My general workflow for processing UCE data with Phyluce v1.5. The code also makes extensive use of phyluce (https://github.com/faircloth-lab/phyluce) and cloudforest (https://github.com/ngcrawford/CloudForest), written by Brant Faircloth and Nick Crawford respectively (and the excellent instructions for Phyluce at http://phyluce.readthedocs.io/en/latest/assembly.html). How I dealt with data using previous Phyluce versions is in prev_phyluce_versions.md in this current directory.
The first steps involve cleaning the reads and extracting the UCEs from the overall assembled contigs. One issue I have noticed with Illumiprocessor is that it expects samples to be named like the following {name}_L001_R1_001.fastq.gz and {name}_L001_R2_001.fastq.gz. Use the sed function to rename the files if need be. Check your cleaned reads through FastQC following the illumiprocessor step, because in same cases cutadapt may be needed to remove the adaptor sequence if trimmomatic doesn't get it all.
for i in *R1_001.fastq.gz; do basename=`echo $i | sed 's/R1_001.fastq.gz//g'`; cutadapt -a AGATCGGAAGAGC -A AGATCGGAAGAGC -o ${basename}adapttrimmed_R1_001.fastq.gz -p ${basename}adapttrimmed_R2_001.fastq.gz $i ${basename}R2_001.fastq.gz -q 5,15 -m 25 >> cutadapt.log; done
Note: recently while processing some other samples, I saw the following on cutadapt's documentation: "Previous versions of this document also recommended using AGATCGGAAGAGC as adapter sequence for both read 1 and read 2, but you should avoid doing so as that sequence occurs multiple times in the human genome." (https://cutadapt.readthedocs.io/en/stable/guide.html). For future projects it would be best to use AGATCGGAAGAGCACACGTCTGAACTCCAGTCA as adapter sequence for read 1 and AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT for read 2, as per cutadapt's recommendations e.g. the following:
for i in *R1_001.fastq.gz; do basename=`echo $i | sed 's/R1_001.fastq.gz//g'`; cutadapt -a AGATCGGAAGAGCACACGTCTGAACTCCAGTCA -A AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT -o ${basename}adapttrimmed_R1_001.fastq.gz -p ${basename}adapttrimmed_R2_001.fastq.gz $i ${basename}R2_001.fastq.gz -q 5,15 -m 25 >> cutadapt.log; done
If there are issues with low percentages of trinity contigs mapping to UCEs, you can improve these numbers by removing over-represented sequences as identified through FastQC (filtering_overrepresented.R). If the FastQC comes back after this with identifiable spikes in kmers at the 5' end of each read, running filtering_kmers.R might be a good idea too if you suspect contamination (note - you should have a good reason to do this, as you could be removing actual useful sequence that just happened to start with that kmer). It might also be a good idea to do this before quality filtering so that these over-represented sequences are not shifted relative to the start of the read, however, this is a pretty time consuming step so I'd see how you go without it first.
In addition, if you have a lot of overlap between your F and R reads, it is a good idea to merge thenm using PEAR if you are planning on using Trinity as your assembler. ABYSS will not be able to utilize these merged reads, so you can skip this if you are going with ABYSS:
for i in *R1_001.fastq.gz; do /public/pear-0.9.10-bin-64/pear-0.9.10-bin-64 -f $i -r ${i/_R1_001/_R2_001} -o ${i/_adapttrimmed_R1_001.fastq.gz/} -n 33 >> pear.log 2>&1; done
#Moving the PEAR assemblies (after deleting the discarded files) into separate folders
for i in *.assembled.fastq; do basename=`echo $i | sed 's/.assembled.fastq//g'`; mkdir $basename; mv $i $basename/${basename}-READ-singleton.fastq; mv $basename.unassembled.forward.fastq $basename/${basename}-READ1.fastq; mv $basename.unassembled.reverse.fastq $basename/${basename}-READ2.fastq; done
for i in *; do gzip $i/*; done
After this, the first thing I do is rename all the files to lower case for the sample names, as this causes issues when converting files to phylip. I conduct the intialsteps on our local linux computers (e.g. the complabs). Things that need to be in paths: Phyluce needs to be in python path, raxml needs to be in path.
Running trinity assemblies using Phyluce 1.5 (http://phyluce.readthedocs.io/en/latest/assembly.html)
phyluce_assembly_assemblo_trinity --config trinity.conf --output trinity-assemblies/ --clean --cores 12 --log-path logs
Alternately, ABYSS:
#Navigate into the cutadaptrimmed folder
for i in *R1_001.fastq.gz; do basename=`echo $i | sed 's/_adapttrimmed_R1_001.fastq.gz//g'`; mkdir $basename; mv $i $basename/${basename}-READ1.fastq.gz; mv ${basename}_adapttrimmed_R2_001.fastq.gz $basename/${basename}-READ2.fastq.gz; done
cd ..
cp trinity.conf abyss.conf
sed -i 's/pearmergeddone/cutadapttrimmed/g' abyss.conf
#ABYSS needs unzipped data
for i in *R1_001.fastq.gz; do basename=`echo $i | sed 's/_adapttrimmed_R1_001.fastq.gz//g'`; mkdir $basename; mv $i $basename/${basename}-READ1.fastq.gz; mv ${basename}_adapttrimmed_R2_001.fastq.gz $basename/${basename}-READ2.fastq.gz; gunzip $basename/${basename}-READ1.fastq.gz; gunzip $basename/${basename}-READ2.fastq.gz; done
phyluce_assembly_assemblo_abyss --config abyss.conf --output abyss-assemblies --kmer 65 --cores 12 --clean --log-path logs
Before matching probes to contigs, I've found I get greater success if I filter the output of trinity to just the longest isoforms (so multiple isoforms of the same gene are not present in the output)
cd trinity-assemblies/contigs
mkdir longest_isoform
cd longest_isoform
for i in ../*.fasta; do newname=`echo $i | sed 's/..\///g'`; /public/trinityrnaseq-2.2.0/util/misc/get_longest_isoform_seq_per_trinity_gene.pl $i > $newname; done
phyluce_assembly_match_contigs_to_probes --contigs trinity-assemblies/contigs/longest_isoform/ --probes coleoptera-v1-master-probe-list-DUPE-SCREENED.fasta --output match_contig_to_probes_longest_iso --log-path logs
Set up a conf file with the names for all your taxa:
[dataset1]
sle0040
sle0047
sle0058
...
For incomplete matrix:
phyluce_assembly_get_match_counts --locus-db match_contig_to_probes_longest_iso/probe.matches.sqlite --taxon-list-config datasets.conf --taxon-group 'dataset1' --output dataset1.conf --log-path logs --incomplete-matrix
Note, if you get the following error, make sure your dataset.conf filename is correct:
Traceback (most recent call last):
File "/public/uce/phyluce/bin/assembly/get_match_counts.py", line 351, in <module>
main()
File "/public/uce/phyluce/bin/assembly/get_match_counts.py", line 329, in main
len(organisms),
TypeError: object of type 'NoneType' has no len()
phyluce_assembly_get_fastas_from_match_counts --contigs trinity-assemblies/contigs/longest_isoform/ --locus-db match_contig_to_probes_longest_iso/probe.matches.sqlite --match-count-output dataset1.conf --incomplete-matrix dataset1.incomplete --output incomplete_fasta --log-path logs
phyluce_align_seqcap_align --fasta incomplete_fasta --output incomplete_mafft_nexus --taxa 64 --aligner mafft --cores 12 --incomplete-matrix --log-path logs
phyluce_align_get_align_summary_data --alignments incomplete_mafft_nexus --cores 10 --log-path logs
phyluce_align_remove_locus_name_from_nexus_lines --alignments incomplete_mafft_nexus --output incomplete_mafft_fasta_no_locus_names --cores 12 --output-format fasta --log-path logs
phyluce_align_get_align_summary_data --alignments incomplete_mafft_fasta_no_locus_names --input-format fasta --cores 10 --log-path logs
(script will not work on nexus file input, even if you specify input-format nexus. You want to run this before adding missing data designators or it will attempt to implement it across the entire dataset, even across taxa the locus is not found in)
phyluce_align_get_gblocks_trimmed_alignments_from_untrimmed --alignments incomplete_mafft_fasta_no_locus_names --output incomplete_mafft_gblocks --output-format nexus --b2 0.5 --log-path logs --cores 10
phyluce_align_get_align_summary_data --alignments incomplete_mafft_gblocks --cores 10 --log-path logs
phyluce_align_get_only_loci_with_min_taxa --alignments incomplete_mafft_gblocks --taxa 64 --percent 0.5 --output 50perc_nexus --cores 12 --log-path logs
phyluce_align_add_missing_data_designators --alignments 50perc_nexus --output 50perc_w_missing --match-count-output dataset1.conf --incomplete-matrix dataset1.incomplete --log-path logs --cores 10 --min-taxa 32 --verbatim --no-check-missing --log-path logs
phyluce_align_get_align_summary_data --alignments 50perc_w_missing --cores 10 --log-path logs
phyluce_align_format_nexus_files_for_raxml --alignments 50perc_w_missing --output concat_phylip
cd concat_phylip
raxmlHPC-PTHREADS-SSE3 -s 50perc_w_missing.phylip -n run1 -m GTRCATI -f a -N 100 -x $RANDOM -p $RANDOM -T 4
raxmlHPC-PTHREADS-SSE3 -s 50perc_w_missing.phylip -n run2 -m GTRCATI -f a -N 100 -x $RANDOM -p $RANDOM -T 4
phyluce_align_convert_one_align_to_another --alignments 50perc_w_missing --output 50perc_w_missing_phylip --input-format nexus --output-format phylip --cores 4 --log-path logs
cd 50perc_w_missing_phylip
#Copy removing_missing.R from https://github.com/laninsky/Phase_hybrid_from_next_gen/blob/master/post-processing/removing_missing.R into the phylip directory
for i in `ls *.phylip`;
do echo $i > name;
Rscript removing_missing.R;
done;
cd ..
I've had problems with phyluce's method for doing this, so this is free-hand code for doing this. After you have made your inputgenetree.tre, follow the code for "Getting the ASTRID and ASTRAL species trees based off gene trees" to generate species trees off your gene trees.
mkdir raxml_genetrees
wd=`pwd`
cd 50perc_w_missing_phylip
unset i
for i in `ls *.phylip`;
do mkdir ../raxml_genetrees/$i;
toraxml="raxmlHPC-SSE3 -m GTRGAMMA -n best -s $wd/50perc_w_missing_phylip/$i -p $RANDOM -w $wd/raxml_genetrees/$i";
$toraxml;
done;
#Summarizing the best trees
cd ../raxml_genetrees;
touch inputgenetrees.tre;
for i in uce*;
do cat $i/RAxML_bestTree.best >> inputgenetrees.tre
done;
#cloudforest needs alignments to be ~9 bp longer than the number of bp in the alignment minus the number taxa in the alignment
cp -r 50perc_w_missing_phylip cloudforest_phylip
cd cloudforest_phylip
rm -rf *.reduced
rm removing_missing.R
rm name
for i in *.phylip;
do nochars=`head -n 1 $i | awk '{print $2}'`;
notaxa=`head -n 1 $i | awk '{print $1}'`;
nochars=$((nochars-notaxa))
nochars=$((nochars-9))
if [ $notaxa -gt $nochars ]
then rm -rf $i;
fi;
done;
cd ..
mkdir cloudforest_genetrees
python2 /usr/local/lib/python2.7/dist-packages/cloudforest/cloudforest_mpi.py cloudforest_phylip cloudforest_genetrees genetrees /public/PhyML-3.1/PhyML-3.1_linux64 --cores 5 --parallelism multiprocessing >> logs/cloudforest.log
#cd into the genetrees folder. The following Phyluce code gets output for each model
phyluce_genetrees_split_models_from_genetrees --genetrees genetrees.tre --output output_models.txt
#R scripts for concatenating together loci with the same substitution model. Make sure you have the two cloudforestconcat Rscripts in the clouldforest_phylip directory
cd ../cloudforest_phylip
cp ../cloudforest_genetrees/output_models.txt output_models.txt
Rscript cloudforestconcat1.R
bash concat_by_model.sh
Rscript cloudforestconcat2.R
#Running RAxML on the partitioned dataset
raxmlHPC-PTHREADS-SSE3 -s concatphylip.phylip -q partitions.txt -n run1 -m GTRCATI -f a -N 100 -x $RANDOM -p $RANDOM -T 4
raxmlHPC-PTHREADS-SSE3 -s concatphylip.phylip -q partitions.txt -n run2 -m GTRCATI -f a -N 100 -x $RANDOM -p $RANDOM -T 4
#Inside the cloudforest_genetrees folder, getting just the genetrees so that the species tree gene tree methods can be run below
awk '{print $5}' genetrees.tre > inputgenetrees.tre
Obtaining *.nex file for use with https://github.com/Tagliacollo/PFinderUCE-SWSC-EN
Alternately, instead of not partitioning, or partitioning on cloudforest models, you might want to use PFinderUCE-SWSC-EN. In this case, the data needs to be partitioned by locus. This script should be run in your phylip_w_missing folder e.g. it should be run in the phyluce output folder that has a separate phylip file per locus, but where you have each taxon present (missing data has been "added" based on the phyluce pipeline. The code we used for adding the missing taxa is here, but for it to work names have to be lower case and the adding-missing-data-designators script has to be run with --verbatim due to this phyluce issue. Thanks for flagging this @ymilesz !). Once you have your phylip_w_missing folder, inside that folder:
Rscript partition_by_locus.R
This will output a file outputdata.nex
Note: you can also achieve this with phyluce using the format_nexus_files_for_raxml script and the --nexus and --charsets flags (thanks to Dr. Michael Branstetter for pointing this out).
Do this for RAxML and cloudforest gene trees - navigate into each of the gene tree folders, and then run the following code
/public/ASTRID-linux -i inputgenetrees.tre -o astrid.tre -m bionj
java -jar /public/Astral/astral.4.10.12.jar -i inputgenetrees.tre -o astral.tre
#Getting local support values for ASTRID tree through Astral
java -jar /public/Astral/astral.4.10.12.jar -q astrid.tre -i inputgenetrees.tre -o astrid_posterior.tre
https://github.com/laninsky/running_SVDquartets
I've made some code that will take a tab-delimited file (called 'key') with the sample names as you have specified them in your UCE fasta files (1st column), as well as the R paste function for what you would like the genbank specifiers to be (2nd column). If you shove it in a folder full of fasta files labelled for each uce locus, it will use the name of the uce-loci in place of 'ucelocus' in the tab-delimited file to rename and print out the fasta sequences for each individual that has data (assuming missing is coded as "-" and "N").
>kaloula_baleata_jam3573 paste(">kaloula_baleata_jam3573","_",ucelocus," [organism=Kaloula baleata] [molecule=DNA] [mol_type=genomic DNA] [specimen_voucher=JAM3573] [note=Sampling location: Sulawesi] Kaloula baleata isolate JAM3573 ","ultra conserved element locus ",ucelocus," genomic sequence",sep="")
>kaloula_baleata_lsuhc5712 paste(">kaloula_baleata_lsuhc5712","_",ucelocus," [organism=Kaloula latidisca] [molecule=DNA] [mol_type=genomic DNA] [specimen_voucher=LSUHC5712] [note=Sampling location: Malaysia] Kaloula latidisca isolate LSUHC5712 ","ultra conserved element locus ",ucelocus," genomic sequence",sep="")
>kaloula_baleata_rmb2401 paste(">kaloula_baleata_rmb2401","_",ucelocus," [organism=Kaloula baleata] [molecule=DNA] [mol_type=genomic DNA] [specimen_voucher=TNHC67086] [note=Sampling location: Java] Kaloula baleata isolate TNHC67086 ","ultra conserved element locus ",ucelocus," genomic sequence",sep="")
After making sure the key file, your fasta files and the R-script(s) are in the same folder. For the linux64.tbl2asn commands, you'll need to have created a template file through sequin which is also in that folder:
template=whatever_your_template_file_is_called
# To submit sqn files with individuals grouped by locus
for i in *.fasta;
do echo $i > name;
Rscript genbankrename_bylocus.R;
outputname=`echo $i | sed 's/.fasta//g'`;
/public/linux64.tbl2asn -i temp -t $template -o $outputname.sqn -s;
rm name;
rm temp;
done;
# To submit sqn files with loci grouped by individuals (currently - 24Mar2017 - what Genbank requests for UCE pop gen datasets)
for i in *.fasta;
do echo $i > name;
Rscript genbankrename_byind.R;
done;
for i in *_ind.fasta;
do outputname=`echo $i | sed 's/_ind.fasta//g'`;
/public/linux64.tbl2asn -i $i -t $template -o $outputname.sqn -s;
done;
The Rscript located in this repository (missing_data.R) will use your final concatenated phylip file to calculate levels of missing data (assuming missing data is represented by "?") by sample (% of sites in concatenated alignment where the sample is missing data). To use it, copy the entire script into R, and then invoke it (in R) by:
missing_data("/path/to/phylip_file")
If you would like to calculate this based on fasta files instead, check out: https://github.com/laninsky/Missing_data_for_UCE_loci
Check out the folder 'extracting_non_UCEs'
First written for:
Alexander, A.M., Su, Y.C., Oliveros, C.H., Olson, K.V., Travers, S.L. and Brown, R.M., 2017. Genomic data reveals potential for hybridization, introgression, and incomplete lineage sorting to confound phylogenetic relationships in an adaptive radiation of narrow‐mouth frogs. Evolution, 71(2), pp.475-488.
Modifed for: Baca SM, Alexander A, Gustafson GT, Short AE. Ultraconserved elements show utility in phylogenetic inference of A dephaga (C oleoptera) and suggest paraphyly of ‘Hydradephaga’. Systematic Entomology. 2017 Oct;42(4):786-95.
This section modified with: Beetles TBD
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