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new mode 100644
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diff --git a/docs/references.md b/docs/references.md
index 54b83b5ebe5fe38f0f6d4b38fee4279f9af5898c..3aa5e67f4b5a5bf680fe88e2f4e5d8e2a4b67f62 100644
--- a/docs/references.md
+++ b/docs/references.md
@@ -4,28 +4,28 @@
* Anaconda (Anaconda Software Distribution, [https://anaconda.com](https://anaconda.com))
2. **DERIVA**:
- * Bugacov, A., Czajkowski, K., Kesselman, C., Kumar, A., Schuler, R. E. and Tangmunarunkit, H. 2017 Experiences with DERIVA: An Asset Management Platform for Accelerating eScience. IEEE 13th International Conference on e-Science (e-Science), Auckland, 2017, pp. 79-88, doi:[10.1109/eScience.2017.20](https://doi.org/10.1109/eScience.2017.20).
+ * Bugacov, A., Czajkowski, K., Kesselman, C., Kumar, A., Schuler, R. E., & Tangmunarunkit, H. (2017, October). Experiences with DERIVA: An asset management platform for accelerating eScience. In 2017 IEEE 13th International Conference on e-Science (e-Science) (pp. 79-88). IEEE. doi:[10.1109/eScience.2017.20](https://doi.org/10.1109/eScience.2017.20).
3. **BDBag**:
- * D'Arcy, M., Chard, K., Foster, I., Kesselman, C., Madduri, R., Saint, N., & Wagner, R.. 2019. Big Data Bags: A Scalable Packaging Format for Science. Zenodo. doi:[10.5281/zenodo.3338725](http://doi.org/10.5281/zenodo.3338725).
+ * Madduri, R., Chard, K., DÂ’Arcy, M., Jung, S. C., Rodriguez, A., Sulakhe, D., ... & Foster, I. (2019). Reproducible big data science: A case study in continuous FAIRness. PloS one, 14(4), e0213013. doi:[10.1371/journal.pone.0213013](https://doi.org/10.1371/journal.pone.0213013).
4. **trimgalore**:
* trimgalore [https://github.com/FelixKrueger/TrimGalore](https://github.com/FelixKrueger/TrimGalore)
5. **hisat2**:
- * Kim ,D.,Paggi, J.M., Park, C., Bennett, C., Salzberg, S.L. 2019 Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. Aug;37(8):907-915. doi:[10.1038/s41587-019-0201-4](https://doi.org/10.1038/s41587-019-0201-4).
+ * Kim, D., Paggi, J. M., Park, C., Bennett, C., & Salzberg, S. L. (2019). Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nature biotechnology, 37(8), 907-915. doi:[10.1038/s41587-019-0201-4](https://doi.org/10.1038/s41587-019-0201-4).
6. **samtools**:
- * Li H., B. Handsaker, A. Wysoker, T. Fennell, J. Ruan, N. Homer, G. Marth, G. Abecasis, R. Durbin, and 1000 Genome Project Data Processing Subgroup. 2009. The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics 25: 2078-9. doi:[10.1093/bioinformatics/btp352](http://dx.doi.org/10.1093/bioinformatics/btp352)
+ * Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., ... & Durbin, R. (2009). The sequence alignment/map format and SAMtools. Bioinformatics, 25(16), 2078-2079. doi:[10.1093/bioinformatics/btp352](http://dx.doi.org/10.1093/bioinformatics/btp352)
7. **picard**:
* “Picard Toolkit.†2019. Broad Institute, GitHub Repository. [http://broadinstitute.github.io/picard/](http://broadinstitute.github.io/picard/); Broad Institute
8. **featureCounts**:
- * Liao, Y., Smyth, G.K., Shi, W. 2014 featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. Apr 1;30(7):923-30. doi:[10.1093/bioinformatics/btt656](https://doi.org/10.1093/bioinformatics/btt656).
+ * Liao, Y., Smyth, G. K., & Shi, W. (2014). featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics, 30(7), 923-930. doi:[10.1093/bioinformatics/btt656](https://doi.org/10.1093/bioinformatics/btt656).
9. **deeptools**:
- * RamÃrez, F., D. P. Ryan, B. Grüning, V. Bhardwaj, F. Kilpert, A. S. Richter, S. Heyne, F. Dündar, and T. Manke. 2016. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Research 44: W160-165. doi:[10.1093/nar/gkw257](http://dx.doi.org/10.1093/nar/gkw257)
+ * RamÃrez, F., Ryan, D. P., Grüning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., ... & Manke, T. (2016). deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic acids research, 44(W1), W160-W165. doi:[10.1093/nar/gkw257](http://dx.doi.org/10.1093/nar/gkw257)
10. **Seqtk**:
* Seqtk [https://github.com/lh3/seqtk](https://github.com/lh3/seqtk)
@@ -37,13 +37,13 @@
* FastQC [https://www.bioinformatics.babraham.ac.uk/projects/fastqc/](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
13. **SeqWho**
- * SeqWho [https://git.biohpc.swmed.edu/s181649/seqwho](https://git.biohpc.swmed.edu/s181649/seqwho)
+ * Bennett, C., Thornton, M., Park, C., Henry, G., Zhang, Y., Malladi, V. S., & Kim, D. (2021). SeqWho: Reliable, rapid determination of sequence file identity using k-mer frequencies. bioRxiv, 2021.2003.2010.434827. doi:[10.1101/2021.03.10.434827](https://doi.org/10.1101/2021.03.10.434827)
14. **RSeQC**:
* Wang, L., Wang, S., Li, W. 2012 RSeQC: quality control of RNA-seq experiments. Bioinformatics. Aug 15;28(16):2184-5. doi:[10.1093/bioinformatics/bts356](https://doi.org/10.1093/bioinformatics/bts356).
15. **MultiQC**:
- * Ewels P., Magnusson M., Lundin S. and Käller M. 2016. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32(19): 3047–3048. doi:[10.1093/bioinformatics/btw354](https://dx.doi.org/10.1093/bioinformatics/btw354)
+ * Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics, 32(19), 3047-3048. doi:[10.1093/bioinformatics/btw354](https://dx.doi.org/10.1093/bioinformatics/btw354)
16. **Nextflow**:
- * Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., and Notredame, C. 2017. Nextflow enables reproducible computational workflows. Nature biotechnology, 35(4), 316.
\ No newline at end of file
+ * Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature biotechnology, 35(4), 316-319.
\ No newline at end of file
diff --git a/docs/software_references_mqc.yaml b/docs/software_references_mqc.yaml
index 4d2164ac1da4196d4bb29b9add8bc839ef7eaec9..825f21fc153d952ebe7b654936f8eb9af76ae302 100644
--- a/docs/software_references_mqc.yaml
+++ b/docs/software_references_mqc.yaml
@@ -16,14 +16,14 @@
<li><strong>DERIVA</strong>:</li>
</ol>
<ul>
- <li>Bugacov, A., Czajkowski, K., Kesselman, C., Kumar, A., Schuler, R. E. and Tangmunarunkit, H. 2017 Experiences with DERIVA: An Asset Management Platform for Accelerating eScience. IEEE 13th International Conference on e-Science (e-Science), Auckland, 2017, pp. 79-88, doi:<a href="https://doi.org/10.1109/eScience.2017.20">10.1109/eScience.2017.20</a>.</li>
+ <li>Bugacov, A., Czajkowski, K., Kesselman, C., Kumar, A., Schuler, R. E., & Tangmunarunkit, H. (2017, October). Experiences with DERIVA: An asset management platform for accelerating eScience. In 2017 IEEE 13th International Conference on e-Science (e-Science) (pp. 79-88). IEEE. doi:<a href="https://doi.org/10.1109/eScience.2017.20">10.1109/eScience.2017.20</a>.</li>
</ul>
<ol start="3" style="list-style-type: decimal">
<li><strong>BDBag</strong>:<br />
</li>
</ol>
<ul>
- <li>D'Arcy, M., Chard, K., Foster, I., Kesselman, C., Madduri, R., Saint, N., & Wagner, R.. 2019. Big Data Bags: A Scalable Packaging Format for Science. Zenodo. doi:<a href="http://doi.org/10.5281/zenodo.3338725">10.5281/zenodo.3338725</a>.</li>
+ <li>Madduri, R., Chard, K., DÂ’Arcy, M., Jung, S. C., Rodriguez, A., Sulakhe, D., ... & Foster, I. (2019). Reproducible big data science: A case study in continuous FAIRness. PloS one, 14(4), e0213013. doi:<a href="https://doi.org/10.1371/journal.pone.0213013">10.1371/journal.pone.0213013</a>.</li>
</ul>
<ol start="4" style="list-style-type: decimal">
<li><strong>trimgalore</strong>:</li>
@@ -35,13 +35,13 @@
<li><strong>hisat2</strong>:</li>
</ol>
<ul>
- <li>Kim ,D.,Paggi, J.M., Park, C., Bennett, C., Salzberg, S.L. 2019 Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. Aug;37(8):907-915. doi:<a href="https://doi.org/10.1038/s41587-019-0201-4">10.1038/s41587-019-0201-4</a>.</li>
+ <li>Kim, D., Paggi, J. M., Park, C., Bennett, C., & Salzberg, S. L. (2019). Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nature biotechnology, 37(8), 907-915. doi:<a href="https://doi.org/10.1038/s41587-019-0201-4">10.1038/s41587-019-0201-4</a>.</li>
</ul>
<ol start="6" style="list-style-type: decimal">
<li><strong>samtools</strong>:</li>
</ol>
<ul>
- <li>Li H., B. Handsaker, A. Wysoker, T. Fennell, J. Ruan, N. Homer, G. Marth, G. Abecasis, R. Durbin, and 1000 Genome Project Data Processing Subgroup. 2009. The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics 25: 2078-9. doi:<a href="http://dx.doi.org/10.1093/bioinformatics/btp352">10.1093/bioinformatics/btp352</a></li>
+ <li>Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., ... & Durbin, R. (2009). The sequence alignment/map format and SAMtools. Bioinformatics, 25(16), 2078-2079. doi:<a href="http://dx.doi.org/10.1093/bioinformatics/btp352">10.1093/bioinformatics/btp352</a></li>
</ul>
<ol start="7" style="list-style-type: decimal">
<li><strong>picard</strong>:</li>
@@ -53,13 +53,13 @@
<li><strong>featureCounts</strong>:</li>
</ol>
<ul>
- <li>Liao, Y., Smyth, G.K., Shi, W. 2014 featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. Apr 1;30(7):923-30. doi:<a href="https://doi.org/10.1093/bioinformatics/btt656">10.1093/bioinformatics/btt656</a>.</li>
+ <li>Liao, Y., Smyth, G. K., & Shi, W. (2014). featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics, 30(7), 923-930. doi:<a href="https://doi.org/10.1093/bioinformatics/btt656">10.1093/bioinformatics/btt656</a>.</li>
</ul>
<ol start="9" style="list-style-type: decimal">
<li><strong>deeptools</strong>:</li>
</ol>
<ul>
- <li>RamÃrez, F., D. P. Ryan, B. Grüning, V. Bhardwaj, F. Kilpert, A. S. Richter, S. Heyne, F. Dündar, and T. Manke. 2016. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Research 44: W160-165. doi:<a href="http://dx.doi.org/10.1093/nar/gkw257">10.1093/nar/gkw257</a></li>
+ <li>RamÃrez, F., Ryan, D. P., Grüning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., ... & Manke, T. (2016). deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic acids research, 44(W1), W160-W165. doi:<a href="http://dx.doi.org/10.1093/nar/gkw257">10.1093/nar/gkw257</a></li>
</ul>
<ol start="10" style="list-style-type: decimal">
<li><strong>Seqtk</strong>:</li>
@@ -83,7 +83,7 @@
<li><strong>SeqWho</strong></li>
</ol>
<ul>
- <li>SeqWho <a href="https://git.biohpc.swmed.edu/s181649/seqwho" class="uri">https://git.biohpc.swmed.edu/s181649/seqwho</a></li>
+ <li>Bennett, C., Thornton, M., Park, C., Henry, G., Zhang, Y., Malladi, V. S., & Kim, D. (2021). SeqWho: Reliable, rapid determination of sequence file identity using k-mer frequencies. bioRxiv, 2021.2003.2010.434827. doi:<a href="https://doi.org/10.1101/2021.03.10.434827">10.1101/2021.03.10.434827</a></li>
</ul>
<ol start="14" style="list-style-type: decimal">
<li><strong>RSeQC</strong>:</li>
@@ -95,11 +95,11 @@
<li><strong>MultiQC</strong>:</li>
</ol>
<ul>
- <li>Ewels P., Magnusson M., Lundin S. and Käller M. 2016. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32(19): 3047–3048. doi:<a href="https://dx.doi.org/10.1093/bioinformatics/btw354">10.1093/bioinformatics/btw354</a></li>
+ <li>Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics, 32(19), 3047-3048. doi:<a href="https://dx.doi.org/10.1093/bioinformatics/btw354">10.1093/bioinformatics/btw354</a></li>
</ul>
<ol start="16" style="list-style-type: decimal">
<li><strong>Nextflow</strong>:</li>
</ol>
<ul>
- <li>Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., and Notredame, C. 2017. Nextflow enables reproducible computational workflows. Nature biotechnology, 35(4), 316.</li>
+ <li>Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature biotechnology, 35(4), 316-319.</li>
</ul>
diff --git a/nextflow.config b/nextflow.config
index 7f33391da6a455ba53664c35309c84b27b04d883..87c06b6f659970989f73bddfc31995cefeb6dc14 100644
--- a/nextflow.config
+++ b/nextflow.config
@@ -44,7 +44,7 @@ process {
container = 'gudmaprbk/fastqc0.11.9:1.0.1'
}
withName:seqwho {
- container = 'gudmaprbk/seqwho0.0.1:1.0.0'
+ container = 'gudmaprbk/seqwho1.0.0:1.0.0'
}
withName:trimData {
container = 'gudmaprbk/trimgalore0.6.6:1.0.0'
diff --git a/rna-seq.nf b/rna-seq.nf
index 311b6c34423e300c013fb1fd5a8407b3b4f708dd..c047b3163848be6415c1fc47646345994dc625ca 100644
--- a/rna-seq.nf
+++ b/rna-seq.nf
@@ -720,13 +720,13 @@ process seqwho {
echo -e "LOG: seqwho ran" >> ${repRID}.seqwho.log
# parse inference from R1
- speciesR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f17 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- seqtypeR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- confidenceR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f16 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ speciesR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ confidenceR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f17 -d\$'\t' | cut -f2 -d":" | tr -d " ")
if [ "\${confidenceR1}" == "low" ]
then
- speciesConfidenceR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f16 -d\$'\t' | cut -f3 -d":" | tr -d " ")
- seqtypeConfidenceR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f16 -d\$'\t' | cut -f4 -d":" | tr -d " ")
+ speciesConfidenceR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f17 -d\$'\t' | cut -f3 -d":" | tr -d " ")
+ seqtypeConfidenceR1=\$(cat SeqWho_call.tsv | grep ${fastq[0]} | cut -f17 -d\$'\t' | cut -f4 -d":" | tr -d " ")
else
speciesConfidenceR1="1"
seqtypeConfidenceR1="1"
@@ -736,13 +736,13 @@ process seqwho {
# parse inference from R2
if [ "${ends}" == "pe" ]
then
- speciesR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f17 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- seqtypeR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- confidenceR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f16 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ speciesR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ confidenceR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f17 -d\$'\t' | cut -f2 -d":" | tr -d " ")
if [ "\${confidenceR2}" == "low" ]
then
- speciesConfidenceR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f16 -d\$'\t' | cut -f3 -d":" | tr -d " ")
- seqtypeConfidenceR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f16 -d\$'\t' | cut -f4 -d":" | tr -d " ")
+ speciesConfidenceR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f17 -d\$'\t' | cut -f3 -d":" | tr -d " ")
+ seqtypeConfidenceR2=\$(cat SeqWho_call.tsv | grep ${fastq[1]} | cut -f17 -d\$'\t' | cut -f4 -d":" | tr -d " ")
else
speciesConfidenceR2="1"
seqtypeConfidenceR2="1"
@@ -857,9 +857,9 @@ process seqwho {
gzip sampled.1.seed300.fastq &
wait
seqwho.py -f sampled.1.seed*.fastq.gz -x SeqWho.ix
- seqtypeR1_1=\$(cat SeqWho_call.tsv | grep sampled.1.seed100.fastq.gz | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- seqtypeR1_2=\$(cat SeqWho_call.tsv | grep sampled.1.seed200.fastq.gz | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- seqtypeR1_3=\$(cat SeqWho_call.tsv | grep sampled.1.seed300.fastq.gz | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR1_1=\$(cat SeqWho_call.tsv | grep sampled.1.seed100.fastq.gz | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR1_2=\$(cat SeqWho_call.tsv | grep sampled.1.seed200.fastq.gz | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR1_3=\$(cat SeqWho_call.tsv | grep sampled.1.seed300.fastq.gz | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
cp SeqWho_call.tsv SeqWho_call_sampledR1.tsv
if [ "\${seqtypeR1_1}" == "\${seqtypeR1}" ] && [ "\${seqtypeR1_2}" == "\${seqtypeR1}" ] && [ "\${seqtypeR1_3}" == "\${seqtypeR1}" ]
then
@@ -878,9 +878,9 @@ process seqwho {
gzip sampled.2.seed300.fastq &
wait
seqwho.py -f sampled.2.seed*.fastq.gz -x SeqWho.ix
- seqtypeR2_1=\$(cat SeqWho_call.tsv | grep sampled.2.seed100.fastq.gz | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- seqtypeR2_2=\$(cat SeqWho_call.tsv | grep sampled.2.seed200.fastq.gz | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
- seqtypeR2_3=\$(cat SeqWho_call.tsv | grep sampled.2.seed300.fastq.gz | cut -f18 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR2_1=\$(cat SeqWho_call.tsv | grep sampled.2.seed100.fastq.gz | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR2_2=\$(cat SeqWho_call.tsv | grep sampled.2.seed200.fastq.gz | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
+ seqtypeR2_3=\$(cat SeqWho_call.tsv | grep sampled.2.seed300.fastq.gz | cut -f19 -d\$'\t' | cut -f2 -d":" | tr -d " ")
cp SeqWho_call.tsv SeqWho_call_sampledR2.tsv
if [ "\${seqtypeR2_1}" == "\${seqtypeR1}" ] && [ "\${seqtypeR2_2}" == "\${seqtypeR1}" ] && [ "\${seqtypeR2_3}" == "\${seqtypeR1}" ]
then