MWMW

metagenomic binning, quantification, and analysis with metawrap

Notes:

• Bin 26 is E. Coli, Bin 52 is M. aeruginosa, Bin 18 should be Runella slithyformis
• Bin 43 is a new thing: https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Info&id=1925548&lvl=3&lin=f&keep=1&srchmode=1&unlock
• Bin 43 contigs are 100% classified as Fonsibacter

TODO:

• Pull reads that map to 16S gene from libraries, classify, and assign to bins based on combined objective of taxanomic class & abundance vector matches
• Make master script to string together accesory shell scripts from marcc
• Add Shell scripts from MARCC to scripts
• use phylosift to add taxonomy to poorly classified bins
• check degree of homology between & within bins
  • determine the degree of e. coli sequence dispersion
• compare environmental gene abundances within each bin to overall bin abundance
• make map of gene:process and plot process by sample in violins
• determine which CAZy genes are responsive to DOM & check their internal consistency

Contents of Data/ include:

• Bin_Taxonomy.xlsx: Consensus bin taxonomy & scores
• BinningMethodsText.docx: Description of methods required by GSC
• MAG_Min_Standards_Description.xlsx: GSC reference document for req'd MAG info
• Mystic_MAG_Quality_Stats.xlsx: Individual MAG stats incl. # unique tRNAs # rRNA seqs, completeness, contamination, GC, # contigs/genes/scaffolds, Coding density, GC pct, GC std, Genome size, contig/scaffold length, N50, and more
• Bin_Abundances/
  • bin_abundance.tab: matrix of average bin coverage per sample
  • bin_counts_normed.tsv: unit normalized within sample & then normalized by library size
  • genome_abundance_heatmap.png: clustered heatmap of bin_abundance.tab with assoc. dendograms
  • sample_read_count.tab: vector of read counts per sample for normalizing bin_abundance.tab
• Blob_Plots/: deeply unhelpful plots of GC% v. coverage of contigs colored in various ways
• KEGG_Annotations/:
  • AllProteinsRenamed.faa.bz2: FASTA of ALL protein sequences with bin name & gene id in header (uploaded to KEGG)
  • Aggregated_Annotations.tsv: Combined & quality filtered KEGG annotations by GhostKoala & BlastKoala programs
  • Select_Annotations.tsv: Same format as Aggregated_Annotations.tsv but restricted to KO numbers of interest
  • Select_Ks_By_Bin.tsv: a matrix of select KO hit counts by bin
  • All_HMM_Hits_raw.tsv: a matrix of db-CAN & metabolic-hmm annotations with gene id & bin info
  • HMM_counts_by_bin.tsv: a matrix of hmm hit counts by bin
  • gene_abundances_raw.tsv: a matrix of select annotation coverages by sample (sample normalized)
  • duplicate_clusters.tsv: output by Salmon as duplicate sequences while calculating coverage (*by_bin.tsv files need correction)
• Krona_Plots/:
  • mysticLibs_kronagram.html: assumed taxanomic abundances using QC'd reads as input
  • final_assembly_kronagram.html: assumed taxanomic abundances using assembled contigs as input
• QUAST_CoAssembly_Stats/
  • report.html: contains co-assembly descriptive statistics
• 16S_Info/
  • 16s_annotations.gff: contains info on bin #, contig id, gene id, and locus, & length
  • RibosomalRNA.RDP_classes.txt: contains taxa classes for assembled 16S rRNA
  • RibosomalRNA.fa: contains assembled 16S rRNA sequence with bin number of origin & gene id in header
• intermediate_files/: probably unecessary stuff