Notes for Lauren Download Illumina RNAseq data conda create -yn sra source activate sra conda install -yc bioconda sra-tools mkdir $HOME/data

rm -fr SRR11037797 rm *fastq tmux new -s project $HOME/Oyster_River_Protocol/oyster.mk \ TPM_FILT=1 \ MEM=50 \ CPU=24 \ SPADES2_KMER=31 \

# P. californicus transcriptome assembly and Annotation ``` 22065| # 20904| # 19743| # 18582| # 17421| # 16260| # 15099| # 13938| # 12777| # 11616| # 10454| # 9293| # 8132| # 6971| # 5810| # 4649| # 3488| # 2327| # 1166| # 5| ############### --------------- -------------------------------- | Summary | -------------------------------- | observations: 27059 | | min value: -1.000000 | | mean : -0.887839 | |

# ELAEVO Students!! Help me find my mistake I just got back from the field, I made a terrible mistake. I had a very valuable RNA sample that I had accidentally left out in the sun for 3 days. I'm sure it is ruined.. :( My lab technician made an even worse mistake. While preparing the sample for sequencing, he might have mis-labeled the samples and now I don't know which is the good sample and which is the bad sample. Can you help me figure out which is the good sample and which is the bad sa

# Transcriptome Assembly Practical RON ELAEVO 2019 #### The following details the steps involved in: - Generating a _de novo_ RNA-Seq assembly using the Oyster River Protocol - Evaluating the quality of the assembly - BUSCO and TransRate - Quantifying transcript expression levels - Using Salmon - Functionally annotating transcripts (won't get here, but see code) - dammit - Predicting coding regions (won't get here, but see code) - TransDecoder #### Oyster River Protocol One of the ni

# Transcriptome Assembly Practical DOCKER ELAEVO 2019 #### The following details the steps involved in: - Generating a _de novo_ RNA-Seq assembly using the Oyster River Protocol - Evaluating the quality of the assembly - BUSCO and TransRate - Quantifying transcript expression levels - Using Salmon - Functionally annotating transcripts (won't get here, but see code) - dammit - Predicting coding regions (won't get here, but see code) - TransDecoder #### Oyster River Protocol One of th

# Connecting to Ron Server 1. If you are on Windows, download Putty: https://the.earth.li/~sgtatham/putty/latest/w64/putty.exe 2. Double click the executable. A window will pop up:  3. En la foto notas el espacio q dice "example.com". You are going to type `ron.sr.unh.edu`, y click open.  Click "Yes" 4. Once the SSH Connection is open, you should see a terminal prompt asking for your username: ``` login as: Connec

# Windows 10 Pro, Linux, Mac users Docker is a nice tool, and should be installable by Win10 Pro, Linux, and Mac Users. Follow the below instructions. At the end of each, procedure you can verify your installation by typing `docker run hello-world` Ubuntu Users: https://docs.docker.com/install/linux/docker-ce/ubuntu/ Windows 10 Pro users: https://docs.docker.com/docker-for-windows/install/ Mac Users: https://docs.docker.com/docker-for-mac/

# Consensin genes ``` >sp|Q15021|CND1_HUMAN Condensin complex subunit 1 OS=Homo sapiens OX=9606 GN=NCAPD2 PE=1 SV=3 >sp|Q15003|CND2_HUMAN Condensin complex subunit 2 OS=Homo sapiens OX=9606 GN=NCAPH PE=1 SV=3 >sp|Q3SZL8|CNDH2_BOVIN Condensin-2 complex subunit H2 OS=Bos taurus OX=9913 GN=NCAPH2 PE=2 SV=1 >sp|Q86XI2|CNDG2_HUMAN Condensin-2 complex subunit G2 OS=Homo sapiens OX=9606 GN=NCAPG2 PE=1 SV=1 >sp|Q6DFV1|CNDG2_MOUSE Condensin-2 complex subunit G2 OS=Mus musculus OX=10090 GN=Ncapg2 PE=1 SV

make_ranges for Pilon == ``` source $HOME/Oyster_River_Protocol/software/anaconda/install/bin/activate 3d-dna python $HOME/nanopolish/scripts/nanopolish_makerange.py \ --segment-length 1000000 \ --overlap-length -1 $HOME/pero_genome/Peer1.7.1.fasta \ | tee -a Peer171.ranges sed -i 's_:0-_:1-_g' Peer171.ranges ``` ### make lists ``` grep ">" $HOME/pero_genome/Peer1.7.1.fasta | sed 's_>__' | tee -a chr.list cat chr.list | shuf | split -d -l 1 - genomechunk. rename genomechunk.0 genomechunk. ge

# DNAZoo Annotation Project Having genomes is good - chromosome level genomes are better... But it's the annotation of those genomes that is really enabling. Knowing something about the full complement of genes, and their order on chromosomes, is exeptionally powerful, and allows direct comparisons of genomes across the tree of life. To begin to understand this, we set out to create a set of annotations for all the mammals of the DNAZoo. tl;dr, the entire set, from 67 genomes, can be found he

Jocie GATK Array Work == ``` ### make 100kb windows for genome python $HOME/nanopolish/scripts/nanopolish_makerange.py \ --segment-length 100000 \ --overlap-length -1 $HOME/pero_genome/Peer1.7.2.fasta \ | tee -a Peer172.ranges ### format properly for GATK (tab sep file) sed -i 's_:_\t_g' /mnt/lustre/macmaneslab/macmanes/Peer172.ranges sed -i 's+-+\t+g' /mnt/lustre/macmaneslab/macmanes/Peer172.ranges split -l 1 ../Peer172.ranges -d 0 --additional-suffix=".bed" -a 5 & ### get rid of leading z