This page will be edited to regroup a list of links to useful bioinformatics tutorials Sam file format - link Transcriptomics General concepts - Link // Good place to start Mapping - Link Alignment QC - Link Counting reads - Link

Quick code to run some correlations on a sample table library(tidyverse) library(readxl) df<-read_xlsx("table.xlsx") df2<-df %>% mutate(Sample=paste0(reactor,"_",day), S=make.names(S)) %>% select(S,Sample,cov) %>%

The previous tutorial here ended with the generation of bins and co Assembly but what now? Now we can look at how the bins are distributed at each time point. For that we use R with the multitool library tidyverse library(tidyverse) Loading the files We will be loading the individual library mapping to the coassembly first:

First note in HackMD. Let see if this space is useful or just yet another forgetable thing that will accumulate digital dust. This note is designed to set up a Google environement to perform metagenomic co Assembly on mouse stool sample. Each individual mouse was sample multiple point in time allowing to boos the microbial signal. Google VM environment preparation sudo apt-get update sudo apt-get install bzip2 libxml2-dev sudo apt-get install git wget tar unzip sudo ln -s /usr/bin/python3 /usr/bin/python

Quick MD note on how to run the GTDB-Tk pipeline on a google machine. GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based on the Genome Database Taxonomy GTDB. This is useful to estimate which taxonomic unit the bin you get from a metagenomic assembly belongs to. I started a Google E2 standard machine with 16 CPUs, 64 GB RAM, and a 200 GB HDD to run the pipeline. Google CLI The Google CLI is a very convenient way to interact with the Google VMs. More details TBD