Raw sequence downloads and NCBI SRA uploads for M. capitata larval thermal tolerance project top off sequencing second upload

This post details the NCBI Sequence Read Archive upload for my Montipora capitata 2023 larval thermal tolerance project. See my notebook posts and my GitHub repo for information on this project.

I previously uploaded and QC’d data from our first round of sequencing in this project with downloads detailed here and QC information here.

Due to low read depth in some samples (13 samples at <20M reads, 7 samples at <15M reads), Azenta performed top off sequencing to meet deliverables for this project. Azenta added additional sequencing for 13 total samples. These samples were distributed across treatments.

In the first round of sequencing (Feb 2024), samples were sequenced on one lane of a NovaX-25B instrument. The top off samples were also performed on one lane of the same instrument on 4/11/2024.

This post details downloads and SRA uploads for the new sequencing files.

1. Download top off data from Azenta

View result statistics and metadata

I used Azenta’s sFTP instructions to view the project results. In their online storage, they provided an .html with an overview of statistics and the R1 and R2 .fastq.gz files for each sample. There are also .md5 files for each .fastq.gz file.

sftp ashuff_uw@sftp.genewiz.com
#entered password from email

lcd MyProjects/larval_symbiont_TPC/data/rna_seq
cd 30-943303755
cd second_delivery
mget Azenta_30-943303755_Data_Report.html

I renamed this file to have “_second” on the title and retained the original file for the first round of sequencing with the file name Azenta_30-943303755_Data_Report.html.

The file for the second sequencing report is on GitHub here.

Overall statistics

  • Number of samples = 13
  • number reads = 145,090,062
  • Yield (Mbases) = 43,525
  • Mean quality scores = 38.00
  • % bases over 30 quality score = 90.00

More detailed statistics

I downloaded the report statistics available on GitHub here as well as the full report and added this data to the sample metadata on GitHub here.

  • All samples had >37 mean quality scores
  • Yeild (Mbases) ranged from ~500-10,000 per sample with an additional 1.6-33 million reads per sample.
  • 89+% bases had quality scores over 30

Here is the summary of the second round of sequencing:

Project Sample ID Barcode Sequence # Reads Yield (Mbases) Mean Quality Score % Bases >= 30
30-943303755 R107 AAGCGACT+CTTCGCCT 17533977 5260 38 90.31
30-943303755 R55 TTCCTCCT+AGGCTATA 2876549 863 38.01 90.43
30-943303755 R56 TTCCTCCT+GCCTCTAT 1661094 498 37.94 90.06
30-943303755 R57 TTCCTCCT+AGGATAGG 3287827 986 38.08 90.73
30-943303755 R58 TTCCTCCT+TCAGAGCC 1373160 412 38.09 90.78
30-943303755 R59 TTCCTCCT+CTTCGCCT 33684113 10105 37.96 90.15
30-943303755 R60 TTCCTCCT+TAAGATTA 2530567 759 38 90.36
30-943303755 R62 TTCCTCCT+GTCAGTAC 2313143 694 38.01 90.39
30-943303755 R67 TGCTTGCT+CTTCGCCT 17430173 5229 37.9 89.84
30-943303755 R75 GGTGATGA+CTTCGCCT 11054008 3316 37.99 90.27
30-943303755 R83 AACCTACG+CTTCGCCT 17612372 5284 37.76 89.18
30-943303755 R91 GGATCTGA+CTTCGCCT 17511498 5253 38.03 90.44
30-943303755 R99 TGATCACG+CTTCGCCT 16221581 4866 37.47 87.83

I then added this data to the sample metadata and generated a column for total reads combined from first and second sequencing.

date sample larvae temperature symbiont parent phenotype code Barcode Sequence # Reads Yield (Mbases) Mean Quality Score % Bases >= 30 ncbi_bioproject ncbi_accession resequenced second_barcode second_reads second_yield second_mean_quality second_bases_30 second_ncbi_bioproject second_ncbi_accession total_reads
20230627 R100 50 33 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_33 TGATCACG+TAAGATTA 34566278 10370 37.79 89.32 PRJNA1078313 SAMN40082680                 34566278
20230627 R101 50 33 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_33 TGATCACG+ACGTCCTG 38457421 11538 37.79 89.29 PRJNA1078313 SAMN40082681                 38457421
20230627 R102 50 33 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_33 TGATCACG+GTCAGTAC 33729404 10119 37.79 89.27 PRJNA1078313 SAMN40082682                 33729404
20230627 R103 50 33 Wildtype Wildtype Wildtype Wildtype_33 AAGCGACT+AGGCTATA 21980396 6594 38.01 90.36 PRJNA1078313 SAMN40082683                 21980396
20230627 R104 50 33 Wildtype Wildtype Wildtype Wildtype_33 AAGCGACT+GCCTCTAT 30634968 9191 37.91 89.86 PRJNA1078313 SAMN40082684                 30634968
20230627 R105 50 33 Wildtype Wildtype Wildtype Wildtype_33 AAGCGACT+AGGATAGG 29434310 8830 37.84 89.51 PRJNA1078313 SAMN40082685                 29434310
20230627 R106 50 33 Wildtype Wildtype Wildtype Wildtype_33 AAGCGACT+TCAGAGCC 34929945 10479 37.94 89.97 PRJNA1078313 SAMN40082686                 34929945
20230627 R107 50 33 Wildtype Wildtype Wildtype Wildtype_33 AAGCGACT+CTTCGCCT 6719567 2016 38.15 90.98 PRJNA1078313 SAMN40082687 yes AAGCGACT+CTTCGCCT 17533977 5260 38 90.31     24253544
20230627 R108 50 33 Wildtype Wildtype Wildtype Wildtype_33 AAGCGACT+TAAGATTA 29304668 8791 37.95 90.04 PRJNA1078313 SAMN40082688                 29304668
20230627 R55 50 27 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_27 TTCCTCCT+AGGCTATA 15818670 4746 37.8 89.36 PRJNA1078313 SAMN40082635 yes TTCCTCCT+AGGCTATA 2876549 863 38.01 90.43     18695219
20230627 R56 50 27 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_27 TTCCTCCT+GCCTCTAT 17457755 5238 37.58 88.32 PRJNA1078313 SAMN40082636 yes TTCCTCCT+GCCTCTAT 1661094 498 37.94 90.06     19118849
20230627 R57 50 27 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_27 TTCCTCCT+AGGATAGG 15232862 4570 37.7 88.88 PRJNA1078313 SAMN40082637 yes TTCCTCCT+AGGATAGG 3287827 986 38.08 90.73     18520689
20230627 R58 50 27 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_27 TTCCTCCT+TCAGAGCC 17987445 5396 37.73 89.03 PRJNA1078313 SAMN40082638 yes TTCCTCCT+TCAGAGCC 1373160 412 38.09 90.78     19360605
20230627 R59 50 27 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_27 TTCCTCCT+CTTCGCCT 6002991 1801 37.96 90.11 PRJNA1078313 SAMN40082639 yes TTCCTCCT+CTTCGCCT 33684113 10105 37.96 90.15     39687104
20230627 R60 50 27 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_27 TTCCTCCT+TAAGATTA 16284649 4885 37.63 88.54 PRJNA1078313 SAMN40082640 yes TTCCTCCT+TAAGATTA 2530567 759 38 90.36     18815216
20230627 R61 50 27 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_27 TTCCTCCT+ACGTCCTG 19891057 5967 37.73 89.05 PRJNA1078313 SAMN40082641                 19891057
20230627 R62 50 27 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_27 TTCCTCCT+GTCAGTAC 16675688 5003 37.64 88.59 PRJNA1078313 SAMN40082642 yes TTCCTCCT+GTCAGTAC 2313143 694 38.01 90.39     18988831
20230627 R63 50 27 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_27 TGCTTGCT+AGGCTATA 23828671 7149 38.01 90.33 PRJNA1078313 SAMN40082643                 23828671
20230627 R64 50 27 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_27 TGCTTGCT+GCCTCTAT 32277087 9683 37.93 89.96 PRJNA1078313 SAMN40082644                 32277087
20230627 R65 50 27 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_27 TGCTTGCT+AGGATAGG 32099169 9630 37.78 89.27 PRJNA1078313 SAMN40082645                 32099169
20230627 R66 50 27 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_27 TGCTTGCT+TCAGAGCC 32272569 9682 37.96 90.08 PRJNA1078313 SAMN40082646                 32272569
20230627 R67 50 27 Wildtype Wildtype Wildtype Wildtype_27 TGCTTGCT+CTTCGCCT 7665773 2300 38.07 90.62 PRJNA1078313 SAMN40082647 yes TGCTTGCT+CTTCGCCT 17430173 5229 37.9 89.84     25095946
20230627 R68 50 27 Wildtype Wildtype Wildtype Wildtype_27 TGCTTGCT+TAAGATTA 30934325 9280 37.92 89.89 PRJNA1078313 SAMN40082648                 30934325
20230627 R69 50 27 Wildtype Wildtype Wildtype Wildtype_27 TGCTTGCT+ACGTCCTG 39517309 11856 37.9 89.77 PRJNA1078313 SAMN40082649                 39517309
20230627 R70 50 27 Wildtype Wildtype Wildtype Wildtype_27 TGCTTGCT+GTCAGTAC 34280767 10284 37.88 89.7 PRJNA1078313 SAMN40082650                 34280767
20230627 R71 50 27 Wildtype Wildtype Wildtype Wildtype_27 GGTGATGA+AGGCTATA 27838736 8352 37.99 90.27 PRJNA1078313 SAMN40082651                 27838736
20230627 R72 50 27 Wildtype Wildtype Wildtype Wildtype_27 GGTGATGA+GCCTCTAT 33950055 10185 37.81 89.34 PRJNA1078313 SAMN40082652                 33950055
20230627 R73 50 30 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_30 GGTGATGA+AGGATAGG 35173243 10552 37.88 89.71 PRJNA1078313 SAMN40082653                 35173243
20230627 R74 50 30 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_30 GGTGATGA+TCAGAGCC 34922263 10476 37.96 90.07 PRJNA1078313 SAMN40082654                 34922263
20230627 R75 50 30 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_30 GGTGATGA+CTTCGCCT 9871112 2961 38.12 90.85 PRJNA1078313 SAMN40082655 yes GGTGATGA+CTTCGCCT 11054008 3316 37.99 90.27     20925120
20230627 R76 50 30 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_30 GGTGATGA+TAAGATTA 33036284 9911 37.95 90.02 PRJNA1078313 SAMN40082656                 33036284
20230627 R77 50 30 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_30 GGTGATGA+ACGTCCTG 39746840 11924 37.98 90.17 PRJNA1078313 SAMN40082657                 39746840
20230627 R78 50 30 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_30 GGTGATGA+GTCAGTAC 35398354 10619 37.86 89.61 PRJNA1078313 SAMN40082658                 35398354
20230627 R79 50 30 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_30 AACCTACG+AGGCTATA 25009225 7502 37.93 89.95 PRJNA1078313 SAMN40082659                 25009225
20230627 R80 50 30 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_30 AACCTACG+GCCTCTAT 36133089 10840 37.85 89.53 PRJNA1078313 SAMN40082660                 36133089
20230627 R81 50 30 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_30 AACCTACG+AGGATAGG 33493354 10048 37.78 89.2 PRJNA1078313 SAMN40082661                 33493354
20230627 R82 50 30 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_30 AACCTACG+TCAGAGCC 35452563 10636 37.92 89.85 PRJNA1078313 SAMN40082662                 35452563
20230627 R83 50 30 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_30 AACCTACG+CTTCGCCT 7497048 2249 38.06 90.57 PRJNA1078313 SAMN40082663 yes AACCTACG+CTTCGCCT 17612372 5284 37.76 89.18     25109420
20230627 R84 50 30 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_30 AACCTACG+TAAGATTA 32220467 9666 37.92 89.86 PRJNA1078313 SAMN40082664                 32220467
20230627 R85 50 30 Wildtype Wildtype Wildtype Wildtype_30 AACCTACG+ACGTCCTG 36878406 11063 37.84 89.46 PRJNA1078313 SAMN40082665                 36878406
20230627 R86 50 30 Wildtype Wildtype Wildtype Wildtype_30 AACCTACG+GTCAGTAC 32691940 9808 37.76 89.14 PRJNA1078313 SAMN40082666                 32691940
20230627 R87 50 30 Wildtype Wildtype Wildtype Wildtype_30 GGATCTGA+AGGCTATA 24408673 7323 38.09 90.72 PRJNA1078313 SAMN40082667                 24408673
20230627 R88 50 30 Wildtype Wildtype Wildtype Wildtype_30 GGATCTGA+GCCTCTAT 30584889 9175 37.85 89.56 PRJNA1078313 SAMN40082668                 30584889
20230627 R89 50 30 Wildtype Wildtype Wildtype Wildtype_30 GGATCTGA+AGGATAGG 33121528 9936 37.87 89.65 PRJNA1078313 SAMN40082669                 33121528
20230627 R90 50 30 Wildtype Wildtype Wildtype Wildtype_30 GGATCTGA+TCAGAGCC 31879658 9564 38.03 90.37 PRJNA1078313 SAMN40082670                 31879658
20230627 R91 50 33 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_33 GGATCTGA+CTTCGCCT 6934253 2080 38.01 90.36 PRJNA1078313 SAMN40082671 yes GGATCTGA+CTTCGCCT 17511498 5253 38.03 90.44     24445751
20230627 R92 50 33 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_33 GGATCTGA+TAAGATTA 28565956 8570 37.93 89.93 PRJNA1078313 SAMN40082672                 28565956
20230627 R93 50 33 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_33 GGATCTGA+ACGTCCTG 31620062 9486 38.02 90.37 PRJNA1078313 SAMN40082673                 31620062
20230627 R94 50 33 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_33 GGATCTGA+GTCAGTAC 32531274 9759 37.87 89.62 PRJNA1078313 SAMN40082674                 32531274
20230627 R95 50 33 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_33 TGATCACG+AGGCTATA 27375934 8213 37.92 89.92 PRJNA1078313 SAMN40082675                 27375934
20230627 R96 50 33 Cladocopium Bleached Bleached_Cladocopium Bleached_Cladocopium_33 TGATCACG+GCCTCTAT 35882529 10765 37.78 89.22 PRJNA1078313 SAMN40082676                 35882529
20230627 R97 50 33 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_33 TGATCACG+AGGATAGG 33376891 10013 37.77 89.17 PRJNA1078313 SAMN40082677                 33376891
20230627 R98 50 33 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_33 TGATCACG+TCAGAGCC 35899983 10770 37.86 89.63 PRJNA1078313 SAMN40082678                 35899983
20230627 R99 50 33 Mixed Nonbleached Nonbleached_Mixed Nonbleached_Mixed_33 TGATCACG+CTTCGCCT 8420607 2526 37.83 89.57 PRJNA1078313 SAMN40082679 yes TGATCACG+CTTCGCCT 16221581 4866 37.47 87.83     24642188

All samples now have >18 M reads ranging from ~18M to ~35M. This is great! It increased read depth for the samples that previously had <12M reads.

Download sequences to URI server

Prepare folders in Andromeda directory.

#logged into Andromeda 
cd /data/putnamlab/ashuffmyer
cd mcap-2023-rnaseq
cd raw-sequences
mkdir second_sequencing

Now the directory that I want sequences in is /data/putnamlab/ashuffmyer/mcap-2023-rnaseq/raw-sequences/second_sequencing.

# in andromeda second_sequencing folder 

pwd 
/data/putnamlab/ashuffmyer/mcap-2023-rnaseq/raw-sequences/second_sequencing

# log into Azenta sftp while logged into Andromeda as directed by Azenta and navigate to sequence folder 00_fastq

#set directory for download
lcd /data/putnamlab/ashuffmyer/mcap-2023-rnaseq/raw-sequences/second_sequencing

#download all files in sequence folder 
mget *

Downloaded to URI Andromeda on April 12 2024.

I then checked for data integrity using md5 checksums.

md5sum *.fastq.gz > checkmd5_20240412.md5
md5sum -c checkmd5_20240412.md5

Output was as follows:

R107_R1_001.fastq.gz: OK
R107_R2_001.fastq.gz: OK
R55_R1_001.fastq.gz: OK
R55_R2_001.fastq.gz: OK
R56_R1_001.fastq.gz: OK
R56_R2_001.fastq.gz: OK
R57_R1_001.fastq.gz: OK
R57_R2_001.fastq.gz: OK
R58_R1_001.fastq.gz: OK
R58_R2_001.fastq.gz: OK
R59_R1_001.fastq.gz: OK
R59_R2_001.fastq.gz: OK
R60_R1_001.fastq.gz: OK
R60_R2_001.fastq.gz: OK
R62_R1_001.fastq.gz: OK
R62_R2_001.fastq.gz: OK
R67_R1_001.fastq.gz: OK
R67_R2_001.fastq.gz: OK
R75_R1_001.fastq.gz: OK
R75_R2_001.fastq.gz: OK
R83_R1_001.fastq.gz: OK
R83_R2_001.fastq.gz: OK
R91_R1_001.fastq.gz: OK
R91_R2_001.fastq.gz: OK
R99_R1_001.fastq.gz: OK
R99_R2_001.fastq.gz: OK

Azenta provided a .md5 file for each sequence file. I then compared generated checksums to these original files to confirm data integrity and content is the same after the transfer from Azenta.

#bind together all .md5 files provided by Azenta 

cat *.gz.md5 > azenta_original_checksums_second.md5

This provided the following list of the original checksums:

less azenta_original_checksums_second.md5

6ee514bdc1bacfb591629a3edf82bcd4  ./R107_R1_001.fastq.gz
3d6b00afc053f2eb770f83c5830f699e  ./R107_R2_001.fastq.gz
16aba2b715ceeb2c2f3a79dbc855e768  ./R55_R1_001.fastq.gz
14e32d9fccd55fd81a3468a4fd5766d1  ./R55_R2_001.fastq.gz
7fbb16f6f920e4a58431cd91e14b912b  ./R56_R1_001.fastq.gz
80bd51fd98400da3fb91b1182252f577  ./R56_R2_001.fastq.gz
aa6b3bd9617c10ca9b504309cc1ff047  ./R57_R1_001.fastq.gz
c52e1d5d9c7caa2189eaedf81944dfc7  ./R57_R2_001.fastq.gz
027601dabbfc6e48829efe5b931e6e05  ./R58_R1_001.fastq.gz
b1e2605ec7c35ad3c25ad7ab03cb4d2f  ./R58_R2_001.fastq.gz
a62cfd57273efefcfc4076e66cb5da1c  ./R59_R1_001.fastq.gz
dfa3021694fd5ddc01c387eafe34a0d9  ./R59_R2_001.fastq.gz
ba4c0c4c8dede34d546ee7ec5293553b  ./R60_R1_001.fastq.gz
dbf68528a9ee3428d378275c83458b24  ./R60_R2_001.fastq.gz
9ae8dc138d0df94197388b9da117f658  ./R62_R1_001.fastq.gz
96e1b11cb6e60415dc6f69fb4849651e  ./R62_R2_001.fastq.gz
0d2b1896bf85c0800a3a3482f34c90ca  ./R67_R1_001.fastq.gz
cbb14c976024dfe72a7561415284c41a  ./R67_R2_001.fastq.gz
f16d7330659ba6e310ade50cdae10b8c  ./R75_R1_001.fastq.gz
9b9ab52837950fdd8108d22e29f9bc31  ./R75_R2_001.fastq.gz
429bf4b34de618d97ec2213e658477c2  ./R83_R1_001.fastq.gz
77cf8a4c7d2db0bf83280df1254b335a  ./R83_R2_001.fastq.gz
86064e95efa1d802371fbda68d2be0ca  ./R91_R1_001.fastq.gz
3e24c0fdad691020cd1140e3a90bea3f  ./R91_R2_001.fastq.gz
c117e340bd9bef1bc295b6e86f6bfcbb  ./R99_R1_001.fastq.gz
0ebb0438dde06d989cfd79a5616ef9a3  ./R99_R2_001.fastq.gz

Then, here is the md5 checksum of the downloaded data on Andromeda:

less checkmd5_20240412.md5

6ee514bdc1bacfb591629a3edf82bcd4  R107_R1_001.fastq.gz
3d6b00afc053f2eb770f83c5830f699e  R107_R2_001.fastq.gz
16aba2b715ceeb2c2f3a79dbc855e768  R55_R1_001.fastq.gz
14e32d9fccd55fd81a3468a4fd5766d1  R55_R2_001.fastq.gz
7fbb16f6f920e4a58431cd91e14b912b  R56_R1_001.fastq.gz
80bd51fd98400da3fb91b1182252f577  R56_R2_001.fastq.gz
aa6b3bd9617c10ca9b504309cc1ff047  R57_R1_001.fastq.gz
c52e1d5d9c7caa2189eaedf81944dfc7  R57_R2_001.fastq.gz
027601dabbfc6e48829efe5b931e6e05  R58_R1_001.fastq.gz
b1e2605ec7c35ad3c25ad7ab03cb4d2f  R58_R2_001.fastq.gz
a62cfd57273efefcfc4076e66cb5da1c  R59_R1_001.fastq.gz
dfa3021694fd5ddc01c387eafe34a0d9  R59_R2_001.fastq.gz
ba4c0c4c8dede34d546ee7ec5293553b  R60_R1_001.fastq.gz
dbf68528a9ee3428d378275c83458b24  R60_R2_001.fastq.gz
9ae8dc138d0df94197388b9da117f658  R62_R1_001.fastq.gz
96e1b11cb6e60415dc6f69fb4849651e  R62_R2_001.fastq.gz
0d2b1896bf85c0800a3a3482f34c90ca  R67_R1_001.fastq.gz
cbb14c976024dfe72a7561415284c41a  R67_R2_001.fastq.gz
f16d7330659ba6e310ade50cdae10b8c  R75_R1_001.fastq.gz
9b9ab52837950fdd8108d22e29f9bc31  R75_R2_001.fastq.gz
429bf4b34de618d97ec2213e658477c2  R83_R1_001.fastq.gz
77cf8a4c7d2db0bf83280df1254b335a  R83_R2_001.fastq.gz
86064e95efa1d802371fbda68d2be0ca  R91_R1_001.fastq.gz
3e24c0fdad691020cd1140e3a90bea3f  R91_R2_001.fastq.gz
c117e340bd9bef1bc295b6e86f6bfcbb  R99_R1_001.fastq.gz
0ebb0438dde06d989cfd79a5616ef9a3  R99_R2_001.fastq.gz

I then added these lists to a spreadsheet and checked that the cells matched for original and downloaded files. The file is on GitHub here.

I also added in the checksums for data that I downloaded to Mox (detailed below). All files are confirmed and everything looks good!

file original_azenta downloaded_andromeda downloaded_mox match_andromeda match_mox
R107_R1_001.fastq.gz 6ee514bdc1bacfb591629a3edf82bcd4 6ee514bdc1bacfb591629a3edf82bcd4 6ee514bdc1bacfb591629a3edf82bcd4 TRUE TRUE
R107_R2_001.fastq.gz 3d6b00afc053f2eb770f83c5830f699e 3d6b00afc053f2eb770f83c5830f699e 3d6b00afc053f2eb770f83c5830f699e TRUE TRUE
R55_R1_001.fastq.gz 16aba2b715ceeb2c2f3a79dbc855e768 16aba2b715ceeb2c2f3a79dbc855e768 16aba2b715ceeb2c2f3a79dbc855e768 TRUE TRUE
R55_R2_001.fastq.gz 14e32d9fccd55fd81a3468a4fd5766d1 14e32d9fccd55fd81a3468a4fd5766d1 14e32d9fccd55fd81a3468a4fd5766d1 TRUE TRUE
R56_R1_001.fastq.gz 7fbb16f6f920e4a58431cd91e14b912b 7fbb16f6f920e4a58431cd91e14b912b 7fbb16f6f920e4a58431cd91e14b912b TRUE TRUE
R56_R2_001.fastq.gz 80bd51fd98400da3fb91b1182252f577 80bd51fd98400da3fb91b1182252f577 80bd51fd98400da3fb91b1182252f577 TRUE TRUE
R57_R1_001.fastq.gz aa6b3bd9617c10ca9b504309cc1ff047 aa6b3bd9617c10ca9b504309cc1ff047 aa6b3bd9617c10ca9b504309cc1ff047 TRUE TRUE
R57_R2_001.fastq.gz c52e1d5d9c7caa2189eaedf81944dfc7 c52e1d5d9c7caa2189eaedf81944dfc7 c52e1d5d9c7caa2189eaedf81944dfc7 TRUE TRUE
R58_R1_001.fastq.gz 027601dabbfc6e48829efe5b931e6e05 027601dabbfc6e48829efe5b931e6e05 027601dabbfc6e48829efe5b931e6e05 TRUE TRUE
R58_R2_001.fastq.gz b1e2605ec7c35ad3c25ad7ab03cb4d2f b1e2605ec7c35ad3c25ad7ab03cb4d2f b1e2605ec7c35ad3c25ad7ab03cb4d2f TRUE TRUE
R59_R1_001.fastq.gz a62cfd57273efefcfc4076e66cb5da1c a62cfd57273efefcfc4076e66cb5da1c a62cfd57273efefcfc4076e66cb5da1c TRUE TRUE
R59_R2_001.fastq.gz dfa3021694fd5ddc01c387eafe34a0d9 dfa3021694fd5ddc01c387eafe34a0d9 dfa3021694fd5ddc01c387eafe34a0d9 TRUE TRUE
R60_R1_001.fastq.gz ba4c0c4c8dede34d546ee7ec5293553b ba4c0c4c8dede34d546ee7ec5293553b ba4c0c4c8dede34d546ee7ec5293553b TRUE TRUE
R60_R2_001.fastq.gz dbf68528a9ee3428d378275c83458b24 dbf68528a9ee3428d378275c83458b24 dbf68528a9ee3428d378275c83458b24 TRUE TRUE
R62_R1_001.fastq.gz 9ae8dc138d0df94197388b9da117f658 9ae8dc138d0df94197388b9da117f658 9ae8dc138d0df94197388b9da117f658 TRUE TRUE
R62_R2_001.fastq.gz 96e1b11cb6e60415dc6f69fb4849651e 96e1b11cb6e60415dc6f69fb4849651e 96e1b11cb6e60415dc6f69fb4849651e TRUE TRUE
R67_R1_001.fastq.gz 0d2b1896bf85c0800a3a3482f34c90ca 0d2b1896bf85c0800a3a3482f34c90ca 0d2b1896bf85c0800a3a3482f34c90ca TRUE TRUE
R67_R2_001.fastq.gz cbb14c976024dfe72a7561415284c41a cbb14c976024dfe72a7561415284c41a cbb14c976024dfe72a7561415284c41a TRUE TRUE
R75_R1_001.fastq.gz f16d7330659ba6e310ade50cdae10b8c f16d7330659ba6e310ade50cdae10b8c f16d7330659ba6e310ade50cdae10b8c TRUE TRUE
R75_R2_001.fastq.gz 9b9ab52837950fdd8108d22e29f9bc31 9b9ab52837950fdd8108d22e29f9bc31 9b9ab52837950fdd8108d22e29f9bc31 TRUE TRUE
R83_R1_001.fastq.gz 429bf4b34de618d97ec2213e658477c2 429bf4b34de618d97ec2213e658477c2 429bf4b34de618d97ec2213e658477c2 TRUE TRUE
R83_R2_001.fastq.gz 77cf8a4c7d2db0bf83280df1254b335a 77cf8a4c7d2db0bf83280df1254b335a 77cf8a4c7d2db0bf83280df1254b335a TRUE TRUE
R91_R1_001.fastq.gz 86064e95efa1d802371fbda68d2be0ca 86064e95efa1d802371fbda68d2be0ca 86064e95efa1d802371fbda68d2be0ca TRUE TRUE
R91_R2_001.fastq.gz 3e24c0fdad691020cd1140e3a90bea3f 3e24c0fdad691020cd1140e3a90bea3f 3e24c0fdad691020cd1140e3a90bea3f TRUE TRUE
R99_R1_001.fastq.gz c117e340bd9bef1bc295b6e86f6bfcbb c117e340bd9bef1bc295b6e86f6bfcbb c117e340bd9bef1bc295b6e86f6bfcbb TRUE TRUE
R99_R2_001.fastq.gz 0ebb0438dde06d989cfd79a5616ef9a3 0ebb0438dde06d989cfd79a5616ef9a3 0ebb0438dde06d989cfd79a5616ef9a3 TRUE TRUE

Data are now downloaded and integrity confirmed on URI Andromeda.

Download data to UW Hyak/Mox

#logged into UW Hyak/Mox
cd /gscratch/srlab/ashuff/mcap-2023-rnaseq
mkdir second_sequencing
cd second_sequencing

The full directory where I want raw sequences to go is /gscratch/srlab/ashuff/mcap-2023-rnaseq/second_sequencing .

# in Hyak ashuffm folder 

# log into Azenta sftp as directed by Azenta 
# cd into my project folder

#set directory for download
lcd /gscratch/srlab/ashuff/mcap-2023-rnaseq/second_sequencing

#download all files into project folder 

mget *

Downloaded on 13 April 2024.

I then checked for data integrity using md5 checksums. Azenta provided a .md5 file for each sequence file. See the table above for confirmation of md5 checksums.

srun -p srlab -A srlab --time=1:00:00 --mem=100G --pty /bin/bash

md5sum *.fastq.gz > checkmd5_20240413.md5

md5sum -c checkmd5_20240413.md5

Check sums from data downloaded on Mox is here:

less checkmd5_20240413.md5

6ee514bdc1bacfb591629a3edf82bcd4  R107_R1_001.fastq.gz
3d6b00afc053f2eb770f83c5830f699e  R107_R2_001.fastq.gz
16aba2b715ceeb2c2f3a79dbc855e768  R55_R1_001.fastq.gz
14e32d9fccd55fd81a3468a4fd5766d1  R55_R2_001.fastq.gz
7fbb16f6f920e4a58431cd91e14b912b  R56_R1_001.fastq.gz
80bd51fd98400da3fb91b1182252f577  R56_R2_001.fastq.gz
aa6b3bd9617c10ca9b504309cc1ff047  R57_R1_001.fastq.gz
c52e1d5d9c7caa2189eaedf81944dfc7  R57_R2_001.fastq.gz
027601dabbfc6e48829efe5b931e6e05  R58_R1_001.fastq.gz
b1e2605ec7c35ad3c25ad7ab03cb4d2f  R58_R2_001.fastq.gz
a62cfd57273efefcfc4076e66cb5da1c  R59_R1_001.fastq.gz
dfa3021694fd5ddc01c387eafe34a0d9  R59_R2_001.fastq.gz
ba4c0c4c8dede34d546ee7ec5293553b  R60_R1_001.fastq.gz
dbf68528a9ee3428d378275c83458b24  R60_R2_001.fastq.gz
9ae8dc138d0df94197388b9da117f658  R62_R1_001.fastq.gz
96e1b11cb6e60415dc6f69fb4849651e  R62_R2_001.fastq.gz
0d2b1896bf85c0800a3a3482f34c90ca  R67_R1_001.fastq.gz
cbb14c976024dfe72a7561415284c41a  R67_R2_001.fastq.gz
f16d7330659ba6e310ade50cdae10b8c  R75_R1_001.fastq.gz
9b9ab52837950fdd8108d22e29f9bc31  R75_R2_001.fastq.gz
429bf4b34de618d97ec2213e658477c2  R83_R1_001.fastq.gz
77cf8a4c7d2db0bf83280df1254b335a  R83_R2_001.fastq.gz
86064e95efa1d802371fbda68d2be0ca  R91_R1_001.fastq.gz
3e24c0fdad691020cd1140e3a90bea3f  R91_R2_001.fastq.gz
c117e340bd9bef1bc295b6e86f6bfcbb  R99_R1_001.fastq.gz
0ebb0438dde06d989cfd79a5616ef9a3  R99_R2_001.fastq.gz

Output from checksums is here:

R107_R1_001.fastq.gz: OK
R107_R2_001.fastq.gz: OK
R55_R1_001.fastq.gz: OK
R55_R2_001.fastq.gz: OK
R56_R1_001.fastq.gz: OK
R56_R2_001.fastq.gz: OK
R57_R1_001.fastq.gz: OK
R57_R2_001.fastq.gz: OK
R58_R1_001.fastq.gz: OK
R58_R2_001.fastq.gz: OK
R59_R1_001.fastq.gz: OK
R59_R2_001.fastq.gz: OK
R60_R1_001.fastq.gz: OK
R60_R2_001.fastq.gz: OK
R62_R1_001.fastq.gz: OK
R62_R2_001.fastq.gz: OK
R67_R1_001.fastq.gz: OK
R67_R2_001.fastq.gz: OK
R75_R1_001.fastq.gz: OK
R75_R2_001.fastq.gz: OK
R83_R1_001.fastq.gz: OK
R83_R2_001.fastq.gz: OK
R91_R1_001.fastq.gz: OK
R91_R2_001.fastq.gz: OK
R99_R1_001.fastq.gz: OK
R99_R2_001.fastq.gz: OK

Everything looks good and all data files were transferred correctly.

Files are now stored on both URI and UW servers.

2. Rename files to indicate they are from the second sequencing

Add an “s” after the sample ID to indicate that samples are from the second round of sequencing, so that they can be uploaded to NCBI and will remain distinct from first round of sequencing.

I am performing this in Andromeda, becuase this is where I am going to conduct analyses and upload to NCBI.

/data/putnamlab/ashuffmyer/mcap-2023-rnaseq/raw-sequences/second_sequencing 

for file in *; do
    # Check if the file name contains ".gz" and an underscore
    if [[ $file == *".gz"* && $file == *_* ]]; then
        # Extract the part of the file name before the first underscore
        prefix="${file%%_*}"
        # Extract the part of the file name after the first underscore
        suffix="${file#*_}"
        # Rename the file by adding "s" after the prefix
        mv "$file" "${prefix}s_$suffix"
        echo "Renamed: $file to ${prefix}s_$suffix"
    fi
done

This changed the files to the following names:

azenta_original_checksums_second.md5  R60s_R1_001.fastq.gz.md5
checkmd5_20240412.md5                 R60s_R2_001.fastq.gz
md5_files                             R60s_R2_001.fastq.gz.md5
R107s_R1_001.fastq.gz                 R62s_R1_001.fastq.gz
R107s_R1_001.fastq.gz.md5             R62s_R1_001.fastq.gz.md5
R107s_R2_001.fastq.gz                 R62s_R2_001.fastq.gz
R107s_R2_001.fastq.gz.md5             R62s_R2_001.fastq.gz.md5
R55s_R1_001.fastq.gz                  R67s_R1_001.fastq.gz
R55s_R1_001.fastq.gz.md5              R67s_R1_001.fastq.gz.md5
R55s_R2_001.fastq.gz                  R67s_R2_001.fastq.gz
R55s_R2_001.fastq.gz.md5              R67s_R2_001.fastq.gz.md5
R56s_R1_001.fastq.gz                  R75s_R1_001.fastq.gz
R56s_R1_001.fastq.gz.md5              R75s_R1_001.fastq.gz.md5
R56s_R2_001.fastq.gz                  R75s_R2_001.fastq.gz
R56s_R2_001.fastq.gz.md5              R75s_R2_001.fastq.gz.md5
R57s_R1_001.fastq.gz                  R83s_R1_001.fastq.gz
R57s_R1_001.fastq.gz.md5              R83s_R1_001.fastq.gz.md5
R57s_R2_001.fastq.gz                  R83s_R2_001.fastq.gz
R57s_R2_001.fastq.gz.md5              R83s_R2_001.fastq.gz.md5
R58s_R1_001.fastq.gz                  R91s_R1_001.fastq.gz
R58s_R1_001.fastq.gz.md5              R91s_R1_001.fastq.gz.md5
R58s_R2_001.fastq.gz                  R91s_R2_001.fastq.gz
R58s_R2_001.fastq.gz.md5              R91s_R2_001.fastq.gz.md5
R59s_R1_001.fastq.gz                  R99s_R1_001.fastq.gz
R59s_R1_001.fastq.gz.md5              R99s_R1_001.fastq.gz.md5
R59s_R2_001.fastq.gz                  R99s_R2_001.fastq.gz
R59s_R2_001.fastq.gz.md5              R99s_R2_001.fastq.gz.md5
R60s_R1_001.fastq.gz                  raw_fastqc

The files that were sequenced in the second round now contain “s” after the sample name.

3. Upload to NCBI project

Project ID: PRJNA1078313

I used the same information on uploading for this project detailed in my previous post and the Putnam Lab SRA protocol..

The sample metadata can be found on GitHub here using the MIMS.me.host-associated template here and sequencing information and metadata is located on GitHub here.

I will upload these files as a new SRA submission and link them to the existing bioproject and biosamples.

I started a new SRA submission process and entered the BioProject number PRJNA1078313. I added a release date of March 1 2025.

I created a new SRA metadata sheet for the samples that are being uploaded in this upload. I added the description “Standard mRNA-seq from libraries prepared using Zymo Quick MiniPrep Plus DNA/RNA extraction kit at the Putnam Lab (University of Rhode Island) with sequencing at Azenta Life Sciences. Additional top off sequencing performed by Azenta Life Sciences with additional sequencing files denoted with “s” following sample name prefix.”.

The metadata sheet for these files can be found on GitHub here.

Transfer data from URI server to NCBI SRA

I next followed FTP instructions to upload top off sequencing files.

First, log onto Andromeda, make a folder for this upload, and symlink all files.

cd /data/putnamlab/ashuffmyer/mcap-2023-rnaseq/ncbi_upload
mkdir 20240416_upload
cd 20240416_upload

ln -s /data/putnamlab/ashuffmyer/mcap-2023-rnaseq/raw-sequences/second_sequencing/*gz /data/putnamlab/ashuffmyer/mcap-2023-rnaseq/ncbi_upload/20240416_upload

Next, upload files using FTP instructions.

cd /data/putnamlab/ashuffmyer/mcap-2023-rnaseq/ncbi_upload/20240416_upload

ftp -i 

open ftp-private.ncbi.nlm.nih.gov

#enter name and password given on SRA webpage

cd uploads/ashuffmyer_gmail.com_bsKvx0RY

mkdir mcap-2023-rnaseq-upload-20240416

cd mcap-2023-rnaseq-upload-20240416

mput *

The upload to SRA will proceed for each file with messages “transfer complete” when each is uploaded. Keep computer active until all uploads are finished.

Files successfully uploaded.

Continue with the submission by selecting the preload folder on SRA once all 26 files registered.

RNA-Seq sequence files were submitted under SRA SUB14381642.

All information added to the Putnam Lab sequence inventory here.

Written on April 12, 2024