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Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data
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| Zeitschriftentitel: | Bioinformatics |
|---|---|
| Personen und Körperschaften: | , , , , , , , , , , , , |
| In: | Bioinformatics, 30, 2014, 2, S. 165-171 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Oxford University Press (OUP)
|
| Schlagwörter: |
| author_facet |
Waszak, Sebastian M. Kilpinen, Helena Gschwind, Andreas R. Orioli, Andrea Raghav, Sunil K. Witwicki, Robert M. Migliavacca, Eugenia Yurovsky, Alisa Lappalainen, Tuuli Hernandez, Nouria Reymond, Alexandre Dermitzakis, Emmanouil T. Deplancke, Bart Waszak, Sebastian M. Kilpinen, Helena Gschwind, Andreas R. Orioli, Andrea Raghav, Sunil K. Witwicki, Robert M. Migliavacca, Eugenia Yurovsky, Alisa Lappalainen, Tuuli Hernandez, Nouria Reymond, Alexandre Dermitzakis, Emmanouil T. Deplancke, Bart |
|---|---|
| author |
Waszak, Sebastian M. Kilpinen, Helena Gschwind, Andreas R. Orioli, Andrea Raghav, Sunil K. Witwicki, Robert M. Migliavacca, Eugenia Yurovsky, Alisa Lappalainen, Tuuli Hernandez, Nouria Reymond, Alexandre Dermitzakis, Emmanouil T. Deplancke, Bart |
| spellingShingle |
Waszak, Sebastian M. Kilpinen, Helena Gschwind, Andreas R. Orioli, Andrea Raghav, Sunil K. Witwicki, Robert M. Migliavacca, Eugenia Yurovsky, Alisa Lappalainen, Tuuli Hernandez, Nouria Reymond, Alexandre Dermitzakis, Emmanouil T. Deplancke, Bart Bioinformatics Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability |
| author_sort |
waszak, sebastian m. |
| spelling |
Waszak, Sebastian M. Kilpinen, Helena Gschwind, Andreas R. Orioli, Andrea Raghav, Sunil K. Witwicki, Robert M. Migliavacca, Eugenia Yurovsky, Alisa Lappalainen, Tuuli Hernandez, Nouria Reymond, Alexandre Dermitzakis, Emmanouil T. Deplancke, Bart 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btt667 <jats:title>Abstract</jats:title> <jats:p>Motivation: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts.</jats:p> <jats:p>Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent–daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.</jats:p> <jats:p>Availability: The R package absfilter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter</jats:p> <jats:p>Contact: sebastian.waszak@epfl.ch or bart.deplancke@epfl.ch</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data Bioinformatics |
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| title |
Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_unstemmed |
Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_full |
Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_fullStr |
Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_full_unstemmed |
Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_short |
Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_sort |
identification and removal of low-complexity sites in allele-specific analysis of chip-seq data |
| topic |
Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability |
| url |
http://dx.doi.org/10.1093/bioinformatics/btt667 |
| publishDate |
2014 |
| physical |
165-171 |
| description |
<jats:title>Abstract</jats:title>
<jats:p>Motivation: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts.</jats:p>
<jats:p>Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent–daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.</jats:p>
<jats:p>Availability: The R package absfilter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter</jats:p>
<jats:p>Contact: sebastian.waszak@epfl.ch or bart.deplancke@epfl.ch</jats:p>
<jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> |
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| author | Waszak, Sebastian M., Kilpinen, Helena, Gschwind, Andreas R., Orioli, Andrea, Raghav, Sunil K., Witwicki, Robert M., Migliavacca, Eugenia, Yurovsky, Alisa, Lappalainen, Tuuli, Hernandez, Nouria, Reymond, Alexandre, Dermitzakis, Emmanouil T., Deplancke, Bart |
| author_facet | Waszak, Sebastian M., Kilpinen, Helena, Gschwind, Andreas R., Orioli, Andrea, Raghav, Sunil K., Witwicki, Robert M., Migliavacca, Eugenia, Yurovsky, Alisa, Lappalainen, Tuuli, Hernandez, Nouria, Reymond, Alexandre, Dermitzakis, Emmanouil T., Deplancke, Bart, Waszak, Sebastian M., Kilpinen, Helena, Gschwind, Andreas R., Orioli, Andrea, Raghav, Sunil K., Witwicki, Robert M., Migliavacca, Eugenia, Yurovsky, Alisa, Lappalainen, Tuuli, Hernandez, Nouria, Reymond, Alexandre, Dermitzakis, Emmanouil T., Deplancke, Bart |
| author_sort | waszak, sebastian m. |
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| description | <jats:title>Abstract</jats:title> <jats:p>Motivation: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts.</jats:p> <jats:p>Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent–daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.</jats:p> <jats:p>Availability: The R package absfilter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter</jats:p> <jats:p>Contact: sebastian.waszak@epfl.ch or bart.deplancke@epfl.ch</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> |
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| imprint | Oxford University Press (OUP), 2014 |
| imprint_str_mv | Oxford University Press (OUP), 2014 |
| institution | DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161, DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275 |
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| spelling | Waszak, Sebastian M. Kilpinen, Helena Gschwind, Andreas R. Orioli, Andrea Raghav, Sunil K. Witwicki, Robert M. Migliavacca, Eugenia Yurovsky, Alisa Lappalainen, Tuuli Hernandez, Nouria Reymond, Alexandre Dermitzakis, Emmanouil T. Deplancke, Bart 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btt667 <jats:title>Abstract</jats:title> <jats:p>Motivation: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts.</jats:p> <jats:p>Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent–daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.</jats:p> <jats:p>Availability: The R package absfilter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter</jats:p> <jats:p>Contact: sebastian.waszak@epfl.ch or bart.deplancke@epfl.ch</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data Bioinformatics |
| spellingShingle | Waszak, Sebastian M., Kilpinen, Helena, Gschwind, Andreas R., Orioli, Andrea, Raghav, Sunil K., Witwicki, Robert M., Migliavacca, Eugenia, Yurovsky, Alisa, Lappalainen, Tuuli, Hernandez, Nouria, Reymond, Alexandre, Dermitzakis, Emmanouil T., Deplancke, Bart, Bioinformatics, Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data, Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability |
| title | Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_full | Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_fullStr | Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_full_unstemmed | Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_short | Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| title_sort | identification and removal of low-complexity sites in allele-specific analysis of chip-seq data |
| title_unstemmed | Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data |
| topic | Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability |
| url | http://dx.doi.org/10.1093/bioinformatics/btt667 |