Eaton & Ree (2013) single-end RAD data set¶
Here we demonstrate a denovo assembly for an empirical RAD data set to give a general idea of the results you might expect to recover. This example was run on a 8-core laptop with 16GB RAM, and takes about 1 hour to run completely.
We will use the 13 taxa Pedicularis data set from Eaton and Ree (2013) (open access link). This data set is composed of single-end 75bp reads from a RAD-seq library prepared with the PstI enzyme. This data set also serves as an example for several of our analysis tools to demonstrate methods for analyzing RAD-seq results. So after you finish this assembly head over there to check out fun ways to analyze the data.
Download the data set (Pedicularis)¶
These data are archived on the NCBI sequence read archive (SRA) under
accession id SRP021469. We’ve written a convenient wrapper for sra-tools
that allows ipyrad to download data from SRA, SRP, ERA, etc.,
IDs easily (more info here). Run the code below to download and decompress the fastq data files,
which will save them into a directory called example_empirical_data/,
or whatever you wish to name it. The directory will be created if it doesn’t
already exist. The compressed file size is approximately 1.1GB.
# first we need to download an additional tool
>>> conda install sra-tools -c bioconda
# then, use ipyrad to download the fastq data from the SRA database
>>> ipyrad --download SRP021469 example_empirical_data/
The –download function will print the following output:
Fetching project data...
Run spots mates ScientificName SampleName
0 SRR1754715 696994 0 Pedicularis superba 29154_superba
1 SRR1754720 1452316 0 Pedicularis thamnophila 30556_thamno
2 SRR1754730 1253109 0 Pedicularis cyathophylla 30686_cyathophylla
3 SRR1754729 964244 0 Pedicularis przewalskii 32082_przewalskii
4 SRR1754728 636625 0 Pedicularis thamnophila 33413_thamno
5 SRR1754727 1002923 0 Pedicularis przewalskii 33588_przewalskii
6 SRR1754731 1803858 0 Pedicularis rex 35236_rex
7 SRR1754726 1409843 0 Pedicularis rex 35855_rex
8 SRR1754725 1391175 0 Pedicularis rex 38362_rex
9 SRR1754723 822263 0 Pedicularis rex 39618_rex
10 SRR1754724 1707942 0 Pedicularis rex 40578_rex
11 SRR1754722 2199740 0 Pedicularis cyathophylloides 41478_cyathophylloides
12 SRR1754721 2199613 0 Pedicularis cyathophylloides 41954_cyathophylloides
Parallel connection | latituba: 8 cores
[####################] 100% 0:01:43 | downloading/extracting fastq data
13 fastq files downloaded to /home/deren/Documents/ipyrad/sandbox/pedicularis/example_empirical_data
Setup a params file¶
Always start an ipyrad assembly by using the -n {name} argument to
create a new named Assembly. I’ll use the name pedicularis to
indicate taxa being assembled.
>>> ipyrad -n pedicularis
This will print the message:
New file 'params-pedicularis.txt' created in /home/deren/Documents/ipyrad/sandbox
In this example, the data come to us already demultiplexed so we are going to simply set the sorted_fastq_path to tell ipyrad the location of our data files. Published data sets will typically be available in this way, already demultiplexed. You can select multiple files at once using regular expressions, in this example we use an asterisk (*.gz) to select all files in the directory ending in .gz. We also set a project_dir, which is useful for grouping all our results into a single directory. For this we’ll use name the project directory “analysis-ipyrad”. If this folder doesn’t exist then ipyrad will create it. Take note when entering the values below into your params file that they properly correspond to parameters 1 and 4, respectively. Use any text editor to edit the params file:
# Use your text editor to enter the following values:
# The wildcard (*) tells ipyrad to select all files ending in .gz
analysis-ipyrad ## [1] [project_dir] ...
example_empirical_data/*.fastq ## [4] [sorted_fastq_path] ...
We’ll add a few additional options as well to: filter for adapters (param 16); trim the 3’ edge of R1 aligned loci by 5bp (param 26; this is optional, but helps to remove poorly aligned 3’ edges); and produce all output formats (param 27):
# enter the following params as well
2 ## [16] [filter_adapters] ...
0, 5, 0, 0 ## [26] [trim_loci] ...
* ## [27] [output_formats] ...
We’ll leave the remaining parameters at their default values.
Step 1: Load the fastq data¶
Start an ipyrad assembly by running step 1. When the data location is entered
as a sorted_fastq_path (param 4), as opposed to the raw_fastq_path
(param 2), step 1 simply counts the number of reads for each Sample and
parses the file names to extract names for each Sample. For example, the
file 29154_superba.fastq.gz will be assigned to Sample 29154_superba.
We use the -s argument followed by 1 to tell ipyrad to run step 1. We also
pass it the -r argument so that it will print a results summary when finished.
>>> ipyrad -p params-pedicularis.txt -s 1 -r
Shows the current state of the assembly:
-------------------------------------------------------------
ipyrad [v.0.9.14]
Interactive assembly and analysis of RAD-seq data
-------------------------------------------------------------
Parallel connection | latituba: 8 cores
Step 1: Loading sorted fastq data to Samples
[####################] 100% 0:00:06 | loading reads
13 fastq files loaded to 13 Samples.
Parallel connection closed.
Summary stats of Assembly pedicularis
------------------------------------------------
state reads_raw
29154_superba_SRR1754715 1 696994
30556_thamno_SRR1754720 1 1452316
30686_cyathophylla_SRR1754730 1 1253109
32082_przewalskii_SRR1754729 1 964244
33413_thamno_SRR1754728 1 636625
33588_przewalskii_SRR1754727 1 1002923
35236_rex_SRR1754731 1 1803858
35855_rex_SRR1754726 1 1409843
38362_rex_SRR1754725 1 1391175
39618_rex_SRR1754723 1 822263
40578_rex_SRR1754724 1 1707942
41478_cyathophylloides_SRR1754722 1 2199740
41954_cyathophylloides_SRR1754721 1 2199613
Full stats files
------------------------------------------------
step 1: ./analysis-ipyrad/pedicularis_s1_demultiplex_stats.txt
step 2: None
step 3: None
step 4: None
step 5: None
step 6: None
step 7: None
Run the remaining assembly steps¶
Because the point of this tutorial is to demonstrate run times and statistics, I will leave the rest of the parameters at their defaults and simply run all remaining steps. Further below I will explain in more detail the stats files for each step and the meaning of the stats values.
## run steps 2-7
>>> ipyrad -p params-pedicularis.txt -s 234567 -r
Which produces abundant progress messages:
-------------------------------------------------------------
ipyrad [v.0.9.14]
Interactive assembly and analysis of RAD-seq data
-------------------------------------------------------------
Parallel connection | latituba: 8 cores
Step 2: Filtering and trimming reads
[####################] 100% 0:01:59 | processing reads
Step 3: Clustering/Mapping reads within samples
[####################] 100% 0:00:12 | dereplicating
[####################] 100% 0:07:34 | clustering/mapping
[####################] 100% 0:00:01 | building clusters
[####################] 100% 0:00:00 | chunking clusters
[####################] 100% 0:12:11 | aligning clusters
[####################] 100% 0:00:04 | concat clusters
[####################] 100% 0:00:03 | calc cluster stats
Step 4: Joint estimation of error rate and heterozygosity
[####################] 100% 0:00:31 | inferring [H, E]
Step 5: Consensus base/allele calling
Mean error [0.00314 sd=0.00090]
Mean hetero [0.02171 sd=0.00385]
[####################] 100% 0:00:03 | calculating depths
[####################] 100% 0:00:05 | chunking clusters
[####################] 100% 0:09:12 | consens calling
[####################] 100% 0:00:06 | indexing alleles
Step 6: Clustering/Mapping across samples
[####################] 100% 0:00:03 | concatenating inputs
[####################] 100% 0:02:06 | clustering across
[####################] 100% 0:00:02 | building clusters
[####################] 100% 0:01:31 | aligning clusters
Step 7: Filtering and formatting output files
[####################] 100% 0:00:14 | applying filters
[####################] 100% 0:00:09 | building arrays
[####################] 100% 0:00:10 | writing conversions
[####################] 100% 0:01:27 | indexing vcf depths
[####################] 100% 0:00:24 | writing vcf output
Parallel connection closed.
Summary stats of Assembly pedicularis
------------------------------------------------
state reads_raw ... error_est reads_consens
29154_superba_SRR1754715 6 696994 ... 0.003211 29903
30556_thamno_SRR1754720 6 1452316 ... 0.003184 43870
30686_cyathophylla_SRR1754730 6 1253109 ... 0.003297 45856
32082_przewalskii_SRR1754729 6 964244 ... 0.003079 34733
33413_thamno_SRR1754728 6 636625 ... 0.003317 26228
33588_przewalskii_SRR1754727 6 1002923 ... 0.003267 38137
35236_rex_SRR1754731 6 1803858 ... 0.002206 46683
35855_rex_SRR1754726 6 1409843 ... 0.004316 46234
38362_rex_SRR1754725 6 1391175 ... 0.002350 46081
39618_rex_SRR1754723 6 822263 ... 0.003636 37259
40578_rex_SRR1754724 6 1707942 ... 0.002229 48255
41478_cyathophylloides_SRR1754722 6 2199740 ... 0.001721 47976
41954_cyathophylloides_SRR1754721 6 2199613 ... 0.005028 64654
[13 rows x 8 columns]
Full stats files
------------------------------------------------
step 1: ./analysis-ipyrad/pedicularis_s1_demultiplex_stats.txt
step 2: ./analysis-ipyrad/pedicularis_edits/s2_rawedit_stats.txt
step 3: ./analysis-ipyrad/pedicularis_clust_0.85/s3_cluster_stats.txt
step 4: ./analysis-ipyrad/pedicularis_clust_0.85/s4_joint_estimate.txt
step 5: ./analysis-ipyrad/pedicularis_consens/s5_consens_stats.txt
step 6: ./analysis-ipyrad/pedicularis_across/pedicularis_clust_database.fa
step 7: ./analysis-ipyrad/pedicularis_outfiles/pedicularis_stats.txt
Take a look at the stats summary¶
Each assembly that finishes step 7 will create a stats.txt output summary in the ‘assembly_name’_outfiles/ directory. This includes information about which filters removed data from the assembly, how many loci were recovered per sample, how many samples had data for each locus, and how many variable sites are in the assembled data.
>>> cat ./analysis-ipyrad/pedicularis_outfiles/pedicularis_stats.txt
Shows the contents of the stats file:
## The number of loci caught by each filter.
## ipyrad API location: [assembly].stats_dfs.s7_filters
total_filters applied_order retained_loci
total_prefiltered_loci 0 0 80481
filtered_by_rm_duplicates 828 828 79653
filtered_by_max_indels 1290 1290 78363
filtered_by_max_SNPs 946 914 77449
filtered_by_max_shared_het 718 699 76750
filtered_by_min_sample 35889 35672 41078
total_filtered_loci 39671 39403 41078
## The number of loci recovered for each Sample.
## ipyrad API location: [assembly].stats_dfs.s7_samples
sample_coverage
29154_superba_SRR1754715 21095
30556_thamno_SRR1754720 31418
30686_cyathophylla_SRR1754730 26754
32082_przewalskii_SRR1754729 14507
33413_thamno_SRR1754728 18504
33588_przewalskii_SRR1754727 16928
35236_rex_SRR1754731 32588
35855_rex_SRR1754726 32462
38362_rex_SRR1754725 33372
39618_rex_SRR1754723 27673
40578_rex_SRR1754724 33260
41478_cyathophylloides_SRR1754722 31255
41954_cyathophylloides_SRR1754721 28381
## The number of loci for which N taxa have data.
## ipyrad API location: [assembly].stats_dfs.s7_loci
locus_coverage sum_coverage
1 0 0
2 0 0
3 0 0
4 5347 5347
5 3809 9156
6 3488 12644
7 3096 15740
8 3330 19070
9 4217 23287
10 5102 28389
11 5422 33811
12 4562 38373
13 2705 41078
The distribution of SNPs (var and pis) per locus.
## var = Number of loci with n variable sites (pis + autapomorphies)
## pis = Number of loci with n parsimony informative site (minor allele in >1 sample)
## ipyrad API location: [assembly].stats_dfs.s7_snps
## The "reference" sample is included if present unless 'exclude_reference=True'
var sum_var pis sum_pis
0 1806 0 10232 0
1 3528 3528 9935 9935
2 4758 13044 7601 25137
3 5297 28935 5109 40464
4 5183 49667 3212 53312
5 4650 72917 2029 63457
6 3893 96275 1225 70807
7 3340 119655 757 76106
8 2529 139887 456 79754
9 1967 157590 302 82472
10 1480 172390 132 83792
11 1145 184985 68 84540
12 796 194537 16 84732
13 541 201570 4 84784
14 151 203684 0 84784
15 13 203879 0 84784
16 0 203879 0 84784
17 0 203879 0 84784
18 0 203879 0 84784
19 1 203898 0 84784
## Final Sample stats summary
state reads_raw reads_passed_filter clusters_total clusters_hidepth hetero_est error_est reads_consens loci_in_assembly
29154_superba_SRR1754715 7 696994 689996 126896 34145 0.024641 0.003211 29903 21095
30556_thamno_SRR1754720 7 1452316 1440314 192920 50491 0.022635 0.003184 43870 31418
30686_cyathophylla_SRR1754730 7 1253109 1206947 225144 52464 0.020622 0.003297 45856 26754
32082_przewalskii_SRR1754729 7 964244 955480 142366 41046 0.027211 0.003079 34733 14507
33413_thamno_SRR1754728 7 636625 626084 165338 30754 0.024820 0.003317 26228 18504
33588_przewalskii_SRR1754727 7 1002923 993873 148920 44642 0.025917 0.003267 38137 16928
35236_rex_SRR1754731 7 1803858 1787366 401906 52694 0.019709 0.002206 46683 32588
35855_rex_SRR1754726 7 1409843 1397068 164312 54484 0.025071 0.004316 46234 32462
38362_rex_SRR1754725 7 1391175 1379626 124417 51061 0.016379 0.002350 46081 33372
39618_rex_SRR1754723 7 822263 813990 138973 42451 0.022817 0.003636 37259 27673
40578_rex_SRR1754724 7 1707942 1695523 210842 54539 0.019760 0.002229 48255 33260
41478_cyathophylloides_SRR1754722 7 2199740 2185364 162093 53191 0.015180 0.001721 47976 31255
41954_cyathophylloides_SRR1754721 7 2199613 2176210 286667 72791 0.017415 0.005028 64654 28381
## Alignment matrix statistics:
snps matrix size: (13, 203898), 35.26% missing sites.
sequence matrix size: (13, 2840602), 35.60% missing sites.
Take a peek at the .loci output¶
This is the first place I look when an assembly finishes. It provides a clean view of the data with variable sites (-) and parsimony informative SNPs (*) highlighted. Use the unix commands less or head to look at this file briefly. Each locus is labelled with a number corresponding to the locus order before filters are applied in step 7. If you branch this assembly and run step 7 again with a different set of parameters you may recover fewer or more total loci.
## head -n 50 prints just the first 50 lines of the file to stdout
>>> head -n 50 analysis-ipyrad/pedicularis_outfiles/pedicularis.loci
29154_superba_SRR1754715 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGGGTACCCTGCGAACTTCCAAATTCACCCTCATCG
30556_thamno_SRR1754720 TAGGGTGGGTCKCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCG
30686_cyathophylla_SRR1754730 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGGGTACCCTGCGAACTTCCAAATTCACCCTCATCG
32082_przewalskii_SRR1754729 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAAGAGGGTACCCTGCGAACTTCCAAATTCACCCTCNTCG
33413_thamno_SRR1754728 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCG
33588_przewalskii_SRR1754727 TAGGGTGGGTCTCNTTCAAGGTATTCGAACAASAGGGTACCCTGCGAACTTCCAAATTCACCCTCATCG
35236_rex_SRR1754731 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCG
35855_rex_SRR1754726 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCG
38362_rex_SRR1754725 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCG
39618_rex_SRR1754723 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCG
40578_rex_SRR1754724 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCCTGCGAACTTCCAAATTCACCCTCATCA
41478_cyathophylloides_SRR1754722 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAATAGGGTACCCAGCGAACTTCCAAATTCACCCTCATCG
41954_cyathophylloides_SRR1754721 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAATAGGGTACCCAGCGAACTTCCAAATTCACCCTCATCG
// - * * * -|0|
29154_superba_SRR1754715 ACGACGTCTCTCCCCGAGCCGGCTATCAGGAGACGGATTTTCGAGATGGGGGGTCGTTTTGCTGTTTGT
30556_thamno_SRR1754720 ACGACGTCTCTCCCCGAGCCGGCTATCAGGAGACGGATTTTCGAGATGGGGGGTCGTTTTGCTGTTTGT
33413_thamno_SRR1754728 ACGACGTCTCTCCCCGAGMCGGCTATCAGGAGACGGATTTTCGAGATGGGGGGTCGTTTTGCTGTTTGT
40578_rex_SRR1754724 ACGACGTCTCTCCCCGAGCCGGCTATCAGGAGACGGATTTTCGAGATGGGGGGTCGTTTTGCTGTTTGT
// - |1|
29154_superba_SRR1754715 CTTGGCACTGAATTAGCAGAACTTCAACAATTAAGTCTCCAGTATAATTGAATTYGATTTAATTTAATT
30686_cyathophylla_SRR1754730 CTTGGCACTGAATTAGCAGAACTTCAACAATTAAGTCTCCAGTATAACTGAATTTGATTTAATTTAATT
35236_rex_SRR1754731 CTTGGCACTGAAGTAGCAGAACTTCAACAATTAAGTCTCCAGTATAATTGAATTTGATTTAATTTAATG
35855_rex_SRR1754726 CTTGGCACTGAAGTAGCAGAACTTCAACAATTAAGTCTCCGGTATAATTGAATTTGATTTAATTTAATG
38362_rex_SRR1754725 CTTGGCACTGAAGTAGCAGAACTTCAACAATTAAGTCTCAGGTATAATTGAATTTGATTTAATTTAATT
40578_rex_SRR1754724 CTTGGCACTCAAGTAGCAGAACTTCAACAATTAAGTCTCCGGTATAATTGAATTTGATTTAATTTAATG
41478_cyathophylloides_SRR1754722 CTTGGCACTGAAGTAGCAGAACTTCAACAATTAAGTCTCCAGTATAATTGAATTTGATTTAATTTAATT
41954_cyathophylloides_SRR1754721 CTTGGCACTGAAGTAGCAGAACTTCAACAATTAAGTCTCCAGTATAATTGAATTTGATTTAATTTAATT
// - * -* - - *|2|
29154_superba_SRR1754715 GATCCTGAAATGACAASAAACATAACANGGGGGTAATTTTTTGTAATTAT---CCCTTAGA-TAAACTATACA
33413_thamno_SRR1754728 GATCCTGAAACGACAACAAACATAACACGGGGGTAATYTTTTGTAATTAT---CCCTTMGA-TAAACTATACA
35236_rex_SRR1754731 GATCCTGAAACGACAACAAACATAACACGGGGGTAATTTTTTGTAATTAT---CCCTTAGA-TAAACTATACA
38362_rex_SRR1754725 GATCCTGAAACGACAACAAACATAACACGGGGGTAATTTTTTGTAATTAT---CCCTTAGA-TAAACTATACA
39618_rex_SRR1754723 GATCCTGAAACGACAACAAACATAACACGGGGGTAATTTTTTGTAATTAT---CCCTTAGA-TAAACTATACA
40578_rex_SRR1754724 GATCCTGAAACGACAACAAACATAACAYGGGGGTAATTTTTTGTAATTAY---CCCTTAGA-TAAACTATACA
41478_cyathophylloides_SRR1754722 GATCCTGAAATGACAACAAACATAACAGGGGGGTAATTTTTTGTAATTATCCCCCCTTAGATTAAACTA----
41954_cyathophylloides_SRR1754721 GATCCTGAAATGACAACAAACATAACAGGGGGGTAATTTTTTGTAATTATCCCCCCTTAGATTAAACT-----
// * - * - - - |3|
29154_superba_SRR1754715 AAAACAGGATGAGTGCATATCTCTCGTTCTAACTACTGCAATGCTAGGNAAATAAAATACAGACTAAAA
30686_cyathophylla_SRR1754730 AAAACAGGATGAGTGCATATCTCTCGTTCTAACTACTGCAATGCTAGGTAAATAAAATACAGACTAAAA
32082_przewalskii_SRR1754729 AAAACAGGATGAGTGCATATCTCTCGTACTAACTACTGCAATGCTAGGTAAATAAAATACAGACTAAAA
33588_przewalskii_SRR1754727 AAAACAGGATGAGTGCATATCTCTCGTACTAACTACTGCAATGCTAGGTAAATAAAATACAGACTAAAA
41478_cyathophylloides_SRR1754722 AAAACAGGATGAGTGCATATCTCTCGTTTTAACTACTGCAATGCTAGGTAAATAAAATAGAGACTAAAA
41954_cyathophylloides_SRR1754721 AAAACAGGATGAGTGCATATCTCTCGTTTTAACTACTGCAATGCTAGGTAAATAAAATAGAGACTAAAA
// ** * |4|
peek at the .phy files¶
This is the concatenated sequence file of all loci in the data set. It is typically used in phylogenetic analyses, like in the program raxml. This super matrix is 13 taxon deep by 2.44 Mbp long.
## cut -c 1-80 prints only the first 80 characters of the file
>>> cut -c 1-80 analysis-ipyrad/pedicularis_outfiles/pedicularis.phy
Shows a small piece of the data:
13 2840602
29154_superba_SRR1754715 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGGGTACCC
30556_thamno_SRR1754720 TAGGGTGGGTCKCGTTCAAGGTATTCGAACAACAGAGTACCC
30686_cyathophylla_SRR1754730 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGGGTACCC
32082_przewalskii_SRR1754729 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAAGAGGGTACCC
33413_thamno_SRR1754728 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCC
33588_przewalskii_SRR1754727 TAGGGTGGGTCTCNTTCAAGGTATTCGAACAASAGGGTACCC
35236_rex_SRR1754731 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCC
35855_rex_SRR1754726 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCC
38362_rex_SRR1754725 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCC
39618_rex_SRR1754723 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCC
40578_rex_SRR1754724 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAACAGAGTACCC
41478_cyathophylloides_SRR1754722 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAATAGGGTACCC
41954_cyathophylloides_SRR1754721 TAGGGTGGGTCTCGTTCAAGGTATTCGAACAATAGGGTACCC
peek at the .snps.phy file¶
This is similar to the phylip file format, but only variable site columns are included. All SNPs are in the file, in contrast to the .u.snps.phy file, which randomly selects only a single SNP per locus.
## cut -c 1-80 prints only the first 80 characters of the file
>>> cut -c 1-80 analysis-ipyrad/pedicularis_outfiles/pedicularis.snps.phy
Just the snps:
13 203898
29154_superba_SRR1754715 TCGTGCGTCATYTTSNTTATCCGAYYACTGTGTAAGCCGGGG
30556_thamno_SRR1754720 KCATGCNNNNNNNNNNNNNNNNGACCGNNGTGTAAGCCGGGG
30686_cyathophylla_SRR1754730 TCGTGNGTCACTTNNNNNNTCCGACCACTGTGTAAGCCAGGG
32082_przewalskii_SRR1754729 TGGTGNNNNNNNNNNNNNNACCNNNNNNNNNNNNNNNTGCAA
33413_thamno_SRR1754728 TCATGMNNNNNNNCCCYTMNNNGACCGNNGTGTAAGCNNNNN
33588_przewalskii_SRR1754727 TSGTGNNNNNNNNNNNNNNACCATCCGNNACATAAGCTGCAA
35236_rex_SRR1754731 TCATGNGGCATTGCCCTTANNNGACCGYTGTGTRRGCNNNNN
35855_rex_SRR1754726 TCATGNGGCGTTGNNNNNNNNNGACCGCTGTGTAAGCNNNNN
38362_rex_SRR1754725 TCATGNGGAGTTTCCCTTANNNGACCGNNTTGTAAGANNNNN
39618_rex_SRR1754723 TCATGNNNNNNNNCCCTTANNNGACCGNNNNNNNNNNNNNNN
40578_rex_SRR1754724 TCATACCGCGTTGCCYTYANNNGACCGCWGTGAAARCNNNNN
41478_cyathophylloides_SRR1754722 TTGAGNGGCATTTTCGTTATTGGACCGCTGTGTAAGCCGGGG
41954_cyathophylloides_SRR1754721 TTGAGNGGCATTTTCGTTATTGGACCGCTGTGTAAGCCGGGG
peek at the .vcf.gz file¶
The VCF output for ipyrad contains the full sequence information for all samples as well as the sequencing depth information for all base calls that were made. This file should be easily parsable if users want to extract information or modify it so that this file can be used in other software such as GATK. We are working on developing our own population-aware genotype caller that will correct low-depth base calls at this stage. Stay tuned.
## gunzip -c decompresses the file and passes it to the pipe (|)
## head -n 50 reads data from the pipe and show the first 50 lines.
## and we pipe this to 'cut', which shows only the first 80 rows of data
## for easier viewing.
>>> head -n 50 analysis-ipyrad/pedicularis_outfiles/pedicularis.vcf | cut -c 1-80
##fileformat=VCFv4.0
##fileDate=2017/02/14
##source=ipyrad_v.0.7.28
##reference=pseudo-reference (most common base at site)
##phasing=unphased
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Dat
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=CATG,Number=1,Type=String,Description="Base Counts (CATG)">
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT 29154_superba 30556_thamno 30
locus_1 2 . A C,G 13 PASS NS=5;DP=49 GT:DP:CATG 0/0:9:0,9,0,0 1/1:7:7,0,0,0
locus_1 3 . T A 13 PASS NS=5;DP=49 GT:DP:CATG 0/0:9:0,0,9,0 1/1:7:0,7,0,0 0
locus_1 19 . A G 13 PASS NS=5;DP=49 GT:DP:CATG 0/0:9:0,9,0,0 1/1:7:0,0,0,7
locus_1 21 . C T 13 PASS NS=5;DP=49 GT:DP:CATG 1/1:9:0,0,9,0 0/0:7:7,0,0,0
locus_1 30 . T C 13 PASS NS=5;DP=49 GT:DP:CATG 0/0:9:0,0,9,0 0/0:7:0,0,7,0
locus_1 36 . C T 13 PASS NS=5;DP=49 GT:DP:CATG 0/0:9:9,0,0,0 1/1:7:0,0,7,0
locus_2 15 . A G 13 PASS NS=11;DP=210 GT:DP:CATG 0/0:12:0,12,0,0 0/0:24:0,2
locus_2 16 . A T,C 13 PASS NS=11;DP=210 GT:DP:CATG 0/0:12:0,12,0,0 0/0:24:0
locus_2 18 . A T 13 PASS NS=11;DP=210 GT:DP:CATG 0/0:12:0,12,0,0 0/0:24:0,2
locus_2 20 . T C 13 PASS NS=11;DP=210 GT:DP:CATG 1/1:12:12,0,0,0 0/0:24:0,0
locus_2 29 . T C 13 PASS NS=11;DP=209 GT:DP:CATG 0/0:12:0,0,12,0 0/0:23:0,0
locus_2 30 . A G 13 PASS NS=11;DP=209 GT:DP:CATG 0/0:12:0,12,0,0 0/0:23:0,2
locus_2 47 . T A 13 PASS NS=11;DP=210 GT:DP:CATG 0/0:12:0,0,12,0 0/0:24:0,0
locus_3 46 . A T 13 PASS NS=6;DP=69 GT:DP:CATG 1/1:10:0,0,10,0 ./.:0:0,0,0,
locus_3 62 . C A 13 PASS NS=6;DP=68 GT:DP:CATG 0/0:10:10,0,0,0 ./.:0:0,0,0,
locus_6 11 . G A 13 PASS NS=4;DP=67 GT:DP:CATG 1/1:11:0,11,0,0 0/0:7:0,0,0,
locus_6 29 . G A 13 PASS NS=4;DP=67 GT:DP:CATG 1/1:11:0,11,0,0 0/0:7:0,0,0,
locus_6 34 . C A 13 PASS NS=4;DP=67 GT:DP:CATG 1/1:11:0,11,0,0 0/0:7:7,0,0,
locus_6 35 . G T 13 PASS NS=4;DP=67 GT:DP:CATG 0/0:11:0,0,0,11 0/0:7:0,0,0,
locus_6 40 . T C 13 PASS NS=4;DP=67 GT:DP:CATG 0/0:11:0,0,11,0 1/1:7:7,0,0,
locus_9 19 . A C 13 PASS NS=13;DP=224 GT:DP:CATG 0/0:12:0,12,0,0 0/0:22:0,2
locus_9 25 . A G 13 PASS NS=13;DP=224 GT:DP:CATG 0/0:12:0,12,0,0 0/0:22:0,2
locus_11 4 . C T 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:11,0,0,0 0/0:17:17,
locus_11 13 . C T 13 PASS NS=10;DP=137 GT:DP:CATG 1/1:11:0,1,10,0 0/0:17:17
locus_11 21 . G A 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:0,0,0,11 0/0:17:0,
locus_11 23 . A G 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:0,11,0,0 1/1:17:0,
locus_11 24 . A T 13 PASS NS=10;DP=137 GT:DP:CATG 1/1:11:0,0,11,0 0/0:17:0,
locus_11 38 . G T 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:0,0,0,11 0/0:17:0,
locus_11 42 . A G 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:0,11,0,0 0/0:17:0,
locus_11 54 . A G 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:0,11,0,0 0/0:17:0,
locus_11 55 . A G 13 PASS NS=10;DP=137 GT:DP:CATG 0/0:11:0,11,0,0 0/0:17:0,
locus_12 6 . C T 13 PASS NS=7;DP=94 GT:DP:CATG 1/0:7:4,0,3,0 ./.:0:0,0,0,0
locus_12 20 . C T 13 PASS NS=7;DP=94 GT:DP:CATG 0/0:7:7,0,0,0 ./.:0:0,0,0,0
locus_12 31 . T C 13 PASS NS=7;DP=94 GT:DP:CATG 0/0:7:0,0,7,0 ./.:0:0,0,0,0
locus_12 33 . G A 13 PASS NS=7;DP=94 GT:DP:CATG 1/1:7:0,7,0,0 ./.:0:0,0,0,0
locus_12 37 . G T 13 PASS NS=5;DP=52 GT:DP:CATG 0/0:7:0,0,0,7 ./.:0:0,0,0,0
locus_12 43 . C G 13 PASS NS=7;DP=94 GT:DP:CATG 1/1:7:0,0,0,7 ./.:0:0,0,0,0
locus_12 45 . G C,A 13 PASS NS=7;DP=94 GT:DP:CATG 0/0:7:0,0,0,7 ./.:0:0,0,0
locus_12 47 . G T 13 PASS NS=7;DP=94 GT:DP:CATG 0/0:7:0,0,0,7 ./.:0:0,0,0,0