Additional file 4: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Additional file 1: of Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

Phelan, Jody
O’Sullivan, Denise M
Machado, Diana
Ramos, Jorge
Oppong, Yaa EA
Campino, Susana
O’Grady, Justin
McNerney, Ruth
Hibberd, Martin L
Viveiros, Miguel
Huggett, Jim F
Clark, Taane G.

June 2019

Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public ...

Additional file 1: of Modified genome comparison method: a new approach for identification of specific targets in molecular diagnostic tests using Mycobacterium tuberculosis complex as an example

Alireza Neshani (5852528)
Reza Kamali Kakhki (5852531)
Mojtaba Sankian (5852534)
Hosna Zare (5852537)
Amin Hooshyar Chichaklu (5852546)
Mahsa Sayyadi (5852549)
Kiarash Ghazvini (5852555)

October 2018

Table S1. Investigating the presence of rpoB and 5KST diagnostic targets in M. tuberculosis complete...

Additional file 3: Table S3. of A multiple genome analysis of Mycobacterium tuberculosis reveals specific novel genes and mutations associated with pyrazinamide resistance

Patricia Sheen (118155)
David Requena (498200)
Eduardo Gushiken (4507708)
Robert Gilman (3490442)
Ricardo Antiparra (4507723)
Bryan Lucero (4507720)
Pilar LizĂĄrraga (4507714)
Basilio Cieza (4507711)
Elisa Roncal (4507717)
Louis Grandjean (118150)
Arnab Pain (37809)
Ruth McNerney (227467)
Taane Clark (3507860)
David Moore (30526)
Mirko Zimic (158470)

October 2017

Complete results of the analysis by gene, showing for each gene the number of resistant strains with...

Additional file 6: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

The total number of samples available and the estimated rate of misclassification of phenotypic DST ...

Additional file 5: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Composition of the dataset analysed in this study. This file presents the details of the databases a...

Additional file 3: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Characteristics of the four bioinformatics software for predicting drug resistance from Mtb genome s...

Additional file 1: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Studies reviewed for the LitRev data set. This file presents the list of studies surveyed for LitRev...

Additional file 2: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Quality screening of sequencing data. This file details the quality control step of the study. (DOCX...

Additional file 5: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
João Perdigão (327131)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Drug-resistance phenotype frequency table, Drug-resistance phenotype frequency table by lineage. ‘To...

Additional file 1: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
JoĂŁo PerdigĂŁo (6525866)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Variant Summary Tables, Summary tables of variants called in comparison to the H37rv reference, with...

Additional file 1 of GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning

Gröschel, Matthias I.
Owens, Martin
Freschi, Luca
Vargas, Roger
Marin, Maximilian G.
Phelan, Jody
Iqbal, Zamin
Dixit, Avika
Farhat, Maha R.

August 2021

Accessions and phenotypic drug susceptibility profiles of isolates included in the benchmarking data...

Additional file 1: of In vivo evolution of drug-resistant Mycobacterium tuberculosis in patients during long-term treatment

Yuhui Xu (525146)
Fei Liu (21082)
Suting Chen (486143)
Jiannan Wu (776349)
Yongfei Hu (256131)
Baoli Zhu (43136)
Zhaogang Sun (525143)

August 2018

Table S1. Sequencing statistics of the 18Â M. tuberculosis isolates. Note: A, B, C, and D indicate t...

Additional file 1: of Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance

Xi Zeng (129687)
Jamie Kwok (5229134)
Kevin Yang (243588)
Kenneth Leung (5229137)
Mai Shi (756927)
Zhiyuan Yang (29801)
Wing-Cheong Yam (332134)
Stephen Tsui (3247803)

May 2018

Figure S1. The profile of 1110 isolates. (a) The distribution of isolates in three studies. (b) The ...

Additional file 9: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
JoĂŁo PerdigĂŁo (6525866)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Study frequency table, Study frequency table, showing numbers and percentage of strains from each st...

Additional file 6: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
JoĂŁo PerdigĂŁo (6525866)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Cross-resistance phenotype table, Cross-Resistance Table upper diagonal shows proportion of samples ...

Additional file 1: of Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

Phelan, Jody
O’Sullivan, Denise M
Machado, Diana
Ramos, Jorge
Oppong, Yaa EA
Campino, Susana
O’Grady, Justin
McNerney, Ruth
Hibberd, Martin L
Viveiros, Miguel
Huggett, Jim F
Clark, Taane G.

June 2019

Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public ...

Additional file 1: of Modified genome comparison method: a new approach for identification of specific targets in molecular diagnostic tests using Mycobacterium tuberculosis complex as an example

Alireza Neshani (5852528)
Reza Kamali Kakhki (5852531)
Mojtaba Sankian (5852534)
Hosna Zare (5852537)
Amin Hooshyar Chichaklu (5852546)
Mahsa Sayyadi (5852549)
Kiarash Ghazvini (5852555)

October 2018

Table S1. Investigating the presence of rpoB and 5KST diagnostic targets in M. tuberculosis complete...

Additional file 3: Table S3. of A multiple genome analysis of Mycobacterium tuberculosis reveals specific novel genes and mutations associated with pyrazinamide resistance

Patricia Sheen (118155)
David Requena (498200)
Eduardo Gushiken (4507708)
Robert Gilman (3490442)
Ricardo Antiparra (4507723)
Bryan Lucero (4507720)
Pilar LizĂĄrraga (4507714)
Basilio Cieza (4507711)
Elisa Roncal (4507717)
Louis Grandjean (118150)
Arnab Pain (37809)
Ruth McNerney (227467)
Taane Clark (3507860)
David Moore (30526)
Mirko Zimic (158470)

October 2017

Complete results of the analysis by gene, showing for each gene the number of resistant strains with...

Additional file 6: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

The total number of samples available and the estimated rate of misclassification of phenotypic DST ...

Additional file 5: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Composition of the dataset analysed in this study. This file presents the details of the databases a...

Additional file 3: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Characteristics of the four bioinformatics software for predicting drug resistance from Mtb genome s...

Additional file 1: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Studies reviewed for the LitRev data set. This file presents the list of studies surveyed for LitRev...

Additional file 2: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Tra-My Ngo (6318062)
Yik-Ying Teo (159446)

February 2019

Quality screening of sequencing data. This file details the quality control step of the study. (DOCX...

Additional file 5: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
João Perdigão (327131)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Drug-resistance phenotype frequency table, Drug-resistance phenotype frequency table by lineage. ‘To...

Additional file 1: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
JoĂŁo PerdigĂŁo (6525866)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Variant Summary Tables, Summary tables of variants called in comparison to the H37rv reference, with...

Additional file 1 of GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning

Gröschel, Matthias I.
Owens, Martin
Freschi, Luca
Vargas, Roger
Marin, Maximilian G.
Phelan, Jody
Iqbal, Zamin
Dixit, Avika
Farhat, Maha R.

August 2021

Accessions and phenotypic drug susceptibility profiles of isolates included in the benchmarking data...

Additional file 1: of In vivo evolution of drug-resistant Mycobacterium tuberculosis in patients during long-term treatment

Yuhui Xu (525146)
Fei Liu (21082)
Suting Chen (486143)
Jiannan Wu (776349)
Yongfei Hu (256131)
Baoli Zhu (43136)
Zhaogang Sun (525143)

August 2018

Table S1. Sequencing statistics of the 18Â M. tuberculosis isolates. Note: A, B, C, and D indicate t...

Additional file 1: of Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance

Xi Zeng (129687)
Jamie Kwok (5229134)
Kevin Yang (243588)
Kenneth Leung (5229137)
Mai Shi (756927)
Zhiyuan Yang (29801)
Wing-Cheong Yam (332134)
Stephen Tsui (3247803)

May 2018

Figure S1. The profile of 1110 isolates. (a) The distribution of isolates in three studies. (b) The ...

Additional file 9: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
JoĂŁo PerdigĂŁo (6525866)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Study frequency table, Study frequency table, showing numbers and percentage of strains from each st...

Additional file 6: of Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Yaa Oppong (6525863)
Jody Phelan (3543014)
JoĂŁo PerdigĂŁo (6525866)
Diana Machado (327130)
Anabela Miranda (3583904)
Isabel Portugal (327133)
Miguel Viveiros (69123)
Taane Clark (3507860)
Martin Hibberd (269015)

March 2019

Cross-resistance phenotype table, Cross-Resistance Table upper diagonal shows proportion of samples ...

Additional file 1: of Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

Phelan, Jody
O’Sullivan, Denise M
Machado, Diana
Ramos, Jorge
Oppong, Yaa EA
Campino, Susana
O’Grady, Justin
McNerney, Ruth
Hibberd, Martin L
Viveiros, Miguel
Huggett, Jim F
Clark, Taane G.

June 2019

Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public ...

Additional file 1: of Modified genome comparison method: a new approach for identification of specific targets in molecular diagnostic tests using Mycobacterium tuberculosis complex as an example

Alireza Neshani (5852528)
Reza Kamali Kakhki (5852531)
Mojtaba Sankian (5852534)
Hosna Zare (5852537)
Amin Hooshyar Chichaklu (5852546)
Mahsa Sayyadi (5852549)
Kiarash Ghazvini (5852555)

October 2018

Table S1. Investigating the presence of rpoB and 5KST diagnostic targets in M. tuberculosis complete...

Additional file 3: Table S3. of A multiple genome analysis of Mycobacterium tuberculosis reveals specific novel genes and mutations associated with pyrazinamide resistance

Patricia Sheen (118155)
David Requena (498200)
Eduardo Gushiken (4507708)
Robert Gilman (3490442)
Ricardo Antiparra (4507723)
Bryan Lucero (4507720)
Pilar LizĂĄrraga (4507714)
Basilio Cieza (4507711)
Elisa Roncal (4507717)
Louis Grandjean (118150)
Arnab Pain (37809)
Ruth McNerney (227467)
Taane Clark (3507860)
David Moore (30526)
Mirko Zimic (158470)

October 2017

Complete results of the analysis by gene, showing for each gene the number of resistant strains with...

Additional file 4: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Abstract

Extracted data

Additional file 4: of Genomic prediction of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms

Abstract

Extracted data

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