our completed annotation of the P.generosa v071 genome (GFF) (subset of sequences >10kbp). See this notebook entry for genome annotation info. This provides a nice metric on how “complete” a genome assembly (or transcriptome) is. Additionally, BUSCO is tied in with Augustus for gene prediction and generates ab initio gene models. With that said, since I just want to evaluate the completeness of this particular genome assembly, I’ll be using the annotated genome generated through two rounds of SNAP gene prediction. Otherwise, I’d use the initial MAKER annotations to generate an Augustus gene model that could be used in conjuction with the SNAP models (I’ll likely do this at a later date).

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Genome Annotation - Pgenerosa_v070 MAKER on Mox

  • 7 min read

Here it goes, a massive undertaking of attempting to annotate the Pgenerosa_v070 genome (FastA; 2.1GB) using MAKER on Mox! I previously started this on 20190115, but killed it in order to fix a number of different issues with the script that were causing problems. I decided the changes were substantial enough, that I’d just make a new working directory and notebook entry.

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Data Wrangling - CpG OE Calculations on C.virginica Genes

  • 2 min read

Steven tasked me with processing ~90 FastA files containing gene sequences from C.virginica in this GitHub Issue. He needed to determine the Observed/Expected (O/E) ratio of CpGs in each FastA. He provided this example code and this link to all the files. Additionally, today, he tasked Kaitlyn with merging all of the output CpG O/E values for each sample in to a single file, but I decided to tackle it anyway.

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Methylation Analysis - C.virginica

  • 4 min read

This is a quick and dirty (i.e. no adaptor/quality trimming) assessment of all of our Crassostrea irginica bisulfite sequencing efforts to date in order to get a rough idea of the methylation mapping, per this GitHub issue. Ran Bismark on Mox on a series of subset of the reads:

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DNA Isolation and Quantification - Ronit’s C.gigas Ploidy Ctenidia

  • ~1 min read

Last week, I isolated DNA from all of Ronti’s ctenidia samples, however one sample (D18-C) didn’t isolate properly. So, I performed another isolation procedure with another section of frozen tissue. Tissue was excised from frozen tissue block via razor blade (weight not recorded) and pulverized under liquid nitrogen. Samples were incubated O/N @ 37oC (heating block) in 350uL of MB1 Buffer + 25uL Proteinase K, per the E.Z.N.A. Mollusc DNA Kit (Omega) instructions.

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Annotation - Olurida_v081 MAKER Proteins InterProScan5 on Mox

  • 1 min read

Continuation of genome annotation of the Olympia oyster genome. Determined initial gene models using MAKER with two rounds of SNAP, relabeled with more user-friendly names, and then performed protein-level annotations using BLASTp. Next, I’m going to run InterProScan5 (IPS5) to help functionally characterize the O.lurida proteins ID’d by MAKER. Once this is complete, I’ll use MAKER to incorporate the IPS5 and BLASTp results into a much more neatly (i.e. human-readable) annotated genome!

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Back to Top ↑

2018

qPCR - Relative mitochondrial abundance in C.gigas diploids and triploids subjected to acute heat stress via COX1

  • 2 min read

Using the C.gigas cytochrome c oxidase (COX1) primers (SR IDs: 1713, 1714)I designed the other day, I ran a qPCR on a subset of Ronit’s diploid/triploid control/heat shocked oyster DNA that Shelly had previously isolated and performed global DNA methylation assay. The goal is to get a rough assessment of whether or not there appear to be differences in relative mitochondrial abundances between these samples.

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FastQC and Trimming - Metagenomics (Geoduck) HiSeqX Reads from 20180809

  • 1 min read

Steven tasked me with assembling our geoduck metagenomics HiSeqX data. The first part of the process is examining the quality of the sequencing reads, performing quality trimming, and then checking the quality of the trimmed reads. It’s also possible (likely) that I’ll need to run another round of trimming. The process is documented in the Jupyter Notebook linked below. After these reads are cleaned up, I’ll transfer them over to our HPC nodes (Mox) and try assembling them.

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Annotation - Olurida_v081 MAKER on Mox

  • 20 min read

Remarkably, I managed to burn through our Xsede computing resources and don’t have terribly much to show for it. Ooof! This is a major bummer, as it “only” takes ~8hrs for a WQ-MAKER job to run there, as opposed to months the last time I tried running it on Mox. Although we have used up our Xsede allocation, all is not lost! The experience of setting up/running WQ-MAKER has enlightened me on how it all works and how to run it on Mox so it will (hopefully) take far, far less time than the last Mox attempt. With that said, here we go…

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Installation - Microsoft Machine Learning Server (Microsoft R Open) on Emu/Roadrunner R Studio Server

  • ~1 min read

Steven recently saw an announcement that Microsoft R Open now handles multi-threaded processing (default R does not), so we were interested in trying it out. I installed MLR/MRO on Emu/Roadrunner (Apple Xserve; Ubuntu 16.04). Followed the Microsoft installation directions for Ubuntu. In retrospect, I think I could’ve just installed MRO, but this gets the job done as well and won’t hurt anything.

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