Correlating the Matrices
56 - Matrix Synergy
Steven Roberts 11 September, 2023
Need for Speed
Can we speed up samtools?
Huddling
updated most recently August 18
methylation distance matrix
Here is an attempt to pull relatedness / distance matrix from methylkit data…
e5 lncRNA comparison
lncRNA Comparison
Steven Roberts 11 August, 2023
CNVs based on ploidy
link to rpub: https://rpubs.com/sr320/1070681
Filtering CT SNPs
removing CT snps from CG methylation data.
Mytilus trossulus Iso-seq Annotation
code: https://github.com/mattgeorgephd/PSMFC-mytilus-byssus-pilot/blob/main/code/06-annotation.Rmd
Mytilus trossulus Iso-seq
Lets take look at Isoseq fasta
Navigating Annotation
The following is a stepwise example or annotation of a gene set using UniProt::Swiss-Prot (reviewed) such that Gene Ontology terms can be associated with each gene.
Where are the SNPs?
Read MoreKallisto v HiSat
In attempting to get quick comparison of alignment across genome, the question arises what is the difference (and accuracy) of kallisto (psuedo-align) and hisat. Spoiler - I was quite surprised with hisat w and w/o gtf. This is A pulcra RNA-seq data….
Evaluating A pulcra alignment rates
Initiating a look on how A pulcra will align to a few good genomes.
February & March Bits
This is a running daily of all the stuff done in February and March. Or just some thoughts.
Reading, Writing and more
In preparation for lab meeting, some answer to Chris’s queries
January Bits
This is a running daily of all the stuff done in January. Or just some thoughts.
January Goals
My January goal is to try to make posting to my notebook easier. I would also like to get a better handle at project management.
November Bits
This is a running daily of all the stuff done in November. Or just some thoughts
Determining exon and intron methylation
An effort to splice out exon and intron methylation levels on a per gene basis.
Finding the predominant
For a the ceabigr data lets ID which isoform is predominant, such that we can find out how treatment and/or methylation might influence this.
September Bits
This is a running daily of all the stuff done in September. Or just some thoughts
Single Cell Library Comparisons
Looking at number of cell, and expression data.
Determining gene methylaiton
Here is some code for getting gene methylation. Will also add to handbook.
Relationship of isoform count and methylation
Some thoughts on the relationship of isoform count and methylation level.
August Bits
This is a running daily of all the stuff done in August. Or just some thoughts
July Bits
This is a running daily of all the stuff done in July.
June Bits
This is a running daily of all the stuff done in June.
Prospective Student Days 2022
Video Recording from Prospective Student Days
Going deep into Bismark
Taking a deeper look at every step. Note this is single-end sequence data.
What's a Weka going to do?
Here I want to examine how Machine Learning might compare with a our conventional gene expression analysis. The data set includes both male and female oysters exposed to OA conditions (and controls). Gonad tissue. Sam ran data through bowtie/stringtie for comparison. Complete sample details are below. PDF of post
Sex-specific OA influence
With limited OA DMLs when considered in totality, looking within each sex to see what any OA influences might be. notebook: https://github.com/epigeneticstoocean/2018_L18-adult-methylation/blob/main/code/03.4-methylkit.Rmd
Stepping back in BS
Digging into Cv DNA methylation data and I was trying to develop bedgraphs of libraries. I noted that in fact I did not have a complete set here. Having also recalled (and seen via .sh files) it took me at least 3 jobs to “complete” the effort that did not complete. So now I question everything. And disappointed that I failed to document the botch of an effort. Well today I am older and wiser and determined not to make a similar mistake. I have decided to cross my fingers and pull deduplicated bams back into mox and run downstream code. This of course presumes my bismark alignment and dedup was done properly.
Taking the oysters to bed
Having previously taken a look at eastern oysters in OA to identify DMLs, here I attempt to take those data, redescribe and generate beds. TLDR: https://github.com/epigeneticstoocean/2018_L18-adult-methylation/tree/main/igv
All the gigas in methylkit
Here want to take all the gigas - previously described and Bismarked - and see what we can glean from methylkit.
Get in Control - Cv multiomics
In an effort to couple DNA methylation data to complementary RNA-seq data we are looking at what the DNA methylation landscape, DML look like. Oysters were exposed to ocean acidification. Males and females were included.
Hemato qPCR in R
02-Crab-qpcr
All gigas at once
What if we start with current data and worked our way back to see if an integration of data was fruitful. Step 1 - bismark it all together..
Getting back to Oly
Visiting the long ago Oly WBGS data. Will start with see if can simply reproduce.
Annotating C gigas genes
After about a year away… here is something.
Getting back into it
Video of Clam sampling: https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8c080c5d-7e85-49f3-846b-ab9b012116db
Sampling Cockles
Video of Clam sampling: https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8c080c5d-7e85-49f3-846b-ab9b012116db
For Duck Sake
Going back to take a peek to see what treating geoduck EPI data as WGBS will look like.
FROGER Day 03
We have some mapping done and will push forward with what we have his AM, which is a 100M subset of Mcap.
FROGER Day 02
Annotating Mcap Proteins
FROGER Day 01
Step 1 is prepping 3 coral genomes
Rebising Oly MBD
Last year :) I ran bismark on Oly samples that Laura is now digging into.
Refreshing the Caligus
Updated: February 05
Looking for the big Duck cat
To have a general description of the geoduck methylation landscape, we take all 51 BS samples, concatenate, and map.
Reproducing whole-Duck analyses, with a few bumps
In preparation for the soon submission of the geoduck genome paper, I re-ran some mox jobs to see if we could reproduce the paper, particular with regard to the new naming scheme. The two scripts were 1217_1300.sh and 1218_1000.sh.
Mapping the spiked lambda phage DNA
First prepared the genome
Point Whitney seed trial
Went out to Pt Whitney with Shelly to semi-wrap up 40 day seed trial where parents experienced different OA regimes.
Geoduck alignments to v74
Taking the trimmed files @ /gscratch/srlab/strigg/data/Pgenr/FASTQS
and aligning to version 74 of the genome.
BS Mapping Oly Cats
Working on the genetics / epigenetics paper, I decided to try to concatenate all reads and align with Bismark in order to get some basic stats.
A simple Oly Gene Track
To get a crude gene track for the Oly genome the big transcriptome was compared to genome.
Comparing Bisulfite Sequencing Approaches
We took DNA from a single Eastern oyster and prepped using MBD, MSP digestion, and plain old DNA. Full details can be found here.
Getting into DNA Methylation
I have to share some information with several new folks, and there are likely old folks that should give this a refresh… thus I am posting it here.
Longest Geoduck Mate-Pair Libraries
In an effort to improve an assembly here is a compilation of MP libraries with longest insert sizes. Specifically this would be an insert size of 8-10kb
OAKL to the Browser
Working in Rmd, here is getting some DMLs into IGV format. TLDR - bedfile
OAKLy Doekly
Full running of the OAKL samples.
Geoduck-EPI on Hi-C Draft
As a better assembly is coming online for the Geoduck, we have started to look at Bismark mapping of prior samples.
Methylkittens
In an attempt to start to visualize differences while waiting on hardware I brought some Bismark alignments into methyKit.
The Bismark Boat
I have been working through Bismark with a few Crassosstrea virginica datasets. This includes the BS data from the 2015 Oil exposure experiment, OA exposure - gonad tissue (OAKL), and a full suite of library preps via Qiagen.
Clc And Virginica
It seems that mapping rates can very a lot. We have a new data set comparing WG-BS, RRBS, and MBDBS. This is valuable as it offers data to run the math on what is most optimal. This first step is mapping. Here I explore CLC results as we are working with Qiagen and this is the software the are using.
Cvirginica Bs Prep Comparison
Here are data corresponding to different types of library preparation.
Oly Bsmapping
I am exploring a few versions of the PBjelly Olympia oyster genome assembly and bisulfite read mapping.
Supernova Output
There are several options for fasta output of Supernova assemblies.
Geoduck 10x Assembly
Supernova completed the 10x Chromium data assembly.
Supernova
About a week ago I started a Supernova 2.0 run to get some of this Chromium 10x data assembled.
Proteomics Chat
We had a nice chat about how to reboot a couple of proteomic projects.
A Little Bowtie
Running some alignments for Charlie.
Geoduck Larvae Filters
As part of this Geoduck Larvae Trial we will be running some filters through proteomics and metagenomics.
Moving Duck Files
Getting back to the command line.
Alanine Retired
Replacing toaster drive.
Test
Oly Assembly Mapping
We have the following several Oly draft assemblies. Available here
Quast Oly
Running QUAST to compare genome assembly.
Illumina Summary
Here is a Summary of the Illumina NS++ data dump (by platform).
Summer 2017 Ph And Temp
Some summary environmental data for DNR project
Oly Pacbio Files
Exploring the different aspects of data generated for the Oly genome.
Srm Technical Reps
Per this issue I took at look at some of Yaamini’s data.
Oly Genome Comparison
Sam has compiled the current status of Olympia oyster genome assemblies here. I am going to try to assess differences.
Geoduck Miseq
We have a few MiSeq files.
Mox Fastqc And Minia
Playing around a bit with Mox (crippled by lack of disk space). Ran FastQC
Geoduck Novaseq Files
Here is a summary of the new data dump.
Geoduck Hiseq Data
While we received a lot of files in HiSeq folder, none were fastq, thus Sam downloaded from BaseSpace. And it is ugly.
Pgen Larval Proteome
Using the Trandsdecoder and the Trinity assembly, a deduced proteome was generated.
Geoduck Larval Proteome
Deduced protein sequences for 0804_Pgen_larvae.fasta
Mox With Purpose
Having spent a day in Hyak, I think I know have a workflow that makes sense.
Geoduck Larval Transcriptome
In preparation for new proteomic analysis here is a transcriptome from the NovaSeq.
Trinity Moxy
Running Trinity on Mox. Geoduck larvae.
Trinity Emu
Running Trinity on EMU
Proteomic Chat
Topic: Proteomic talk w/ Emma Date : Aug 3, 2017 10:53 AM Pacific Time (US and Canada)
Geoduck Rna
Exploring RNA-Seq data from Illumina effort
Sqlshare Join
Here is a set of videos where I
1) download annotations from UniProt
2) upload said file to the new SQLShare
3) upload Blastx output to SQLShare and…
4) do a left join.
Proteomic Visualization
Here is how one might go about visualizing Proteomic Data. This is based on a list of proteins Laura found to be different in geoducks in eel grass (as opposed to not being in eel grass).
Geoduck Eelgrass Proteins
comp138254
comp142216
comp125530
comp48421
comp144401
comp135856
comp143411
comp122035
comp134625
comp144270
comp142142
comp143197
comp143411
comp142396
comp88705
comp144180
comp131660
comp128586
comp28288
comp144604
comp141473
comp139766
comp116351
comp129221
comp22527
comp134200
comp136492
comp133552
comp144504
comp141096
comp99434
comp142358
comp143236
comp124813
comp144421
comp131211
comp143770
comp144132
comp127542
comp133562
comp142424
comp142890
comp135129
comp134692
comp144262
comp143418
comp133063
comp144191
comp90334
comp139531
comp142589
comp137055
comp143502
comp131651
comp141946
comp139881
comp143082
comp130569
comp143835
comp153529
comp128923
comp114823
comp143766
comp142589
comp135181
comp137628
comp140039
comp144637
comp137991
comp123956
comp128513
comp144581
comp135366
comp141512
Video Snippet
Coge Synteny
Exploring various options for comparative genomic in CoGe
Abacus fail
Yesterday Emma was concerned about Rhonda’s Abacus file. If fact there were differences. I created a new Abacus parameter file
Going through DDA
In an attempt to go from mzXML to Abacus, I took Rhonda’s mzXML files on Emu, copied them to my directory and rand the following
Geoduck 10 Day DMR annotations
Here is an attempt to annotate about half of the 41 DMRs Sean has identified.
Geoduck RRBS- Locating 41
Sean has identified 41 loci that are different in the 3 treatments at Day 10!
Geoduck RRBS - Batch 01 Methylation Calls
Having run the first batch of geoduck RRBS throught CoGe - Here is the mCpG file and information of how these files were generated.
Geoduck RRBS Library - First Look
Fifty RRBS Libraries were constructed by Hollie and sequenced (Maybe? these numbers do not match nightingales).
Two Treatment Temperature Trial
I went out to Manchester yesterday and checked on the TripleT (Two Treatment Trial) project.
Bioinformatics Class Projects
Another quarter is complete for our Bioinformatics class , and once again we learned a bit.
Annotating Geoduck Genome
find-xargs-basename
!find /Volumes/web/nightingales/O_lurida/20160223_gbs/1NF*1.fq.gz | xargs basename -s _1.fq.gz \
| xargs -I{} /Applications/bioinfo/bowtie2-2.2.4/bowtie2 \
-x /Users/sr320/git-repos/student-fish546-2016/data/Ostrea_lurida-Scaff-10k-bowtie-index \
-1 /Volumes/web/nightingales/O_lurida/20160223_gbs/{}_1.fq.gz \
-2 /Volumes/web/nightingales/O_lurida/20160223_gbs/{}_2.fq.gz \
-p 8 \
--very-sensitive-local \
-S /Volumes/caviar/wd/2016-12-01/{}.sam
Mapping GBS
Installing GNU Coreutils
``` D-128-95-149-192:~ sr320$ brew install coreutils Updating Homebrew… ==> Auto-updated Homebrew! Updated 1 tap (homebrew/core). ==> Updated Formulae mercurial
SAM lacked header
Checking Bismark BAM
Why BSMAP limits scallfolds
Oly 2bRad Bowtie Mapping
Mapped RNA-seq reads yesterday. Today trying 2bRAD that matches BS data.
Running Repeatmasker on Greenbird
Kallisto on Oly Genome
Bowtie for Oly Genome Expression
!/Applications/bioinfo/bowtie2-2.2.4/bowtie2 \
-x ../data/Ostrea_lurida-Scaff-10k-bowtie-index \
-1 /Volumes/web/nightingales/O_lurida/filtered_106A_Male_Mix_TAGCTT_L004_R1.fastq.gz \
-2 /Volumes/web/nightingales/O_lurida/filtered_106A_Male_Mix_TAGCTT_L004_R2.fastq.gz \
-p 6 \
--very-fast \
-S /Volumes/caviar/wd/2016-11-11/bw-106A_Male_Mix_TAGCTT_L004.sam
!samtools view -bS /Volumes/caviar/wd/2016-11-11/bw-106A_Male_Mix_TAGCTT_L004.sam \
| samtools sort -o /Volumes/caviar/wd/2016-11-11/bw-106A_Male_Mix_TAGCTT_L004.bam
!samtools index /Volumes/caviar/wd/2016-11-11/bw-106A_Male_Mix_TAGCTT_L004.bam
Oly 10k Gene Annotation
Gigaton Protein Annotation Complete
Ran Blastp against UniProt.
Fidalgo Sibs on 10k Genome
Running BSMAP on version of Ostrea lurida genome that is limited by 10k minimum scaffold threshold.
Ssalar Protein Annotation Complete
With a third blasting and comparing hits for all 10 parts of the query, I am satisfied with the output.
Mystery blast fails
On genefish. Will try splitting.
Problem with Ssalar blastp
Geoduck Big Table
Working on the finalizing the big table for the the transcriptome.
Big Table Nb
Link to notebook exploring the table https://github.com/sr320/paper-pano-go/blob/master/jupyter-nbs/11-Exploring-the-Big-Table.ipynb
One more time
Fidalgo 8 Oly Oyster BS
Analysis of eight Fidalgo Olympia oysters. Maybe I just need a second sentence.
ls analyses/2016-10-11
mkfmt_M2.txt mkfmt_M3.txt
ls -lh /Volumes/caviar/wd/2016-10-11/bsmap*sam
-rw-r--r-- 1 sr320 staff 208M Oct 15 02:52 /Volumes/caviar/wd/2016-10-11/bsmap_out_1_ATCACG.sam
-rw-r--r-- 1 sr320 staff 254M Oct 16 04:21 /Volumes/caviar/wd/2016-10-11/bsmap_out_2_CGATGT.sam
-rw-r--r-- 1 sr320 staff 253M Oct 17 05:33 /Volumes/caviar/wd/2016-10-11/bsmap_out_3_TTAGGC.sam
-rw-r--r-- 1 sr320 staff 253M Oct 18 08:19 /Volumes/caviar/wd/2016-10-11/bsmap_out_4_TGACCA.sam
-rw-r--r-- 1 sr320 staff 264M Oct 20 15:50 /Volumes/caviar/wd/2016-10-11/bsmap_out_5_ACAGTG.sam
-rw-rw-rw- 1 sr320 staff 263M Oct 22 02:37 /Volumes/caviar/wd/2016-10-11/bsmap_out_6_GCCAAT.sam
-rw-rw-rw- 1 sr320 staff 225M Oct 20 18:49 /Volumes/caviar/wd/2016-10-11/bsmap_out_7_CAGATC.sam
-rw-rw-rw- 1 sr320 staff 299M Oct 19 18:55 /Volumes/caviar/wd/2016-10-11/bsmap_out_8_ACTTGA.sam
-rw-r--r-- 1 sr320 staff 1.5G Oct 11 08:06 /Volumes/caviar/wd/2016-10-11/bsmap_out_M2.sam
-rw-r--r-- 1 sr320 staff 1.6G Oct 11 08:10 /Volumes/caviar/wd/2016-10-11/bsmap_out_M3.sam
bsmaploc="/Applications/bioinfo/BSMAP/bsmap-2.74/"
cd /Volumes/caviar/wd/2016-10-11/
/Volumes/caviar/wd/2016-10-11
for i in ("1_ATCACG","2_CGATGT","3_TTAGGC","4_TGACCA","5_ACAGTG","6_GCCAAT","7_CAGATC","8_ACTTGA"):
!python {bsmaploc}methratio.py \
-d ../data/Ostrea_lurida.scafSeq \
-u -z -g \
-o methratio_out_{i}.txt \
-s {bsmaploc}samtools \
bsmap_out_{i}.sam \
@ Sat Oct 22 09:46:37 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 09:47:26 2016: reading bsmap_out_1_ATCACG.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 09:47:53 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 09:49:11 2016: writing methratio_out_1_ATCACG.txt ...
@ Sat Oct 22 09:54:10 2016: done.
total 467574 valid mappings, 618824 covered cytosines, average coverage: 2.02 fold.
@ Sat Oct 22 09:54:15 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 09:55:04 2016: reading bsmap_out_2_CGATGT.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 09:55:37 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 09:56:55 2016: writing methratio_out_2_CGATGT.txt ...
@ Sat Oct 22 10:01:55 2016: done.
total 579365 valid mappings, 689492 covered cytosines, average coverage: 2.19 fold.
@ Sat Oct 22 10:02:00 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 10:02:49 2016: reading bsmap_out_3_TTAGGC.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 10:03:21 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 10:04:39 2016: writing methratio_out_3_TTAGGC.txt ...
@ Sat Oct 22 10:09:37 2016: done.
total 579579 valid mappings, 678634 covered cytosines, average coverage: 2.24 fold.
@ Sat Oct 22 10:09:42 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 10:10:31 2016: reading bsmap_out_4_TGACCA.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 10:11:04 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 10:12:21 2016: writing methratio_out_4_TGACCA.txt ...
@ Sat Oct 22 10:17:20 2016: done.
total 577435 valid mappings, 690889 covered cytosines, average coverage: 2.18 fold.
@ Sat Oct 22 10:17:25 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 10:18:14 2016: reading bsmap_out_5_ACAGTG.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 10:18:47 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 10:20:04 2016: writing methratio_out_5_ACAGTG.txt ...
@ Sat Oct 22 10:25:04 2016: done.
total 608092 valid mappings, 691864 covered cytosines, average coverage: 2.27 fold.
@ Sat Oct 22 10:25:09 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 10:25:58 2016: reading bsmap_out_6_GCCAAT.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 10:26:32 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 10:27:51 2016: writing methratio_out_6_GCCAAT.txt ...
@ Sat Oct 22 10:32:57 2016: done.
total 604365 valid mappings, 689831 covered cytosines, average coverage: 2.27 fold.
@ Sat Oct 22 10:33:02 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 10:33:51 2016: reading bsmap_out_7_CAGATC.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 10:34:20 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 10:35:33 2016: writing methratio_out_7_CAGATC.txt ...
@ Sat Oct 22 10:40:32 2016: done.
total 507109 valid mappings, 646374 covered cytosines, average coverage: 2.09 fold.
@ Sat Oct 22 10:40:38 2016: reading reference ../data/Ostrea_lurida.scafSeq ...
@ Sat Oct 22 10:41:27 2016: reading bsmap_out_8_ACTTGA.sam ...
[samopen] SAM header is present: 765755 sequences.
@ Sat Oct 22 10:42:05 2016: combining CpG methylation from both strands ...
@ Sat Oct 22 10:43:22 2016: writing methratio_out_8_ACTTGA.txt ...
@ Sat Oct 22 10:48:21 2016: done.
total 689625 valid mappings, 732123 covered cytosines, average coverage: 2.42 fold.
#first methratio files are converted to filter for CG context, 3x coverage (mr3x.awk), and reformatting (mr_gg.awk.sh).
#due to issue passing variable to awk, simple scripts were used (included in repository)
for i in ("1_ATCACG","2_CGATGT","3_TTAGGC","4_TGACCA","5_ACAGTG","6_GCCAAT","7_CAGATC","8_ACTTGA"):
!echo {i}
!grep "[A-Z][A-Z]CG[A-Z]" <methratio_out_{i}.txt> methratio_out_{i}CG.txt
!awk -f /Users/sr320/git-repos/sr320.github.io/jupyter/scripts/mr3x.awk methratio_out_{i}CG.txt \
> mr3x.{i}.txt
!awk -f /Users/sr320/git-repos/sr320.github.io/jupyter/scripts/mr_gg.awk.sh \
mr3x.{i}.txt > mkfmt_{i}.txt
1_ATCACG
2_CGATGT
3_TTAGGC
4_TGACCA
5_ACAGTG
6_GCCAAT
7_CAGATC
8_ACTTGA
#maybe we need to ignore case
!md5 mkfmt_M2.txt mkfmti_M2.txt | head
MD5 (mkfmt_M2.txt) = df67fde9e87ec165618d384374074057
MD5 (mkfmti_M2.txt) = df67fde9e87ec165618d384374074057
#nope
!head -5 mkfmt*
==> mkfmt_1_ATCACG.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 3 0.00 100.00
scaffold1.143 scaffold1 143 F 4 0.00 100.00
scaffold1.244 scaffold1 244 F 3 66.67 33.33
scaffold1.265 scaffold1 265 F 7 14.29 85.71
==> mkfmt_2_CGATGT.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 11 0.00 100.00
scaffold1.143 scaffold1 143 F 9 0.00 100.00
scaffold1.566 scaffold1 566 F 8 0.00 100.00
scaffold1.572 scaffold1 572 F 3 0.00 100.00
==> mkfmt_3_TTAGGC.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.12 scaffold1 12 F 4 25.00 75.00
scaffold1.33 scaffold1 33 F 3 0.00 100.00
scaffold1.109 scaffold1 109 F 5 0.00 100.00
scaffold1.143 scaffold1 143 F 9 0.00 100.00
==> mkfmt_4_TGACCA.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.109 scaffold1 109 F 9 11.11 88.89
scaffold1.143 scaffold1 143 F 11 9.09 90.91
scaffold1.244 scaffold1 244 F 3 0.00 100.00
scaffold1.265 scaffold1 265 F 4 25.00 75.00
==> mkfmt_5_ACAGTG.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 8 0.00 100.00
scaffold1.109 scaffold1 109 F 5 0.00 100.00
scaffold1.143 scaffold1 143 F 5 0.00 100.00
scaffold1.244 scaffold1 244 F 6 33.33 66.67
==> mkfmt_6_GCCAAT.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.12 scaffold1 12 F 3 0.00 100.00
scaffold1.33 scaffold1 33 F 11 9.09 90.91
scaffold1.109 scaffold1 109 F 7 0.00 100.00
scaffold1.143 scaffold1 143 F 11 0.00 100.00
==> mkfmt_7_CAGATC.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 10 0.00 100.00
scaffold1.109 scaffold1 109 F 6 0.00 100.00
scaffold1.143 scaffold1 143 F 16 0.00 100.00
scaffold1.244 scaffold1 244 F 3 0.00 100.00
==> mkfmt_8_ACTTGA.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 7 0.00 100.00
scaffold1.109 scaffold1 109 F 4 0.00 100.00
scaffold1.143 scaffold1 143 F 10 10.00 90.00
scaffold1.244 scaffold1 244 F 6 0.00 100.00
==> mkfmt_M2.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.14274 scaffold1 14274 F 4 0.00 100.00
scaffold1.14305 scaffold1 14305 F 4 0.00 100.00
scaffold1.15309 scaffold1 15309 F 4 0.00 100.00
scaffold1.15315 scaffold1 15315 F 4 0.00 100.00
==> mkfmt_M3.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.259 scaffold1 259 F 4 100.00 0.00
scaffold1.263 scaffold1 263 F 4 100.00 0.00
scaffold1.267 scaffold1 267 F 4 100.00 0.00
scaffold1.271 scaffold1 271 F 4 100.00 0.00
==> mkfmti_M2.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.14274 scaffold1 14274 F 4 0.00 100.00
scaffold1.14305 scaffold1 14305 F 4 0.00 100.00
scaffold1.15309 scaffold1 15309 F 4 0.00 100.00
scaffold1.15315 scaffold1 15315 F 4 0.00 100.00
==> mkfmti_M3.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.259 scaffold1 259 F 4 100.00 0.00
scaffold1.263 scaffold1 263 F 4 100.00 0.00
scaffold1.267 scaffold1 267 F 4 100.00 0.00
scaffold1.271 scaffold1 271 F 4 100.00 0.00
Products
cd git-repos/sr320.github.io/jupyter/
/Users/sr320/git-repos/sr320.github.io/jupyter
ls
[34mCgigas[m[m/ [34mOlurida[m[m/ [34manalyses[m[m/ [34mscripts[m[m/
mkdir analyses/$(date +%F)
for i in ("1_ATCACG","2_CGATGT","3_TTAGGC","4_TGACCA","5_ACAGTG","6_GCCAAT","7_CAGATC","8_ACTTGA"):
!cp /Volumes/caviar/wd/2016-10-11/mkfmt_{i}.txt analyses/$(date +%F)/mkfmt_{i}.txt
!head analyses/$(date +%F)/*
==> analyses/2016-10-22/mkfmt_1_ATCACG.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 3 0.00 100.00
scaffold1.143 scaffold1 143 F 4 0.00 100.00
scaffold1.244 scaffold1 244 F 3 66.67 33.33
scaffold1.265 scaffold1 265 F 7 14.29 85.71
scaffold1.579 scaffold1 579 F 4 0.00 100.00
scaffold1.591 scaffold1 591 F 4 0.00 100.00
scaffold1.622 scaffold1 622 F 4 0.00 100.00
scaffold1.641 scaffold1 641 F 3 66.67 33.33
scaffold1.723 scaffold1 723 F 3 0.00 100.00
==> analyses/2016-10-22/mkfmt_2_CGATGT.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 11 0.00 100.00
scaffold1.143 scaffold1 143 F 9 0.00 100.00
scaffold1.566 scaffold1 566 F 8 0.00 100.00
scaffold1.572 scaffold1 572 F 3 0.00 100.00
scaffold1.576 scaffold1 576 F 9 0.00 100.00
scaffold1.579 scaffold1 579 F 8 0.00 100.00
scaffold1.582 scaffold1 582 F 6 83.33 16.67
scaffold1.591 scaffold1 591 F 6 0.00 100.00
scaffold1.602 scaffold1 602 F 5 0.00 100.00
==> analyses/2016-10-22/mkfmt_3_TTAGGC.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.12 scaffold1 12 F 4 25.00 75.00
scaffold1.33 scaffold1 33 F 3 0.00 100.00
scaffold1.109 scaffold1 109 F 5 0.00 100.00
scaffold1.143 scaffold1 143 F 9 0.00 100.00
scaffold1.244 scaffold1 244 F 4 0.00 100.00
scaffold1.265 scaffold1 265 F 11 0.00 100.00
scaffold1.566 scaffold1 566 F 5 0.00 100.00
scaffold1.576 scaffold1 576 F 5 0.00 100.00
scaffold1.579 scaffold1 579 F 6 0.00 100.00
==> analyses/2016-10-22/mkfmt_4_TGACCA.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.109 scaffold1 109 F 9 11.11 88.89
scaffold1.143 scaffold1 143 F 11 9.09 90.91
scaffold1.244 scaffold1 244 F 3 0.00 100.00
scaffold1.265 scaffold1 265 F 4 25.00 75.00
scaffold1.566 scaffold1 566 F 4 0.00 100.00
scaffold1.572 scaffold1 572 F 3 0.00 100.00
scaffold1.576 scaffold1 576 F 7 0.00 100.00
scaffold1.579 scaffold1 579 F 5 0.00 100.00
scaffold1.582 scaffold1 582 F 4 50.00 50.00
==> analyses/2016-10-22/mkfmt_5_ACAGTG.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 8 0.00 100.00
scaffold1.109 scaffold1 109 F 5 0.00 100.00
scaffold1.143 scaffold1 143 F 5 0.00 100.00
scaffold1.244 scaffold1 244 F 6 33.33 66.67
scaffold1.265 scaffold1 265 F 6 0.00 100.00
scaffold1.566 scaffold1 566 F 3 0.00 100.00
scaffold1.572 scaffold1 572 F 3 0.00 100.00
scaffold1.576 scaffold1 576 F 4 0.00 100.00
scaffold1.579 scaffold1 579 F 5 0.00 100.00
==> analyses/2016-10-22/mkfmt_6_GCCAAT.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.12 scaffold1 12 F 3 0.00 100.00
scaffold1.33 scaffold1 33 F 11 9.09 90.91
scaffold1.109 scaffold1 109 F 7 0.00 100.00
scaffold1.143 scaffold1 143 F 11 0.00 100.00
scaffold1.244 scaffold1 244 F 9 11.11 88.89
scaffold1.265 scaffold1 265 F 11 0.00 100.00
scaffold1.566 scaffold1 566 F 10 0.00 100.00
scaffold1.572 scaffold1 572 F 4 0.00 100.00
scaffold1.576 scaffold1 576 F 11 0.00 100.00
==> analyses/2016-10-22/mkfmt_7_CAGATC.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 10 0.00 100.00
scaffold1.109 scaffold1 109 F 6 0.00 100.00
scaffold1.143 scaffold1 143 F 16 0.00 100.00
scaffold1.244 scaffold1 244 F 3 0.00 100.00
scaffold1.265 scaffold1 265 F 9 0.00 100.00
scaffold1.566 scaffold1 566 F 6 0.00 100.00
scaffold1.576 scaffold1 576 F 5 0.00 100.00
scaffold1.579 scaffold1 579 F 6 16.67 83.33
scaffold1.582 scaffold1 582 F 5 80.00 20.00
==> analyses/2016-10-22/mkfmt_8_ACTTGA.txt <==
chr.Base chr base strand coverage freqC freqT
scaffold1.33 scaffold1 33 F 7 0.00 100.00
scaffold1.109 scaffold1 109 F 4 0.00 100.00
scaffold1.143 scaffold1 143 F 10 10.00 90.00
scaffold1.244 scaffold1 244 F 6 0.00 100.00
scaffold1.265 scaffold1 265 F 7 14.29 85.71
scaffold1.566 scaffold1 566 F 7 0.00 100.00
scaffold1.576 scaffold1 576 F 6 0.00 100.00
scaffold1.579 scaffold1 579 F 7 14.29 85.71
scaffold1.582 scaffold1 582 F 7 42.86 57.14
url for 8 tables..
https://github.com/sr320/sr320.github.io/tree/master/jupyter/analyses/2016-10-22
Where are the lncRNAs?
Last year Cris sent me some Atlantic salmon lncRNAs (~21k) where he wanted to know what the adjacent gene ID.
Olympia Oyster Genome Read Check
Reposted from the FISH546 Project
Analysis of two oyster samples
I started analysis of two gigas samples to eventually be compared with methylRAD. Below is a snapshot of the Jupyter notebook.
Updating @ https://github.com/sr320/sr320.github.io/blob/master/jupyter/Cgigas/Lotterhos%20BS%20samples.ipynb
The M2 and M3 samples are here:
http://owl.fish.washington.edu/nightingales/C_gigas/9_GATCAG_L001_R1_001.fastq.gz http://owl.fish.washington.edu/nightingales/C_gigas/10_TAGCTT_L001_R1_001.fastq.gz
bsmaploc="/Applications/bioinfo/BSMAP/bsmap-2.74/"
Genome version
!curl \
ftp://ftp.ensemblgenomes.org/pub/release-32/metazoa/fasta/crassostrea_gigas/dna/Crassostrea_gigas.GCA_000297895.1.dna_sm.toplevel.fa.gz \
> /Volumes/caviar/wd/data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa.gz
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 148M 100 148M 0 0 5192k 0 0:00:29 0:00:29 --:--:-- 5790k
!curl ftp://ftp.ensemblgenomes.org/pub/release-32/metazoa/fasta/crassostrea_gigas/dna/CHECKSUMS
08778 148199 Crassostrea_gigas.GCA_000297895.1.dna.nonchromosomal.fa.gz
08778 148199 Crassostrea_gigas.GCA_000297895.1.dna.toplevel.fa.gz
57175 143732 Crassostrea_gigas.GCA_000297895.1.dna_rm.nonchromosomal.fa.gz
57175 143732 Crassostrea_gigas.GCA_000297895.1.dna_rm.toplevel.fa.gz
45604 151782 Crassostrea_gigas.GCA_000297895.1.dna_sm.nonchromosomal.fa.gz
45604 151782 Crassostrea_gigas.GCA_000297895.1.dna_sm.toplevel.fa.gz
62118 5 README
!ls /Volumes/caviar/wd/data/
Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa.gz
!md5 /Volumes/caviar/wd/data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa.gz
MD5 (/Volumes/caviar/wd/data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa.gz) = c70084d76bd6d7a1ba52c13843e69ccc
cd /Volumes/caviar/wd/
/Volumes/caviar/wd
mkdir $(date +%F)
ls
[34m2016-10-11[m[m/ [34mdata[m[m/
ls /Volumes/web/nightingales/C
!curl \
http://owl.fish.washington.edu/nightingales/C_gigas/9_GATCAG_L001_R1_001.fastq.gz \
> /Volumes/caviar/wd/2016-10-11/9_GATCAG_L001_R1_001.fastq.gz
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 560M 100 560M 0 0 55.6M 0 0:00:10 0:00:10 --:--:-- 77.8M
!curl \
http://owl.fish.washington.edu/nightingales/C_gigas/10_TAGCTT_L001_R1_001.fastq.gz \
> /Volumes/caviar/wd/2016-10-11/10_TAGCTT_L001_R1_001.fastq.gz
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 619M 100 619M 0 0 46.1M 0 0:00:13 0:00:13 --:--:-- 44.0M
cd 2016-10-11/
/Volumes/caviar/wd/2016-10-11
!cp 9_GATCAG_L001_R1_001.fastq.gz M2.fastq.gz
!cp 10_TAGCTT_L001_R1_001.fastq.gz M3.fastq.gz
for i in ("M2","M3"):
!{bsmaploc}bsmap \
-a {i}.fastq.gz \
-d ../data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa \
-o bsmap_out_{i}.sam \
-p 6
BSMAP v2.74
Start at: Tue Oct 11 08:02:27 2016
Input reference file: ../data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa (format: FASTA)
Load in 7658 db seqs, total size 557717710 bp. 8 secs passed
total_kmers: 43046721
Create seed table. 24 secs passed
max number of mismatches: read_length * 8% max gap size: 0
kmer cut-off ratio: 5e-07
max multi-hits: 100 max Ns: 5 seed size: 16 index interval: 4
quality cutoff: 0 base quality char: '!'
min fragment size:28 max fragemt size:500
start from read #1 end at read #4294967295
additional alignment: T in reads => C in reference
mapping strand: ++,-+
Single-end alignment(6 threads)
Input read file: M2.fastq.gz (format: gzipped FASTQ)
Output file: bsmap_out_M2.sam (format: SAM)
Thread #1: 100000 reads finished. 30 secs passed
Thread #0: 50000 reads finished. 30 secs passed
Thread #2: 150000 reads finished. 31 secs passed
Thread #3: 200000 reads finished. 31 secs passed
Thread #5: 250000 reads finished. 31 secs passed
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Thread #0: 3000000 reads finished. 88 secs passed
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Thread #5: 8350000 reads finished. 199 secs passed
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Thread #2: 10300000 reads finished. 241 secs passed
Thread #4: 10350000 reads finished. 241 secs passed
Thread #5: 10400000 reads finished. 241 secs passed
Thread #3: 10450000 reads finished. 241 secs passed
Thread #2: 10564512 reads finished. 242 secs passed
for i in ("M2","M3"):
!python {bsmaploc}methratio.py \
-d ../data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa \
-u -z -g \
-o methratio_out_{i}.txt \
-s {bsmaploc}samtools \
bsmap_out_{i}.sam \
Oly OA 48hr Sampling Event
We sampled 96 oysters that were part of Katherine Silliman’s summer project. These oysters were from three locales and had spent about 48 hours in OA treatment (half in contol water). Full sensor data is available here.
Geoduck data table
Getting closer to a master table for a the gonad transcriptome.
Geoduck Gonad Gene Annotations
After kicking around how to make a very big table with all of the annotations… I finally made some progress.
SRA and Cyverse
Curious to see how Jay might tackle genome assembly (and looking ahead to FISH546) I wanted to see what could be done. I was able to bring an SRA file directly into Cyverse
Blast2GO
Frustrated with roll you own option in with EBI GO association files etc. I am trialing Blast2GO commandline. It was not much better getting going but it is downloading stuff now.
CoGe on Fidalgo Sibs
As per this pipeline I will run the 8 individuals in the environmental epigenetics mini-experiment.