Citation: Please cite Villanea and Peede et al. 2025 (https://doi.org/10.1126/science.adl0882) when using this data.

To use the data, you will first need to extract the individual data archives (.tar.gz). For example, run tar -xf {data_archive}.tar.gz. After extraction, you may need to edit the code on GitHub so that the paths are appropriate for the computer on which the code is run. The paths provided in this README reflect my original project directory structure.

Below is a quick reference of the naming conventions I used throughout the project.

Naming Conventions

• Archaic Individuals
  • den: Altai Denisovan
  • alt: Altai Neanderthal
  • cha: Chagyrskaya Neanderthal
    • This individual is considered a late Neanderthal.
  • vin: Vindija Neanderthal
    • This individual is considered a late Neanderthal.
• Modern Human Datasets
  • tgp: 1000 Genomes Project
  • sgdp: Simon's Genome Diversity Project
• 1000 Genomes Project Superpopulations & Populations
  • afr: Africans
    • Populations: yri, lwk, gwd, msl, esn
  • amr: Admixed Americans
    • Populations: mxl, pel, clm, pur
  • sas: South Asians
    • Populations: beb, stu, itu, pjl, gih
  • eas: East Asians
    • Populations: chb, khv, chs, jpt, cdx
  • eur: Europeans
    • Populations: tsi, ceu, ibs, gbr, fin

Data Description

Note on Paths: The file paths listed below correspond to the directory structure used in the original study. After extracting the archives, you may need to organize the files accordingly or adjust paths in the analysis scripts.

amr_lai

72kb_amr_beds.tar.gz & short_read_repeat_amr_beds.tar.gz

Both 72kb_amr_beds.tar.gz and short_read_repeat_amr_beds.tar.gz contain BED files, which are the output from the bedtools code found here.

Paths

• 72kb_amr_beds.tar.gz
  • ./muc19/amr_lai/region_beds/72kb/{amr_ind}_{A,B}.bed
• short_read_repeat_amr_beds.tar.gz
  • ./muc19/amr_lai/region_beds/short_read_repeat/{amr_ind}_{A,B}.bed

{amr_ind}_{A,B}.bed

Each admixed American individual ({amr_ind}) has two corresponding BED files, one per haplotype ({A,B}). Each BED file has the following columns:

• Columns 1-6: Original columns from RFmix.
• Columns 7-9: Coordinates for the intersecting region of interest.
  • The BED files for the intersecting region of interest can be found here.
• Column 10: Number of base pairs of overlap with respect to the intersecting region of interest.

annotations

annotations.tar.gz

annotations.tar.gz contains the output from data_processing_v_revisions.ipynb found here and the outputs from tgp_single_archaic_gene_qc_v_revisions.py and consolidate_tgp_single_archaic_genes_v_revisions.py, which can be found here.

Paths

• annotations.tar.gz
  • ./muc19/annotations/hg19_genes/ncbi_refseq_genes_chr{1..22}.csv.gz
  • ./muc19/annotations/hg19_genes/ncbi_refseq_transcripts.txt
  • ./muc19/annotations/hg19_genes/ncbiRefSeqSelect.txt.gz
  • ./muc19/annotations/rate_files/genetic_map_GRCh37_chr12.txt
  • ./muc19/annotations/rate_files/subst_rate_autosome.bed.gz
  • ./muc19/annotations/rate_files/subst_rate_autosome.bed.gz.tbi
  • ./muc19/annotations/rate_files/{742,72}kb_region.bed
  • ./muc19/annotations/rate_files/subst_rate_{742,72}kb.bed
  • ./muc19/annotations/tgp_den_masked_no_aa/ncbi_refseq_genes_summary_chr{1..22}.csv.gz
  • ./muc19/annotations/tgp_den_masked_no_aa/ncbi_refseq_{invariant,variant}_genes.csv.gz

ncbi_refseq_genes_chr{1..22}.csv.gz

One file per autosome ({1..22}) containing the NCBI RefSeq Select gene coordinates with the following columns:

• GENE_ID: NCBI RefSeq Select gene ID.
• TRANSCRIPT_ID: NCBI RefSeq Select transcript ID.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).

ncbi_refseq_transcripts.txt

One file with a single column listing all of the autosomal NCBI RefSeq Select transcript IDs used for the SnpEff annotations.

ncbiRefSeqSelect.txt.gz

Original NCBI RefSeq Select gene coordinates in GTF format downloaded from UCSC Genome browser (download link), and the format of the file is described here.

genetic_map_GRCh37_chr12.txt

HapMap genetic map for chromosome 12 build GRCh37/hg19, with the following columns:

• Chromosome: Chromosome.
• Position(bp) : Physical position.
• Rate(cM/Mb): Local recombination rate.
• Map(cM): The cumulative genetic map position with respect to the corresponding Position(bp) coordinate.

subst_rate_autosome.bed.gz and subst_rate_autosome.bed.gz.tbi

subst_rate_autosome.bed.gz is a bgzipped BED file containing local mutation rates. This BED file was generated using this script, with the following columns:

• Column 1: Chromosome.
• Column 2: Start position (inclusive).
• Column 3: End position (exclusive).
• Column 4: Local mutation rate.
  subst_rate_autosome.bed.gz.tbi is the corresponding binary index file using tabix, generated by running the following code:

tabix -p bed subst_rate_autosome.bed.gz

{742,72}kb_region.bed

BED files with a single row per file for the focal 742kb and 72kb ({742,72}kb) MUC19 regions, with the following columns:

• Column 1: Chromosome.
• Column 2: Start position (inclusive).
• Column 3: End position (exclusive).

subst_rate_{742,72}kb.bed

BED files containing the local mutation rates for the focal 742kb and 72kb ({742,72}kb) MUC19 regions, generated by running the following bedtools code:

bedtools intersect -a subst_rate_autosome.bed.gz -b 72kb_region.bed -wo > subst_rate_72kb.bed
bedtools intersect -a subst_rate_autosome.bed.gz -b 742kb_region.bed -wo > subst_rate_742kb.bed

with the following columns:

• Columns 1-4: Original columns from subst_rate_autosome.bed.gz for the regions that intersect with the focal 742kb and 72kb ({742,72}kb) MUC19 regions.
• Columns 5-7: Original columns from 742kb and 72kb MUC19 regions.
• Column 8: Number of base pairs from subst_rate_autosome.bed.gz (i.e., columns 1-3 for a given row) that overlap with {742,72}kb_region.bed (i.e., columns 5-7 for a given row).

ncbi_refseq_genes_summary_chr{1..22}.csv.gz

One file per autosome (chr{1..22} ) where each row corresponds to the QC summary per NCBI RefSeq Select gene, with the following columns:

• IDX: Gene index with respect to the CHR column.
• GENE_ID: NCBI RefSeq Select gene ID.
• TRANSCRIPT_ID: NCBI RefSeq Select transcript ID.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• DEN: Effective sequence length with respect to the Altai Denisovan.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

ncbi_refseq_{invariant,variant}_genes.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) NCBI RefSeq Select genes, with the following columns:

• IDX: Gene index with respect to the CHR column.
• GENE_ID: NCBI RefSeq Select gene ID.
• TRANSCRIPT_ID: NCBI RefSeq Select transcript ID.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• DEN: Effective sequence length with respect to the Altai Denisovan.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

arc_snp_density

classify_tgp_snps_chromosome.tar.gz

classify_tgp_snps_chromosome.tar.gz is the output from classify_tgp_snps_chromosome_v_revisions.py found here. The original path is ./muc19/muc19_results/tgp_arcs_masked_no_aa/{non_afr_pop,tgp}_{snp_type}_chr{1..22}.txt.gz.

‌{non_afr_pop,tgp}_{snp_type}_chr{1..22}.txt.gz

For each non-African population ({non_afr_pop}) and the entire 1000 Genomes Project ({tgp}), each file has one row listing the positions for the specified SNP classification ({snp_type}), stratified by autosome (chr{1..22}).

tgp_archaic_snp_denisty_windows.tar.gz

tgp_archaic_snp_denisty_windows.tar.gz is the output from tgp_archaic_snp_denisty_windows_v_revisions.py found here. The original path is ./muc19/muc19_results/tgp_arcs_masked_no_aa/{non_afr_pop}_arc_snp_denisty_chr{1..22}_{742,72}kb.txt.gz.

{non_afr_pop}_arc_snp_denisty_chr{1..22}_{742,72}kb.txt.gz

For each non-African population ({non_afr_pop}), each row contains archaic SNP partition counts for a non-overlapping 742kb or 72kb window ({742,72}kb), stratified by autosome (chr{1..22}), with the following columns:

• Column 1: Denisovan-specific SNPs.
• Column 2: Neanderthal-specific SNPs.
• Column 3: Shared archaic SNPs.
• Column 4: Archaic SNPs.

heterozygosity

{den,alt,cha,vin}_heterozygosity_chromosome.tar.gz

den_heterozygosity_chromosome.tar.gz, alt_heterozygosity_chromosome.tar.gz, cha_heterozygosity_chromosome.tar.gz, and vin_heterozygosity_chromosome.tar.gz are the output from archaic_heterozygosity_chromosome_v_revisions.py found here.

Paths

• den_heterozygosity_chromosome.tar.gz
  • ./muc19/muc19_results/den_masked_no_aa/archaic_het_sites_heterozygosity_eff_seq_len_chr{1..22}.txt.gz
• alt_heterozygosity_chromosome.tar.gz
  • ./muc19/muc19_results/alt_masked_no_aa/archaic_het_sites_heterozygosity_eff_seq_len_chr{1..22}.txt.gz
• cha_heterozygosity_chromosome.tar.gz
  • ./muc19/muc19_results/cha_masked_no_aa/archaic_het_sites_heterozygosity_eff_seq_len_chr{1..22}.txt.gz
• vin_heterozygosity_chromosome.tar.gz
  • ./muc19/muc19_results/vin_masked_no_aa/archaic_het_sites_heterozygosity_eff_seq_len_chr{1..22}.txt.gz

archaic_het_sites_heterozygosity_eff_seq_len_chr{1..22}.txt.gz

For each archaic individual ({den,alt,cha,vin}), there is one corresponding file per autosome (chr{1..22}) with the following columns:

• Column 1: Number of heterozygous sites.
• Column 2: Gene diversity.
• Column 3: Effective sequence length.

{den,alt,cha,vin}_heterozygosity_windows.tar.gz

den_heterozygosity_windows.tar.gz, alt_heterozygosity_windows.tar.gz, cha_heterozygosity_windows.tar.gz, and vin_heterozygosity_windows.tar.gz are the output from archaic_heterozygosity_windows_v_revisions.py found here.

Paths

• den_heterozygosity_windows.tar.gz
  • ./muc19/muc19_results/den_masked_no_aa/archaic_het_sites_heterozygosity_chr{1..22}_72kb.txt.gz
• alt_heterozygosity_windows.tar.gz
  • ./muc19/muc19_results/alt_masked_no_aa/archaic_het_sites_heterozygosity_chr{1..22}_72kb.txt.gz
• cha_heterozygosity_windows.tar.gz
  • ./muc19/muc19_results/cha_masked_no_aa/archaic_het_sites_heterozygosity_chr{1..22}_72kb.txt.gz
• vin_heterozygosity_windows.tar.gz
  • ./muc19/muc19_results/vin_masked_no_aa/archaic_het_sites_heterozygosity_chr{1..22}_72kb.txt.gz

archaic_het_sites_heterozygosity_chr{1..22}_72kb.txt.gz

For each archaic individual ({den,alt,cha,vin}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping 72kb window and has the following columns:

• Column 1: Number of heterozygous sites.
• Column 2: Gene diversity.

tgp_heterozygosity_chromosome.tar.gz

tgp_heterozygosity_chromosome.tar.gz is the output from tgp_heterozygosity_chromosome_v_revisions.py found here.

Paths

• tgp_heterozygosity_chromosome.tar.gz
  • ./muc19/muc19_results/tgp_mod_no_aa/tgp_het_sites_chr{1..22}.txt.gz
  • ./muc19/muc19_results/tgp_mod_no_aa/afr_heterozygosity_eff_seq_len_chr{1..22}.txt.gz

tgp_het_sites_chr{1..22}.txt.gz

For each autosome (chr{1..22}), the columns correspond to a 1000 Genomes Project individual, in the same order as individuals appear in ./muc19/meta_data/tgp_mod.txt. Each entry is the number of heterozygous sites for that individual in that chromosome.

afr_heterozygosity_eff_seq_len_chr{1..22}.txt.gz

For the African superpopulation (afr) in the 1000 Genomes Project, there is one corresponding file per autosome (chr{1..22}) with the following columns:

• Column 1: Gene diversity.
• Column 2: Effective sequence length.

tgp_heterozygosity_windows.tar.gz

tgp_heterozygosity_windows.tar.gz is the output from tgp_heterozygosity_windows_v_revisions.py found here. The original path is ./muc19/muc19_results/tgp_mod_no_aa/{afr,het,hom}_het_sites_chr{1..22}_72kb.txt.gz.

{afr,het,hom}_het_sites_chr{1..22}_72kb.txt.gz

For each focal group ({afr,het,hom}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping 72kb window, and the columns correspond to the number of heterozygous sites per 1000 Genomes Project individual. The order of individuals is as specified in the following metadata files:

• afr: African individuals.
  • ./muc19/meta_data/tgp_mod.txt
• het: Individuals with one introgressed haplotype at the 72kb region.
  • ./muc19/meta_data/tgp_het_den_like_ind_idx_72kb.txt.gz
• hom: Individuals with two introgressed haplotypes at the 72kb region.
  • ./muc19/meta_data/tgp_hom_den_like_ind_idx_72kb.txt.gz

iHS

tgp_selscan_maps.tar.gz & tgp_selscan_vcfs.tar.gz

tgp_selscan_maps.tar.gz and tgp_selscan_vcfs.tar.gz are the outputs from make_selscan_population_data_v_revisions.py found here.

Paths

• tgp_selscan_maps.tar.gz
  • ./muc19/iHS/maps/{pop}_selscan_chr{1..22}.map
• tgp_selscan_vcfs.tar.gz
  • ./muc19/iHS/selscan_vcfs/{pop}_selscan_chr{1..22}.vcf

‌‌{pop}_selscan_chr{1..22}.map

For every population in the 1000 Genomes Project ({pop}), there is one corresponding map file per autosome (chr{1..22}) with the following columns:

• Column 1: Chromosome.
• Column 2: Locus ID.
• Column 3: Genetic position.
• Column 4: Physical position.

‌‌{pop}_selscan_chr{1..22}.vcf

For every population in the 1000 Genomes Project ({pop}), there is one corresponding selscan formatted VCF file per autosome (chr{1..22}) with the following columns:

• Column 1: Chromosome.
• Column 2: Physical position.
• Column 3: Locus ID.
• Column 4: Ancestral allele.
• Column 5: Derived allele.
• Column 6: Quality field.
• Column 7: Filter field.
• Column 8: Info field.
• Column 9: Format field.
• Subsequent columns contain genotype information for individuals in the same order as they appear in ./muc19/meta_data/tgp_mod.txt.

tgp_selscan_ihs_output.tar.gz

tgp_selscan_ihs_output.tar.gz is the output from the selscan code found here.

Paths

• tgp_selscan_ihs_output.tar.gz
  • ./muc19/muc19_results/tgp_mod_aa/{pop}_chr{1..22}.ihs.out
  • ./muc19/muc19_results/tgp_mod_aa/{pop}_chr{1..22}.ihs.out.100bins.norm

{pop}_chr{1..22}.ihs.out & {pop}_chr{1..22}.ihs.out.100bins.norm

For every population in the 1000 Genomes Project ({pop}), there is a corresponding unnormalized (.ihs.out) and normalized (.ihs.out.100bins.norm) iHS file per autosome (chr{1..22}). The columns are described in the selscan documentation, which you can find here.

tgp_ihs_tables.tar.gz

tgp_ihs_tables.tar.gz is the output from compile_ihs_tables_v_revisions.py found here.

Paths

• tgp_ihs_tables.tar.gz:
  • ./muc19/muc19_results/tgp_mod_aa/{pop}_ihs_genome_wide.csv.gz
  • ./muc19/muc19_results/tgp_mod_aa/{pop}_ihs_windows_{742,72}kb.csv.gz

{pop}_ihs_genome_wide.csv.gz

For every population in the 1000 Genomes Project ({pop}), this file contains genome-wide iHS data with the following columns:

• ID: Locus ID.
• CHR: Chromosome.
• POS: Physical position.
• DAF: Derived allele frequency.
• IHH1: Integrated haplotype homozygosity for the derived allele.
• IHH0: Integrated haplotype homozygosity for the ancestral allele.
• U_IHS: Unnormalized integrated haplotype score.
• N_IHS: Normalized integrated haplotype score.
• CRIT: Is the absolute value of the normalized iHS greater than two? (numeric, e.g., 1 if true, 0 if false).
• DEN: Is this a Denisovan-specific SNP? (boolean).
• NEA: Is this a Neanderthal-specific SNP? (boolean).
• SHR: Is this a shared archaic SNP? (boolean).
• ARC: Is this an archaic SNP? (boolean).
• HOM: Is this a shared Hominin SNP? (boolean).
• HUM: Is this a human-specific SNP? (boolean).
• ALL_CRIT: Is the absolute value of the normalized iHS greater than two? (boolean).
• DEN_CRIT: Is this a Denisovan-specific SNP AND is the absolute value of the normalized iHS greater than two? (boolean).
• NEA_CRIT: Is this a Neanderthal-specific SNP AND is the absolute value of the normalized iHS greater than two? (boolean).
• SHR_CRIT: Is this a shared archaic SNP AND is the absolute value of the normalized iHS greater than two? (boolean).
• ARC_CRIT: Is this an archaic SNP AND is the absolute value of the normalized iHS greater than two? (boolean).
• HOM_CRIT: Is this a shared Hominin SNP AND is the absolute value of the normalized iHS greater than two? (boolean).
• HUM_CRIT: Is this a human-specific SNP AND is the absolute value of the normalized iHS greater than two? (boolean).

{pop}_ihs_windows_{742,72}kb.csv.gz

For every population in the 1000 Genomes Project ({pop}), this file contains windowed iHS data. Each row corresponds to a non-overlapping window ({742,72}kb) with the following columns:

• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (exclusive).
• N_ALL_SNPS: Number of SNPs.
• N_DEN_SNPS: Number of Denisovan-specific SNPs.
• N_NEA_SNPS: Number of Neanderthal-specific SNPs.
• N_SHR_SNPS: Number of shared archaic SNPs.
• N_ARC_SNPS: Number of archaic SNPs.
• N_HOM_SNPS: Number of shared Hominin SNPs.
• N_HUM_SNPS: Number of human-specific SNPs.
• N_ALL_CRIT: Number of SNPs with an absolute value of the normalized iHS greater than two.
• PROP_ALL_CRIT: Proportion of SNPs with an absolute value of the normalized iHS greater than two.
• N_DEN_CRIT: Number of Denisovan-specific SNPs with an absolute value of the normalized iHS greater than two.
• PROP_DEN_CRIT: Proportion of Denisovan-specific SNPs with an absolute value of the normalized iHS greater than two.
• N_NEA_CRIT: Number of Neanderthal-specific SNPs with an absolute value of the normalized iHS greater than two.
• PROP_NEA_CRIT: Proportion of Neanderthal-specific SNPs with an absolute value of the normalized iHS greater than two.
• N_SHR_CRIT: Number of shared archaic SNPs with an absolute value of the normalized iHS greater than two.
• PROP_SHR_CRIT: Proportion of shared archaic SNPs with an absolute value of the normalized iHS greater than two.
• N_ARC_CRIT: Number of archaic SNPs with an absolute value of the normalized iHS greater than two.
• PROP_ARC_CRIT: Proportion of archaic SNPs with an absolute value of the normalized iHS greater than two.
• N_HOM_CRIT: Number of shared Hominin SNPs with an absolute value of the normalized iHS greater than two.
• PROP_HOM_CRIT: Proportion of shared Hominin SNPs with an absolute value of the normalized iHS greater than two.
• N_HUM_CRIT: Number of human-specific SNPs with an absolute value of the normalized iHS greater than two.
• PROP_HUM_CRIT: Proportion of human-specific SNPs with an absolute value of the normalized iHS greater than two.

introgression

archaic_site_patterns_windows.tar.gz

archaic_site_patterns_windows.tar.gz is the output from archaic_site_patterns_windows_v_revisions.py found here.

Paths

• archaic_site_patterns_windows.tar.gz
  • ./muc19/muc19_results/arcs_masked_aa/alt_{cha,vin}_den_chr{1..22}_72kb.txt.gz

alt_{cha,vin}_den_chr{1..22}_72kb.txt.gz

For each late Neanderthal ({cha,vin}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping 72kb window with the following columns:

• Column 1: Number of ABBA sites.
• Column 2: Number of BABA sites.
• Column 3: Number of BBAA sites.
• Column 4: Number of BAAA sites.
• Column 5: Number of ABAA sites.
• Column 6: Number of AABA sites.

yri_na19664_archaic_site_patterns_windows.tar.gz

yri_na19664_archaic_site_patterns_windows.tar.gz is the output from mxl_archaic_site_patterns_windows_v_revisions.py found here.

Paths

• yri_na19664_archaic_site_patterns_windows.tar.gz:
  • ./muc19/muc19_results/tgp_den_masked_aa/yri_na19664_den_chr{1..22}_{742,72}kb.txt.gz
  • ./muc19/muc19_results/tgp_alt_masked_aa/yri_na19664_alt_chr{1..22}_{742,72}kb.txt.gz
  • ./muc19/muc19_results/tgp_cha_masked_aa/yri_na19664_cha_chr{1..22}_{742,72}kb.txt.gz
  • ./muc19/muc19_results/tgp_vin_masked_aa/yri_na19664_vin_chr{1..22}_{742,72}kb.txt.gz

yri_na19664_{den,alt,cha,vin}_chr{1..22}_{742,72}kb.txt.gz

For each archaic individual ({den,alt,cha,vin}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping window ({742,72}kb) with the following columns:

• Column 1: Number of ABBA sites.
• Column 2: Number of BABA sites.
• Column 3: Number of BBAA sites.
• Column 4: Number of BAAA sites.
• Column 5: Number of ABAA sites.
• Column 6: Number of AABA sites.

tgp_q95_u30_afr_b_den_windows.tar.gz

tgp_q95_u30_afr_b_den_windows.tar.gz is the output from tgp_q95_u30_afr_b_den_windows_v_revisions.py found here.

Paths

• tgp_q95_u30_afr_b_den_windows.tar.gz
  • ./muc19/muc19_results/tgp_den_masked_no_aa/q95_u20_u30_afr_{non_afr_pop}_den_chr{1..22}_{742,72}kb.txt.gz

q95_u20_u30_afr_{non_afr_pop}_den_chr{1..22}_{742,72}kb.txt.gz

For each non-African population ({non_afr_pop}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping window ({742,72}kb) with the following columns:

• Column 1: The Q95 value.
• Column 2: The U20 value.
• Column 3: The U30 value.

tgp_u30_afr_b_den_windows.tar.gz

tgp_u30_afr_b_den_windows.tar.gz is the output from tgp_u30_afr_b_den_windows_v_revisions.py found here.

Paths

• tgp_u30_afr_b_den_windows.tar.gz
  • ./muc19/muc19_results/tgp_den_masked_no_aa/u30_afr_b_den_chr{1..22}_{742,72}kb.txt.gz

u30_afr_b_den_chr{1..22}_{742,72}kb.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. Each row corresponds to a non-overlapping window ({742,72}kb), and the columns correspond to the non-African population used to compute U30 in the following order: MXL, PEL, CLM, PUR, BEB, STU, ITU, PJL, GIH, CHB, KHV, CHS, JPT, CDX, TSI, CEU, IBS, GBR, FIN.

tgp_u30_afr_b_den_genes.tar.gz

tgp_u30_afr_b_den_genes.tar.gz is the output from tgp_u30_afr_b_den_genes_v_revisions.py found here.

Paths

• tgp_u30_afr_b_den_genes.tar.gz
  • ./muc19/muc19_results/tgp_den_masked_no_aa/u30_afr_b_den_per_gene_chr{1..22}.txt.gz

u30_afr_b_den_per_gene_chr{1..22}.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. Each row corresponds to an NCBI RefSeq Select gene, and the columns correspond to the non-African population used to compute U30 in the following order: MXL, PEL, CLM, PUR, BEB, STU, ITU, PJL, GIH, CHB, KHV, CHS, JPT, CDX, TSI, CEU, IBS, GBR, FIN.

pbs

amr_asn_eur_pbs_windows.tar.gz

amr_asn_eur_pbs_windows.tar.gz is the output from amr_asn_eur_pbs_windows_v_revisions.py found here.

Paths

• amr_asn_eur_pbs_windows.tar.gz
  • ./muc19/muc19_results/tgp_mod_no_aa/{amr_pop}_{asn_pop}_{eur_pop}_chr{1..22}_{742,72}kb.txt.gz

{amr_pop}_{asn_pop}_{eur_pop}_chr{1..22}_{742,72}kb.txt.gz

PBS(A, B, C) values for all unique combinations of A = AMR population ({amr_pop}), B = EAS/SAS population ({asn_pop}), and C = EUR population ({eur_pop}). There is one corresponding file per autosome (chr{1..22}). Each file contains a single row, where each column in that row represents the PBS(A,B,C) value for a non-overlapping window ({742,72}kb).

mxl_chb_ceu_pbs_chromsome.tar.gz

mxl_chb_ceu_pbs_chromsome.tar.gz is the output from mxl_chb_ceu_pbs_chromsome_v_revisions.py found here.

Paths

• mxl_chb_ceu_pbs_chromsome.tar.gz
  • ./muc19/muc19_results/tgp_mod_no_aa/mxl_chb_ceu_pbs_partitions_chr{1..22}.txt.gz

mxl_chb_ceu_pbs_partitions_chr{1..22}.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. Each row corresponds to a genomic position and has the following columns:

• Column 1: PBS using all MXL individuals.
• Column 2: PBS using only MXL individuals with more than 50% Indigenous American ancestry.
• Column 3: PBS using only MXL individuals with less than 50% Indigenous American ancestry.

mxl_chb_ceu_pbs_windows.tar.gz

mxl_chb_ceu_pbs_windows.tar.gz is the output from mxl_chb_ceu_pbs_windows_v_revisions.py found here.

Paths

• mxl_chb_ceu_pbs_windows.tar.gz
  • ./muc19/muc19_results/tgp_mod_no_aa/mxl_chb_ceu_pbs_partitions_chr{1..22}_{742,72}kb.txt.gz

mxl_chb_ceu_pbs_partitions_chr{1..22}_{742,72}kb.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. Each row corresponds to a non-overlapping window ({742,72}kb) with the following columns:

• Column 1: PBS using all MXL individuals.
• Column 2: PBS using only MXL individuals with more than 50% Indigenous American ancestry.
• Column 3: PBS using only MXL individuals with less than 50% Indigenous American ancestry.

sprime_sites_mxl_chb_ceu_pbs_windows.tar.gz

sprime_sites_mxl_chb_ceu_pbs_windows.tar.gz is the output from sprime_sites_mxl_chb_ceu_pbs_windows_v_revisions.py found here.

Paths

• sprime_sites_mxl_chb_ceu_pbs_windows.tar.gz
  • ./muc19/muc19_results/tgp_mod_no_aa/mxl_chb_ceu_pbs_sprime_all_arc_chr{1..22}_{742,72}kb.txt.gz

mxl_chb_ceu_pbs_sprime_all_arc_chr{1..22}_{742,72}kb.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. Each row corresponds to a non-overlapping window ({742,72}kb) with the following columns:

• Column 1: PBS for SPrime sites in MXL that match with either the Altai Denisovan or Altai Neanderthal.
• Column 2: Number of SPrime sites in MXL that match with either the Altai Denisovan or Altai Neanderthal.

pbs_sims

{neutral,negative,positive_neutral_s1,positive_neutral_s01,positive_neutral_s0015}_recomb_map_slimulated_vcfs.tar.gz

These archives (listed below) contain the VCF files from the SLiMulations. The SLiM scripts can be found here.

• neutral_recomb_map_slimulated_vcfs.tar.gz is output from sim_sneutral_rmap.slim.
• negative_recomb_map_slimulated_vcfs.tar.gz is output from sim_snegative_rmap.slim.
• positive_neutral_s1_recomb_map_slimulated_vcfs.tar.gz is output from sim_spositive_neutral_1_rmap.slim.
• positive_neutral_s01_recomb_map_slimulated_vcfs.tar.gz is output from sim_spositive_neutral_01_rmap.slim.
• positive_neutral_s0015_recomb_map_slimulated_vcfs.tar.gz is output from sim_spositive_neutral_0015_rmap.slim.

Paths

• neutral_recomb_map_slimulated_vcfs.tar.gz
  • ./muc19/pbs_sims/smodel/neutral/recomb_map/VCF_sneutral_{sim_id}_{rep_id}.txt.gz
• negative_recomb_map_slimulated_vcfs.tar.gz
  • ./muc19/pbs_sims/smodel/negative/recomb_map/VCF_snegative_{sim_id}_{rep_id}.txt.gz
• positive_neutral_s1_recomb_map_slimulated_vcfs.tar.gz
  • ./muc19/pbs_sims/smodel/positive_neutral_1/VCF_spositive_neutral_{sim_id}_{rep_id}.txt
• positive_neutral_s01_recomb_map_slimulated_vcfs.tar.gz
  • ./muc19/pbs_sims/smodel/positive_neutral_01/VCF_spositive_neutral_{sim_id}_{rep_id}.txt
• positive_neutral_s0015_recomb_map_slimulated_vcfs.tar.gz
  • ./muc19/pbs_sims/smodel/positive_neutral_0015/VCF_spositive_neutral_{sim_id}_{rep_id}.txt

VCF_{sneutral,snegative,spositive_neutral}_{sim_id}_{rep_id}.{txt,txt.gz}

There are 10,000 simulated replicates ({sim_id}_{rep_id}), each as a bgzipped VCF file (.txt.gz), for the neutral ({sneutral}) and heterosis ({snegative}) SLiMulations. There are 1,000 simulated replicates, each as a VCF file (.txt), for the positive selection ({spositive_neutral}) SLiMulations. In each VCF file, the first 99 samples are simulated European individuals, the next 103 samples are simulated East Asian individuals, and the last 64 samples are simulated Mexican individuals. The VCF format specification can be found here.

mxl_slimulations.tar.gz

mxl_slimulations.tar.gz is the output from extract_neutral_negative_recomb_map_slimulated_results.py and extract_positive_slimulations_info.py found here.

Paths

• mxl_slimulations.tar.gz
  • ./muc19/muc19_results/mxl_slimulations/{neutral,negative}_per_10k_replicates.csv.gz
  • ./muc19/muc19_results/mxl_slimulations/{neutral,negative}_{all,arc}_snp_freqs_{742,72}kb_per_snp.txt.gz
  • ./muc19/muc19_results/mxl_slimulations/{neutral,negative}_pbs_{all,arc}_snps_{742,72}kb_per_snp.txt.gz
  • ./muc19/muc19_results/mxl_slimulations/positive_s{s1,s01,s0015}_per_1k_replicates.csv.gz

{neutral,negative}_per_10k_replicates.csv.gz

For each selection scenario ({neutral,negative}), there is one corresponding file. Each row corresponds to one simulated replicate, with the following columns:

• geq_all_snps_742kb: Number of SNPs in MXL segregating at a frequency greater than or equal to 0.3 in the 742kb region.
• pbs_all_snps_742kb: PBS(A=MXL,B=EAS,C=EUR) value for the 742kb region using all SNPs.
• prop_out_pbs_all_snps_742kb: Proportion of per-SNP PBS(A=MXL,B=EAS,C=EUR) values greater than the empirical 99.95th percentile for the 742kb region.
• geq_arc_snps_742kb: Number of archaic SNPs in MXL segregating at a frequency greater than or equal to 0.3 in the 742kb region.
• pbs_arc_snps_742kb: PBS(A=MXL,B=EAS,C=EUR) value for the 742kb region using archaic SNPs.
• prop_out_pbs_arc_snps_742kb: Proportion of per-archaic SNP PBS(A=MXL,B=EAS,C=EUR) values greater than the empirical 99.95th percentile for the 742kb region.
• geq_all_snps_72kb: Number of SNPs in MXL segregating at a frequency greater than or equal to 0.3 in the 72kb region.
• pbs_all_snps_72kb: PBS(A=MXL,B=EAS,C=EUR) value for the 72kb region using all SNPs.
• prop_out_pbs_all_snps_72kb: Proportion of per-SNP PBS(A=MXL,B=EAS,C=EUR) values greater than the empirical 99.95th percentile for the 72kb region.
• geq_arc_snps_72kb: Number of archaic SNPs in MXL segregating at a frequency greater than or equal to 0.3 in the 72kb region.
• pbs_arc_snps_72kb: PBS(A=MXL,B=EAS,C=EUR) value for the 72kb region using archaic SNPs.
• prop_out_pbs_arc_snps_72kb: Proportion of per-archaic SNP PBS(A=MXL,B=EAS,C=EUR) values greater than the empirical 99.95th percentile for the 72kb region.

{neutral,negative}_{all,arc}_snp_freqs_{742,72}kb_per_snp.txt.gz

For each selection scenario ({neutral,negative}), there is one corresponding file for all ({all}) and archaic ({arc}) SNPs per focal region ({742,72}kb). Each file has one row, where the values represent the allele frequency for sites segregating in MXL across all 10,000 simulated replicates.

{neutral,negative}_pbs_{all,arc}_snps_{742,72}kb_per_snp.txt.gz

For each selection scenario ({neutral,negative}), there is one corresponding file for all ({all}) and archaic ({arc}) SNPs per focal region ({742,72}kb). Each file has one row, where the values represent the per-SNP PBS(A=MXL,B=EAS,C=EUR) values across all 10,000 simulated replicates.

positive_s{s1,s01,s0015}_per_1k_replicates.csv.gz

For each selection coefficient ({s1,s01,s0015}), there is one corresponding file. Each row corresponds to one simulated replicate, with the following columns:

• vcf_file: Corresponding VCF file.
• rng_seed: Corresponding SLiM rng seed.
• org_rep_id: Arbitrary replicate ID.
• n_den_742kb: Number of Denisovan SNPs in the 742kb region.
• n_nea_742kb: Number of Neanderthal SNPs in the 742kb region.
• n_arc_742kb: Number of archaic SNPs in the 742kb region.
• n_den_72kb: Number of Denisovan SNPs in the 72kb region.
• n_nea_72kb: Number of Neanderthal SNPs in the 72kb region.
• n_arc_72kb: Number of archaic SNPs in the 72kb region.
• sel_pos: Position of the selected mutation.
• sel_origin: Population origin of the selected mutation.
• sel_mxl_daf: Frequency of the selected allele in the sampled MXL individuals.
• sel_eas_daf: Frequency of the selected allele in the sampled EAS individuals.
• sel_eur_daf: Frequency of the selected allele in the sampled EUR individuals.
• MXB_before: Frequency of the mutation in the MXB population before positive selection.
• EAS_before: Frequency of the mutation in the EAS population before positive selection.
• EUR_before: Frequency of the mutation in the EUR population before positive selection.
• MXB_after: Frequency of the selected allele in the MXB population at the end of the SLiMulation.
• MXL_after: Frequency of the selected allele in the MXL population at the end of the SLiMulation.
• EAS_after: Frequency of the selected allele in the EAS population at the end of the SLiMulation.
• EUR_after: Frequency of the selected allele in the EUR population at the end of the SLiMulation.
• n_seg_all_snps_742kb: Number of segregating sites in the 742kb region.
• pbs_all_snps_742kb: PBS(A=MXL,B=EAS,C=EUR) value for the 742kb region using all SNPs.
• fst_mxl_eas_all_snps_742kb: Fst(MXL,EAS) value for the 742kb region using all SNPs.
• fst_mxl_eur_all_snps_742kb: Fst(MXL,EUR) value for the 742kb region using all SNPs.
• fst_eas_eur_all_snps_742kb: Fst(EAS,EUR) value for the 742kb region using all SNPs.
• n_seg_arc_snps_742kb: Number of archaic SNPs segregating in the 742kb region.
• pbs_arc_snps_742kb: PBS(A=MXL,B=EAS,C=EUR) value for the 742kb region using archaic SNPs.
• fst_mxl_eas_arc_snps_742kb: Fst(MXL,EAS) value for the 742kb region using archaic SNPs.
• fst_mxl_eur_arc_snps_742kb: Fst(MXL,EUR) value for the 742kb region using archaic SNPs.
• fst_eas_eur_arc_snps_742kb: Fst(EAS,EUR) value for the 742kb region using archaic SNPs.
• n_seg_all_snps_72kb: Number of segregating sites in the 722kb region.
• pbs_all_snps_72kb: PBS(A=MXL,B=EAS,C=EUR) value for the 72kb region using all SNPs.
• fst_mxl_eas_all_snps_72kb: Fst(MXL,EAS) value for the 72kb region using all SNPs.
• fst_mxl_eur_all_snps_72kb: Fst(MXL,EUR) value for the 72kb region using all SNPs.
• fst_eas_eur_all_snps_72kb: Fst(EAS,EUR) value for the 72kb region using all SNPs.
• n_seg_arc_snps_72kb: Number of archaic SNPs segregating in the 72kb region.
• pbs_arc_snps_72kb: PBS(A=MXL,B=EAS,C=EUR) value for the 72kb region using archaic SNPs.
• fst_mxl_eas_arc_snps_72kb: Fst(MXL,EAS) value for the 72kb region using archaic SNPs.
• fst_mxl_eur_arc_snps_72kb: Fst(MXL,EUR) value for the 72kb region using archaic SNPs.
• fst_eas_eur_arc_snps_72kb: Fst(EAS,EUR) value for the 72kb region using archaic SNPs.

psuedo_ancestry_painting

archaic_psuedo_ancestry_painting_windows.tar.gz

archaic_psuedo_ancestry_painting_windows.tar.gz is the output from archaic_psuedo_ancestry_painting_windows_v_revisions.py found here.

Paths

• archaic_psuedo_ancestry_painting_windows.tar.gz
  • ./muc19/muc19_results/arcs_masked_no_aa/{cha,vin}_den_alt_pap_counts_chr{1..22}_72kb.txt.gz

{cha,vin}_den_alt_pap_counts_chr{1..22}_72kb.txt.gz

For each late Neanderthal ({cha,vin}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping 72kb window with the following columns:

• Column 1: Number of PAP sites.
• Column 2: Number of heterozygous sites.

tgp_archaic_psuedo_ancestry_painting_windows.tar.gz

tgp_archaic_psuedo_ancestry_painting_windows.tar.gz is the output from tgp_archaic_psuedo_ancestry_painting_windows_v_revisions.py found here.

Paths

• tgp_archaic_psuedo_ancestry_painting_windows.tar.gz
  • ./muc19/muc19_results/tgp_arcs_masked_no_aa/{den,alt,cha,vin}_mxl_yri_pap_counts_chr{1..22}_72kb.txt.gz

{cha,vin}_den_alt_pap_counts_chr{1..22}_72kb.txt.gz

For each archaic individual ({den,alt,cha,vin}), there is one corresponding file per autosome (chr{1..22}). Each row corresponds to a non-overlapping 72kb window with the following columns:

• Column 1: Number of PAP sites.
• Column 2: Number of heterozygous sites.

sequence_divergence

den_v_alt_divergence_windows.tar.gz

den_v_alt_divergence_windows.tar.gz is the output from arc_dip_v_arc_dip_divergence_windows_v_revisions.py found here.

Paths

• den_v_alt_divergence_windows.tar.gz
  • ./muc19/muc19_results/arcs_masked_no_aa/den_v_alt_pw_diffs_chr{1..22}_72kb.txt.gz

den_v_alt_pw_diffs_chr{1..22}_72kb.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. This file contains a single row, where each column in that row corresponds to the average number of pairwise differences between the Altai Denisovan's and Altai Neanderthal's two chromosomes per non-overlapping 72kb window.

sgdp_denisovan_sequence_divergence_at_denisovan_intro_tracts_in_papuans.tar.gz

sgdp_denisovan_sequence_divergence_at_denisovan_intro_tracts_in_papuans.tar.gz is the output from sgdp_denisovan_sequence_divergence_at_denisovan_intro_tracts_in_papuans_v_revisions.py found here.

Paths

• sgdp_denisovan_sequence_divergence_at_denisovan_intro_tracts_in_papuans.tar.gz
  • ./muc19/muc19_results/sgdp_den_masked_no_aa/{pap_ind}_hap{1,2}_den_pw_diffs_seq_div_at_den_intro_tracts_chr{1..22}.txt.gz

{pap_ind}_hap{1,2}_den_pw_diffs_seq_div_at_den_intro_tracts_chr{1..22}.txt.gz

For each Papuan individual ({pap_ind}), there is one corresponding file per autosome (chr{1..22}) for each haploid genome (hap{1,2}). Each row corresponds to a Denisovan introgressed tract for the corresponding haploid genome (hap{1,2}) in the respective Papuan individual ({pap_ind}) with the following columns:

• Column 1: The average number of pairwise differences between the Papuan individual's haplotype and the Altai Denisovan's two chromosomes.
• Column 2: The corresponding sequence divergence.

tgp_hap_v_arc_dip_divergence_windows.tar.gz

tgp_hap_v_arc_dip_divergence_windows.tar.gz is the output from tgp_hap_v_arc_dip_divergence_windows_v_revisions.py found here.

Paths

• tgp_hap_v_arc_dip_divergence_windows.tar.gz
  • ./muc19/muc19_results/tgp_den_masked_no_aa/den_hap_{1,2}_pw_diffs_chr{1..22}_{742,72}kb.txt.gz
  • ./muc19/muc19_results/tgp_alt_masked_no_aa/alt_hap_{1,2}_pw_diffs_chr{1..22}_{742,72}kb.txt.gz
  • ./muc19/muc19_results/tgp_cha_masked_no_aa/cha_hap_{1,2}_pw_diffs_chr{1..22}_{742,72}kb.txt.gz
  • ./muc19/muc19_results/tgp_vin_masked_no_aa/vin_hap_{1,2}_pw_diffs_chr{1..22}_{742,72}kb.txt.gz

{den,alt,cha,vin}_hap_{1,2}_pw_diffs_chr{1..22}_{742,72}kb.txt.gz

For each archaic individual ({den,alt,cha,vin}), there is one corresponding file per autosome (chr{1..22}) for each haploid genome (hap_{1,2}). Each row corresponds to a non-overlapping window ({742,72}kb). The columns correspond to the average number of pairwise differences between a 1000 Genomes Project individual's haplotype (hap_{1,2}) and the archaic individual's ({den,alt,cha,vin}) two chromosomes, in the same order as individuals appear in ./muc19/meta_data/tgp_mod.txt.

tgp_hap_v_arc_dip_divergence_windows.tar.gz

tgp_hap_v_arc_dip_divergence_windows.tar.gz is the output from tgp_hap_v_arc_psuedo_hap_divergence_windows_v_revisions.py found here.

Paths

• tgp_hap_v_arc_psuedo_hap_divergence_windows.tar.gz
  • ./muc19/muc19_results/tgp_cha_masked_no_aa/cha_hap_{1,2}_psuedo_hap_diffs_chr{1..22}_72kb.txt.gz
  • ./muc19/muc19_results/tgp_vin_masked_no_aa/vin_hap_{1,2}_psuedo_hap_diffs_chr{1..22}_72kb.txt.gz

{cha,vin}_hap_{1,2}_psuedo_hap_diffs_chr{1..22}_72kb.txt.gz

For each late Neanderthal ({cha,vin}), there is one corresponding file per autosome (chr{1..22}) for each haploid genome (hap_{1,2}). Each row corresponds to a non-overlapping 72kb window. The columns correspond to the average number of pairwise differences between a 1000 Genomes Project individual's haplotype (hap_{1,2}) and the late Neanderthal's ({cha,vin}) pseudo-haplotype, in the same order as individuals appear in ./muc19/meta_data/tgp_mod.txt.

afr_v_den_divergence_windows.tar.gz

afr_v_den_divergence_windows.tar.gz is the output from tgp_spop_v_arc_dip_divergence_windows_v_revisions.py found here.

Paths

• afr_v_den_divergence_windows.tar.gz
  • ./muc19/muc19_results/tgp_den_masked_no_aa/afr_den_avg_pw_diffs_chr{1..22}_72kb.txt.gz

afr_den_avg_pw_diffs_chr{1..22}_72kb.txt.gz

For each autosome (chr{1..22}), there is one corresponding file. This file contains one row, where each column corresponds to the average number of pairwise differences between all African chromosomes in the 1000 Genomes Project and the Altai Denisovan's two chromosomes per non-overlapping 72kb window.

vcf_data

Since ALL of the VCF files and bookkeeping information are well over 3TB, we provide the converted Zarr arrays, which are the output of vcf_to_zarr_v_revisions.py found here, as 99.99% of analyses are performed using these data. Additionally, in the following windowing subsubsection, we provide the corresponding bookkeeping files used in our analyses and include the raw bookkeeping files for the sake of completeness, which are located in bookkeeping.tar.gz. Note that all VCF files are formatted in accordance with the VCF specification, and the format of the raw bookkeeping files is described in the VCF processing scripts found here. The {prefix}.tar.gz files are named by the dataset ({prefix}) and, unless otherwise noted, contain the corresponding Zarr arrays for all autosomes (chr{1..22}).

Datasets & Paths

• arcs_masked_no_aa.tar.gz
  • All archaic individuals without ancestral allele calls. Individuals are in the following order: Altai Neanderthal, Chagyrskaya Neanderthal, Vindija Neanderthal, Altai Denisovan.
  • ./muc19/zarr_data/arcs_masked_no_aa_chr{1..22}.zarr
• arcs_masked_aa.tar.gz
  • All archaic individuals with ancestral allele calls. Individuals are in the following order: Altai Neanderthal, Chagyrskaya Neanderthal, Vindija Neanderthal, Altai Denisovan, and a placeholder individual "Ancestor" who is always homozygous for the ancestral allele.
  • ./muc19/zarr_data/arcs_masked_no_aa_chr{1..22}.zarr
• {den,alt,cha,vin}_masked_no_aa.tar.gz
  • den_masked_no_aa.tar.gz: Altai Denisovan without ancestral allele calls.
    • ./muc19/zarr_data/den_masked_no_aa_chr{1..22}.zarr
  • alt_masked_no_aa.tar.gz: Altai Denisovan without ancestral allele calls.
    • ./muc19/zarr_data/alt_masked_no_aa_chr{1..22}.zarr
  • cha_masked_no_aa.tar.gz: Chagyrskaya Neanderthal without ancestral allele calls.
    • ./muc19/zarr_data/cha_masked_no_aa_chr{1..22}.zarr
  • vin_masked_no_aa.tar.gz: Vindija Neanderthal without ancestral allele calls.
    • ./muc19/zarr_data/vin_masked_no_aa_chr{1..22}.zarr
• tgp_arcs_masked_no_aa.tar.gz
  • 1000 Genomes Project and all archaic individuals without ancestral allele calls. Individuals are in the following order: 1000 Genomes Project individuals (order as in ./muc19/meta_data/tgp_mod.txt), Altai Neanderthal, Chagyrskaya Neanderthal, Vindija Neanderthal, Altai Denisovan.
  • ./muc19/zarr_data/tgp_arcs_masked_no_aa_chr{1..22}.zarr
• tgp_{den,alt,cha,vin}_masked_no_aa.tar.gz
  • tgp_den_masked_no_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt) and the Altai Denisovan, without ancestral allele calls.
    • ./muc19/zarr_data/tgp_den_masked_no_aa_chr{1..22}.zarr
  • tgp_alt_masked_no_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt) and the Altai Neanderthal, without ancestral allele calls.
    • ./muc19/zarr_data/tgp_alt_masked_no_aa_chr{1..22}.zarr
  • tgp_cha_masked_no_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt) and the Chagyrskaya Neanderthal, without ancestral allele calls.
    • ./muc19/zarr_data/tgp_cha_masked_no_aa_chr{1..22}.zarr
  • tgp_vin_masked_no_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt) and the Vindija Neanderthal, without ancestral allele calls.
    • ./muc19/zarr_data/tgp_vin_masked_no_aa_chr{1..22}.zarr
• tgp_{den,alt,cha,vin}_masked_aa.tar.gz
  • tgp_den_masked_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt), the Altai Denisovan, and a placeholder individual "Ancestor" who is always homozygous for the ancestral allele.
    • ./muc19/zarr_data/tgp_den_masked_aa_chr{1..22}.zarr
  • tgp_alt_masked_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt), the Altai Neanderthal, and a placeholder individual "Ancestor" who is always homozygous for the ancestral allele.
    • ./muc19/zarr_data/tgp_alt_masked_aa_chr{1..22}.zarr
  • tgp_cha_masked_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt), the Chagyrskaya Neanderthal, and a placeholder individual "Ancestor" who is always homozygous for the ancestral allele.
    • ./muc19/zarr_data/tgp_cha_masked_aa_chr{1..22}.zarr
  • tgp_vin_masked_aa.tar.gz: 1000 Genomes Project (order as in ./muc19/meta_data/tgp_mod.txt), the Vindija Neanderthal, and a placeholder individual "Ancestor" who is always homozygous for the ancestral allele.
    • ./muc19/zarr_data/tgp_vin_masked_aa_chr{1..22}.zarr
• sgdp_arcs_masked_no_aa.tar.gz
  • Simon's Genome Diversity Project and all archaic individuals without ancestral allele calls. Individuals are in the following order: Simon's Genome Diversity Project individuals (order as in ./muc19/meta_data/sgdp.txt), Altai Neanderthal, Chagyrskaya Neanderthal, Vindija Neanderthal, Altai Denisovan.
  • ./muc19/zarr_data/sgdp_arcs_masked_no_aa_chr{1..22}.zarr
• sgdp_{den,alt,cha,vin}_masked_no_aa.tar.gz
  • sgdp_den_masked_no_aa.tar.gz: Simon's Genome Diversity Project (order as in ./muc19/meta_data/sgdp.txt) and the Altai Denisovan, without ancestral allele calls.
    • ./muc19/zarr_data/sgdp_den_masked_no_aa_chr{1..22}.zarr
  • sgdp_alt_masked_no_aa.tar.gz: Simon's Genome Diversity Project (order as in ./muc19/meta_data/sgdp.txt) and the Altai Neanderthal, without ancestral allele calls.
    • ./muc19/zarr_data/sgdp_alt_masked_no_aa_chr{1..22}.zarr
  • sgdp_cha_masked_no_aa.tar.gz: Simon's Genome Diversity Project (order as in ./muc19/meta_data/sgdp.txt) and the Chagyrskaya Neanderthal, without ancestral allele calls.
    • ./muc19/zarr_data/sgdp_cha_masked_no_aa_chr{1..22}.zarr
  • sgdp_vin_masked_no_aa.tar.gz: Simon's Genome Diversity Project (order as in ./muc19/meta_data/sgdp.txt) and the Vindija Neanderthal, without ancestral allele calls.
    • ./muc19/zarr_data/sgdp_vin_masked_no_aa_chr{1..22}.zarr
• tgp_mod_no_aa.tar.gz
  • 1000 Genomes Project without ancestral allele calls. Individuals are in the same order as they appear in ./muc19/meta_data/tgp_mod.txt.
  • ./muc19/zarr_data/tgp_mod_no_aa_chr{1..22}.zarr
• tgp_mod_aa.tar.gz
  • 1000 Genomes Project with ancestral allele calls. Individuals are in the same order as they appear in ./muc19/meta_data/tgp_mod.txt, and a placeholder individual "Ancestor" who is always homozygous for the ancestral allele.
  • ./muc19/zarr_data/tgp_mod_aa_chr{1..22}.zarr
• cha_phased_ref_panel_all_inds.tar.gz
  • Corresponding output from BEAGLE before read-based phasing for the focal 72kb region, without ancestral allele calls. Individuals are in the following order: Altai Neanderthal, Chagyrskaya Neanderthal, Altai Denisovan.
  • ./muc19/zarr_data/cha_phased_ref_panel_all_inds.zarr
    • Note that this is a single Zarr array for the focal 72kb region.
  • The input VCF file can be found here.
• vin_phased_ref_panel_all_inds.tar.gz
  • Corresponding output from BEAGLE before read-based phasing for the focal 72kb region, without ancestral allele calls. Individuals are in the following order: Altai Neanderthal, Vindija Neanderthal, Altai Denisovan.
  • ./muc19/zarr_data/vin_phased_ref_panel_all_inds.zarr
    • Note that this is a single Zarr array for the focal 72kb region.
  • The input VCF file can be found here.

windowing

arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz

arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/arcs_masked_no_aa/72kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/arcs_masked_no_aa/72kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/arcs_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz

72kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) 72kb non-overlapping windows, with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• ALT: Altai Neanderthal effective sequence length.
• CHA: Chagyrskaya Neanderthal effective sequence length.
• VIN: Vindija Neanderthal effective sequence length.
• DEN: Altai Denisovan effective sequence length.
• DEN-ALT: Effective sequence length for Altai Denisovan-Altai Neanderthal comparisons.
• DEN-CHA: Effective sequence length for Altai Denisovan-Chagyrskaya Neanderthal comparisons.
• DEN-VIN: Effective sequence length for Altai Denisovan-Vindija Neanderthal comparisons.
• ALT-CHA: Effective sequence length for Altai Neanderthal-Chagyrskaya Neanderthal comparisons.
• ALT-VIN: Effective sequence length for Altai Neanderthal-Vindija Neanderthal comparisons.
• CHA-VIN: Effective sequence length for Chagyrskaya Neanderthal-Vindija Neanderthal comparisons.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

72kb_esl_qced_nonoverlapping_variant_windows.txt.gz

Indices of 72kb variant windows of comparable effective sequence length, used for subsetting 72kb_nonoverlapping_variant_windows.csv.gz.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with the following columns:

• Column 1: Altai Neanderthal effective sequence length.
• Column 2: Chagyrskaya Neanderthal effective sequence length.
• Column 3: Vindija Neanderthal effective sequence length.
• Column 4: Altai Denisovan effective sequence length.
• Column 5: Effective sequence length for Altai Denisovan-Altai Neanderthal comparisons.
• Column 6: Effective sequence length for Altai Denisovan-Chagyrskaya Neanderthal comparisons.
• Column 7: Effective sequence length for Altai Denisovan-Vindija Neanderthal comparisons.
• Column 8: Effective sequence length for Altai Neanderthal-Chagyrskaya Neanderthal comparisons.
• Column 9: Effective sequence length for Altai Neanderthal-Vindija Neanderthal comparisons.
• Column 10: Effective sequence length for Chagyrskaya Neanderthal-Vindija Neanderthal comparisons.

arcs_masked_aa_window_info_and_eff_seq_len.tar.gz

arcs_masked_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• arcs_masked_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/arcs_masked_aa/72kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/arcs_masked_aa/72kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/arcs_masked_aa/{742,72}kb_eff_seq_len.txt.gz

72kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) 72kb non-overlapping windows, with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• ALT: Altai Neanderthal effective sequence length.
• CHA: Chagyrskaya Neanderthal effective sequence length.
• VIN: Vindija Neanderthal effective sequence length.
• DEN: Altai Denisovan effective sequence length.
• DEN-ALT: Effective sequence length for Altai Denisovan-Altai Neanderthal comparisons.
• DEN-CHA: Effective sequence length for Altai Denisovan-Chagyrskaya Neanderthal comparisons.
• DEN-VIN: Effective sequence length for Altai Denisovan-Vindija Neanderthal comparisons.
• ALT-CHA: Effective sequence length for Altai Neanderthal-Chagyrskaya Neanderthal comparisons.
• ALT-VIN: Effective sequence length for Altai Neanderthal-Vindija Neanderthal comparisons.
• CHA-VIN: Effective sequence length for Chagyrskaya Neanderthal-Vindija Neanderthal comparisons.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

72kb_esl_qced_nonoverlapping_variant_windows.txt.gz

Indices of 72kb variant windows of comparable effective sequence length, used for subsetting 72kb_nonoverlapping_variant_windows.csv.gz.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with the following columns:

• Column 1: Altai Neanderthal effective sequence length.
• Column 2: Chagyrskaya Neanderthal effective sequence length.
• Column 3: Vindija Neanderthal effective sequence length.
• Column 4: Altai Denisovan effective sequence length.
• Column 5: Effective sequence length for Altai Denisovan-Altai Neanderthal comparisons.
• Column 6: Effective sequence length for Altai Denisovan-Chagyrskaya Neanderthal comparisons.
• Column 7: Effective sequence length for Altai Denisovan-Vindija Neanderthal comparisons.
• Column 8: Effective sequence length for Altai Neanderthal-Chagyrskaya Neanderthal comparisons.
• Column 9: Effective sequence length for Altai Neanderthal-Vindija Neanderthal comparisons.
• Column 10: Effective sequence length for Chagyrskaya Neanderthal-Vindija Neanderthal comparisons.

{den,alt,cha,vin}_masked_no_aa_window_info_and_eff_seq_len.tar.gz

arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• den_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/den_masked_no_aa/72kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/den_masked_no_aa/72kb_esl_qced_nonoverlapping_{invariant,variant}_windows.txt.gz
  • ./muc19/windowing/den_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• alt_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/alt_masked_no_aa/72kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/alt_masked_no_aa/72kb_esl_qced_nonoverlapping_{invariant,variant}_windows.txt.gz
  • ./muc19/windowing/alt_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• cha_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/cha_masked_no_aa/72kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/cha_masked_no_aa/72kb_esl_qced_nonoverlapping_{invariant,variant}_windows.txt.gz
  • ./muc19/windowing/cha_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• vin_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/vin_masked_no_aa/72kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/vin_masked_no_aa/72kb_esl_qced_nonoverlapping_{invariant,variant}_windows.txt.gz
  • ./muc19/windowing/vin_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz

72kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) 72kb non-overlapping windows, with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• {ARC}: Effective sequence length with respect to the given archaic individual (e.g., DEN for Altai Denisovan).
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

72kb_esl_qced_nonoverlapping_{invariant,variant}_windows.txt.gz

Indices of non-overlapping 72kb invariant (_invariant_) and variant (_variant_) windows of comparable effective sequence length, used for subsetting the corresponding 72kb_nonoverlapping_{invariant,variant}_windows.csv.gz file.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with respect to the given archaic individual—singe value per file.

tgp_arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz

tgp_arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• tgp_arcs_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_arcs_masked_no_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_arcs_masked_no_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_arcs_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz

{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) per window size ({742,72}kb), with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• ALT: Effective sequence length for Altai Neanderthal comparisons.
• CHA: Effective sequence length for Chagyrskaya Neanderthal comparisons.
• VIN: Effective sequence length for Vindija Neanderthal comparisons.
• DEN: Effective sequence length for Altai Denisovan comparisons.
• DEN-ALT: Effective sequence length for Altai Denisovan-Altai Neanderthal comparisons.
• DEN-CHA: Effective sequence length for Altai Denisovan-Chagyrskaya Neanderthal comparisons.
• DEN-VIN: Effective sequence length for Altai Denisovan-Vindija Neanderthal comparisons.
• ALT-CHA: Effective sequence length for Altai Neanderthal-Chagyrskaya Neanderthal comparisons.
• ALT-VIN: Effective sequence length for Altai Neanderthal-Vindija Neanderthal comparisons.
• CHA-VIN: Effective sequence length for Chagyrskaya Neanderthal-Vindija Neanderthal comparisons.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz

Indices of variant windows per window size ({742,72}kb) of comparable effective sequence length, used for subsetting {742,72}kb_nonoverlapping_variant_windows.csv.gz.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with the following columns:

• Column 1: Effective sequence length for Altai Neanderthal comparisons.
• Column 2: Effective sequence length for Chagyrskaya Neanderthal comparisons.
• Column 3: Effective sequence length for Vindija Neanderthal comparisons.
• Column 4: Effective sequence length for Altai Denisovan comparisons.
• Column 5: Effective sequence length for Altai Denisovan-Altai Neanderthal comparisons.
• Column 6: Effective sequence length for Altai Denisovan-Chagyrskaya Neanderthal comparisons.
• Column 7: Effective sequence length for Altai Denisovan-Vindija Neanderthal comparisons.
• Column 8: Effective sequence length for Altai Neanderthal-Chagyrskaya Neanderthal comparisons.
• Column 9: Effective sequence length for Altai Neanderthal-Vindija Neanderthal comparisons.
• Column 10: Effective sequence length for Chagyrskaya Neanderthal-Vindija Neanderthal comparisons.

tgp_{den,alt,cha,vin}_masked_no_aa_window_info_and_eff_seq_len.tar.gz

tgp_{den,alt,cha,vin}_masked_no_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• tgp_den_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_den_masked_no_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_den_masked_no_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_den_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• tgp_alt_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_alt_masked_no_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_alt_masked_no_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_alt_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• tgp_cha_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_cha_masked_no_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_cha_masked_no_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_cha_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• tgp_vin_masked_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_vin_masked_no_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_vin_masked_no_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_vin_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz

{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) per window size ({742,72}kb), with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• {ARC}: Effective sequence length with respect to the given archaic individual (e.g., DEN for Altai Denisovan).
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz

Indices of variant windows per window size ({742,72}kb) of comparable effective sequence length, used for subsetting {742,72}kb_nonoverlapping_variant_windows.csv.gz.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with respect to the given archaic individual—singe value per file.

tgp_{den,alt,cha,vin}_masked_aa_window_info_and_eff_seq_len.tar.gz

tgp_{den,alt,cha,vin}_masked_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• tgp_den_masked_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_den_masked_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_den_masked_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_den_masked_aa/{742,72}kb_eff_seq_len.txt.gz
• tgp_alt_masked_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_alt_masked_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_alt_masked_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_alt_masked_aa/{742,72}kb_eff_seq_len.txt.gz
• tgp_cha_masked_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_cha_masked_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_cha_masked_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_cha_masked_aa/{742,72}kb_eff_seq_len.txt.gz
• tgp_vin_masked_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_vin_masked_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_vin_masked_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_vin_masked_aa/{742,72}kb_eff_seq_len.txt.gz

{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) per window size ({742,72}kb), with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• {ARC}: Effective sequence length with respect to the given archaic individual (e.g., DEN for Altai Denisovan).
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz

Indices of variant windows per window size ({742,72}kb) of comparable effective sequence length, used for subsetting {742,72}kb_nonoverlapping_variant_windows.csv.gz.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with respect to the given archaic individual—singe value per file.

sgdp_{den,alt,cha,vin}_masked_no_aa_eff_seq_len.tar.gz

sgdp_{den,alt,cha,vin}_masked_no_aa_eff_seq_len.tar.gz is the output from compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• sgdp_den_masked_no_aa_eff_seq_len.tar.gz
  • ./muc19/windowing/sgdp_den_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• sgdp_alt_masked_no_aa_eff_seq_len.tar.gz
  • ./muc19/windowing/sgdp_alt_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• sgdp_cha_masked_no_aa_eff_seq_len.tar.gz
  • ./muc19/windowing/sgdp_cha_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz
• sgdp_vin_masked_no_aa_eff_seq_len.tar.gz
  • ./muc19/windowing/sgdp_vin_masked_no_aa/{742,72}kb_eff_seq_len.txt.gz

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with respect to the given archaic individual—singe value per file.

tgp_mod_no_aa_window_info_and_eff_seq_len.tar.gz

tgp_mod_no_aa_window_info_and_eff_seq_len.tar.gz is the output from consolidate_all_archaics_tgp_sgdp_windows_v_revisions.py and compute_region_effective_sequence_lengths_v_revisions.py found here.

Paths

• tgp_mod_no_aa_window_info_and_eff_seq_len.tar.gz
  • ./muc19/windowing/tgp_mod_no_aa/{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz
  • ./muc19/windowing/tgp_mod_no_aa/{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz
  • ./muc19/windowing/tgp_mod_no_aa/{742,72}kb_eff_seq_len.txt.gz

{742,72}kb_nonoverlapping_{invariant,variant}_windows.csv.gz

One file for invariant (_invariant_) and one for variant (_variant_) per window size ({742,72}kb), with the following columns:

• IDX: Window index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• HUM: Effective sequence length.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).

Note: If only column headers are present in the invariant file (_invariant_), no invariant windows passed initial QC.

{742,72}kb_esl_qced_nonoverlapping_variant_windows.txt.gz

Indices of variant windows per window size ({742,72}kb) of comparable effective sequence length, used for subsetting {742,72}kb_nonoverlapping_variant_windows.csv.gz.

{742,72}kb_eff_seq_len.txt.gz

Effective sequence lengths for the focal regions ({742,72}kb) with respect to the given archaic individual—singe value per file.

sgdp_denisovan_intro_tracts_in_papuans_qc_info.tar.gz

sgdp_denisovan_intro_tracts_in_papuans_qc_info.tar.gz is the output from consolidate_sgdp_denisovan_intro_tracts_in_papuans_v_revisions.py found here.

Paths

• sgdp_denisovan_intro_tracts_in_papuans_qc_info.tar.gz
  • ./muc19/windowing/sgdp_den_masked_no_aa/{pap_ind}_hap{1,2}_den_intro_{invariant,variant}_tracts.csv.gz

sgdp_denisovan_intro_tracts_in_papuans_qc_info.tar.gz

For each Papuan individual ({pap_ind}), there is one file for invariant (_invariant_) and one for variant (_variant_) for each haploid genome (hap{1,2}), with the following columns:

• IDX: Denisovan introgressed tract index with respect to the CHR column.
• CHR: Chromosome.
• START: Start position (inclusive).
• STOP: Stop position (inclusive).
• DEN: Effective sequence length for Altai Denisovan comparisons.
• S: Number of segregating sites.
• QC: QC condition (numeric, e.g., 1 if true, 0 if false).